Category: Features

Work in the Future: Technological Opportunity or Human Obsolescence in Science Fiction and Reality

Tiff Graham

Everybody knew what was supposed to happen. Technological forecasters predicted it. Economic prognosticators confirmed the warnings. Politicians viewed with alarm. The displacement of flesh and blood works by ugly, anthropomorphic machines meant violence! The Luddites would rise again, and the factory aisles would run sticky with lubricating oil. But it didn’t happen.

–Frederick Pohl’s Midas World (1983:29)

Conversation starter questions such as “what kind of work do you do?” or “what do you do for a living?” are commonplace as people often assume a person occupies time with some sort of work activity. Why that work is performed may be due to financial security, a sense of purpose, a need to serve/help, or simply the work opportunity arose (Duncan; Gross). Initially, a person will learn specific jobs tasks and often spend years maintaining employment in a particular occupational field. Yet with the introduction of new advanced technologies meant to provide greater efficiency, reduction of the more repetitive and mundane job tasks, and safer working conditions, it is possible that various forms of work will be transformed or at risk for elimination in the future. None of this is new knowledge, as history has shown technological advancements often reshape how people work and live. From the First Industrial Revolution (mid-1700s to early 1800s), the use of steam engines and mechanization increased productivity, making some manual labor jobs no longer needed; to the Second Industrial Revolution (late 1800s to early 1900s), where electricity, telephones, and automobiles created new job positions and simultaneously eliminated other ones (Olsen). The Third Industrial Revolution, referred to as the Digital Age, from the 1960s to 2000s, brought in computers, various electronics, automated processes, and the Internet which altered how jobs were performed, while also creating a more globally accessible job market and eliminating occupations that a computer could do more efficiently. The Fourth Industrial Revolution, referred to as the SecondMachine Age, from 2010 to our present, has introduced the world to more advanced AI, robotic machines, smart technology, and other scientific innovations that are currently reshaping work experience in both beneficial and problematic ways (Byrnjolfsson and McAfee; Penprase; Schwab).

By focusing on AI and robotic machine technology associated with the Fourth Industrial Revolution (4IR), this paper draws attention to the transformation of jobs across the business, healthcare, entertainment, restaurant, and government sectors as expectations and anxieties arise with the evolving relationship people have to their new technological collaborators and potential rivals. Reality based examples and science fiction/speculative fiction stories of mundane, utopian, and dystopian futures provide evidence and possibilities of what job seekers of tomorrow may need to consider.

Hype, History, and the Current State of Technology

As societies are becoming more attune to these new 4IR technologies reshaping work and everyday life, the voices of the corporate tech leadership are also gaining attention. There are frequent announcements of the inevitability of AI and robotic tech reach; technologies’ beneficent power to improve the world; and, in some cases its dangers to society while concurrently gaining more publicity. When Bill Gates, cofounder of Microsoft, was interviewed on a late-night show in 2025, he said that AI would “solve problems, enable us to work fewer days, and offer free and commonplace medical advice and tutoring.” He also suggested that we will “not need humans for most things, but we will decide what those things are” (Gates). Other tech leaders have proclaimed AI agents, also called Agentic AI systems, are the future of personal assistants and members of the workforce (Huskins). These autonomous AI entities will work for us using all the available Internet data, software tools, and personal information gathered to meet any business needs in order to serve us better (Metz and Weise). And Jeff Bezos, founder of Amazon and Blue Origin, has suggested that tech will increase human labor and opportunity, though his distribution centers seem to do the opposite as robotic automation replaces human jobs (Bezos; McCallum; Weise).

With much of the techno-optimism rhetoric, there is a great deal of utopian thinking around the new technologies, though some are cautioning governments, businesses, and society to consider the potential unwanted consequences. In the book The Workplace of the Future: The Fourth Industrial Revolution, the Precariat and the Death of Hierarchies, it’s suggested that we are entering a more insecure job market as robotization and digitization replace the human workforce. We could say that job displacement due to new technologies has always been a concern from the earlier industrial revolution with the Luddite Movement (1811-16) to Karl Marx addressing the impact of industrial capitalism (Das Kapital, 1867), and 19^th and 20^th century laborers protesting railroads, assembly lines, and other machine technology impacting traditional forms of work of the time (Johannessen). There is even a 1930s term, ‘technological unemployment, coined by the economist John Maynard Keyes to describe the effect, though in his essay, “Economic Possibilities for our Grandchildren,” he also envisions an optimistic future where this technology replacing human effort is a temporary step to a better standard of living with humans working less (Schwab; Keyes 1930:363).

Many technological advancements have historically led to changes in the workspace, yet this technological age is different for some critics. It has been described as more disruptive because it can transform jobs associated with creativity, knowledge, and information processing, once a domain of mainly human minds. In books such as Only Humans Need Apply, Winners & Losers in the Age of Smart Machines by Davenport and Kirby, concerns are raised about jobs associated with “knowledge workers” that include lawyers, accountants, doctors, scientists, and various white-collar professions. And now, due to the generative AI text and image programs, even creative artists are feeling their occupational livelihood threatened.

Are these alarm bells we should pay attention to, or is it just a matter of perspective? For example, Sam Altman, CEO of Open AI, has an optimistic spin on the AI revolution, suggesting it is not a new industrialization period but should be seen as more of a renaissance, a time of enlightenment (Barlow). Elon Musk, CEO of Tesla and SpaceX, expects that AI will continue to do things better than humans and his humanoid robots like Optimus Bot will be deployed everywhere in society and many industries (Elon Buzz; Carter). Tech leaders often talk favorably about these new AI and robotic machine technologies, referring to the machines as collaborators, assistants, and agents that will augment us and make the world better. I’ve also heard educators, professionals from various fields, and everyday individuals refer to AI positively as a partner, therapist, mentor, companion, and even as a friend (Brockes; Tangermann; Williams). In addition, educational institutions and cities are championing greater investment, knowledge, and skill building with AI tools and technology company partnerships. For example, The Chronicle of Higher Education articles and webinars feature AI-themed literature and virtual forums (e.g., “AI on Campus”; “New Academic Programs”). Florida State University has promoted an Artificial Intelligence Initiative across the curriculum with donor support from NVIDIA (Southworth et al.). Harvard Business School’s online blog includes advice about the future of AI-powered businesses (Gibson). California State Universities have joined numerous leading tech companies (i.e., OpenAI, Intel, Meta, etc.) on advisory boards “to help identify AI skills needed in the California workforce and provide advice on how best to teach them” (Watanabe). Cities such as Palm Springs, California have hosted an annual AI Expo (2025-2026) to “explore artificial intelligence’s potential to reshape the desert community’s economic future” (Palm Springs Chamber of Commerce; Valley Voice Media) and according to a World Economic Forum article, various global cities in Argentina, Netherlands, Singapore, United States are incorporating AI strategies for projects (North).

As AI and robotic technologies become more embedded in every aspect of work and social life, opting out might prove increasingly difficult (Bilton). In the book Working with AI: Real Stories of Human-Machine Collaboration (2022), Davenport and Miller identify a number of employers who have adopted AI-based systems. For example, in the underwriter profession, where customers apply for life insurance policies, these businesses can use an AI system that automatically reviews applications and client information, simultaneously cross-referencing data about risks and underwriter rules, enabling a quicker turnaround (Davenport and Miller 36:2022). This process allows the business to reserve human labor for the more complex decision-making, something often repeated when advocating for AI (Davenport and Miller 37:2022). While the cost-saving benefits are present, there are downsides, such as what if people are not given entry-level work, how will they gain the experience to become the experts who deal with complex decision-making. And when AI and robotics are used in workplaces, it does raise the question of who truly benefits in the long term. Will we all benefit from the outsourcing, augmenting, and leveraging of new technologies to solve problems or are there consequences we should pay attention to? In the marketing and creative industry field, producers of generative AI content iterate quicker, with multiple versions/designs/ideas delivered to customers and consumers, but at what point do the graphic designers, writers, and marketing individuals no longer have their jobs or find themselves in lower pay or lower skill jobs monitoring AI systems versus engaging in creative thinking. In addition, in the health industry, AI systems are employed in diagnostic imaging, medical transcription, and other services, which seems promising alongside human expertise, but does it mean radiologists and therapists need to reconsider their job market opportunities along with hospital nurses who may find their duties shifted to more management of technologies (Ackermann).

Futuristic Scenarios Sprinkled with Reality

Possibly, this is all just another stage in human evolution where we will adapt and carry on in the 4IR-Renaissance age outsourcing, augmenting, and leveraging our new technologies to solve problems before we enter Ray Kurzweil’s 5^th and 6^th epoch stages of the singularity; or maybe we should pay attention to what may become irreversible consequences of these technological advancements (Kurzweil 2005). By building a futures focused mindset that includes some science fiction and speculative fiction stories, it may help us better envision those preferrable, probable, possible, or seemingly impossible scenarios associated with work in the future (Balagtas 2024:78).

In the short video, “TempBot” (2006), directed by Neill Blomkamp, a humanoid robot is trucked in to perform temp work at a credit union. Human office workers barely pay attention to the walking metal robot as it uses the copy machine and types on a computer while sitting in a cubicle. As the audience, we see the robot’s perspective through its computer screen vision, a Version 3.02 model, overlayed with task commands and drop-down menus of information interpreting human words, actions, and materials. The workload and productivity speed for the humans and robot are initially equivalent. Then one day, the robot speeds up its productivity as it becomes obsessed with the new human HR manager who pays attention to it. It works faster to impress her while also stalking her like a jealous romantic mate, that is until a work social event when it inappropriately touches the HR manager’s breast, leading to a demotion back to the realm of robots-only offices. This particular story of a robot working in an office is humorous and not too spectacular nor much to fear, apart from its unexpected sentient misconduct.

From a real-world perspective, maybe robots will take on human jobs, but is it something we should be more worried about? In a 2025 news story/podcast from the NPR Short Wave science program, it mentions that humanoid robots are not actually at this level of functioning independently, as it takes many hours to build and train due to changing environments (Brumfiel et al.; Brumfiel). A Berkeley scientist and cofounder of Ambi Robotics, Ken Goldberg, further suggests that with robots, it’s not the same as with the AI chatbots where “they scooped up pretty much the entire Internet to train themselves how to write sentences and draw pictures,” whereas with robot data, it is limited (Brumfiel et al.; Brumfiel). However, there is plenty of robot hype in the news with robotic demonstrations, tech conferences, humans reclassified in jobs as robot wranglers and robot trainers/cyber-laborers in arm farms, along with the extensive research presented in Morgan Stanley’s financial investment report about the top 100 companies that could contribute to advanced humanoid development (Christopher “Delivery robots”; “Why hundreds”; Morgan Stanley; Zhou and Lo). On the other hand, with the generative AI programs, it does seem that knowledge workers should be worried as AI systems often can research, reason, compute, and output patterns and decisions based on data much more efficiently than humans.

If this is a harbinger of the future, what can humans do to save their jobs from machines in the future? In the science fiction animation, “Seniors 3000” (2022), directed by Julien David, the solution for technology taking jobs is to adapt oneself into a robotic cyborg. The story opens with an office boss requiring his employees to be digitally savvy, and if they can’t, then they need to retire. Marlene, an older office worker cannot handle the Bluetooth element of the newest copiers. She is forced to leave her job. She finds her old printer which somehow alters her DNA, transforming her into a printer cyborg that can scan, copy, print, upload .pdf copies, and spit out paper copies instantly through her mouth. The boss then greedily profits from her robotic adaptation. He soon realizes that Marlene can also transform others into cyborgs. He markets her to the French government’s Minister of Work and Profit, saying that he can create workers “requiring no payroll taxes, no paid vacations, and it’s all voluntary.” More retirees are transformed into cyborgs as TVs, floor fans, robotic surgeons, and other technology. But soon after, Marlene’s tech body disfunctions, and she is disposed of with other obsolete humans who have become cyborgs. Eventually, Marlene fights back, leading these obsolete cyborgs in a revolution against those in power. A science fiction story like “Seniors 3000” visually entertains, while also engages audiences to reflect on the embedded social commentary related to themes of aging, human obsolescence, and worker resistance.

Another speculative example is “B.E.N. Bionically Engineered Nursing” (2016), sponsored by the Society of Saint-Vincent-De-Paul. This short video raises the question, what jobs should be given over to AI and robots? On-screen, we see B.E.N., a white, puffy humanoid robot with big, circular, dew-drop black eyes, wearing a blue nurse’s shirt. It cares daily for an older woman named Claudine in her family home, providing nutritious meals, administering medicines, and even entertaining her with dancing. One morning, we see Claudine lying in bed and staring absently ahead in a way that could be interpreted as feeling sad and lonely, as the night before we saw a picture on her nightstand of what could have been her former husband. Upon seeing her in bed, the robot repeatedly says, “Claudine, would you like to get up now, I am here to assist you” and Claudine, physically unresponsive, maintains her absent stare. Later, at the breakfast table, Claudine tells B.E.N. she needed that quiet moment earlier in the morning. The robot, while helpful, doesn’t seem to provide nuanced emotional support apart from what it’s programmed to do. At the end of the short video, a service message appears on the screen displaying the text, “Today, companion robots are being introduced to assist lonely people,” followed by “At Society of Saint-Vincent-De-Paul, we think that only human beings can help in fighting loneliness.” This speculative public service announcement in 2016 reflected a particular perspective of the times, but we can now see more recently that attitudes are changing in the healthcare sector as various AI and robotic models are utilized in reality.

Robots are currently featured in healthcare articles about medical care facilities and home healthcare services. In a Nurse.org article, “This Humanoid AI Robot Is Being Tested in Hospitals-Plus 7 More Transforming Healthcare” by Sarah Falcone, the robots are described as “collaborators, not replacements” and are said to “free up nurses to perform specialized interventions.” One robot featured was Moxi from the US-based Diligent Healthcare, which is said to roam autonomously, deliver lab specimens, and greet patients (Burke, Falcone). Other types of robots mentioned help answer people’s questions, provide emotional support (e.g., robot seal Paro and robot Pepper) and transport supplies, food trays, and samples in the healthcare setting (Burke, Falcone). And for seniors needing home healthcare, the ElliQ by Intuition Robotics is promoted as a social and health coach device initially provided to healthcare organizations (Broadbent et al.). Some recent testimonies by customers in health news websites and on the ElliQ company site suggests a digital companion can help with loneliness and overall wellbeing (ElliQ, Lynn).

In a different work sector, the restaurant industry, AI and robotic implementation is also being promoted. The Spoon, a food technology podcast and website, has featured tech innovations, from AI drive-thru translator assistants at Wendy’s fast food to other robotic AI culinary technology (Wolf). While it’s not clear if everyone welcomes the AI and robotic technology in the kitchen, it is used in some restaurants. A restaurant in South Korea called Munmak uses a ramen-preparing robotic machine. A worker interviewed said, ‘It reduced the workload,” but also suggested there is a “loss of feeling pride in cooking the food” (Kim, “Robot Chefs”). In Japan, the DAWN Avatar robot café uses humanoid robots to serve, greet, and make food recommendations. These robots are not autonomous, but rather, are operated remotely by disabled humans (Steen). With this interconnectedness of AI and robotic machines in the food industry, it seems possible that humans in the future could work alongside robots or in some situations be replaced by them.

The science fiction short video “The Chef” (2021), directed by Hao Zheng and written by Ithaca Deng and Leqi Vanessa Kong, challenges this use of robotic technology and the potential replacement of humans in restaurants. It begins with a restaurant owner escorting William, a humanoid robot, to the kitchen to train under the older chef named Chef Pu. Initially, the chef is reluctant in teaching this machine as he says, “Chinese cooking is not science; it’s a feeling” as William asks for specific measurements in cooking braised meatball and tofu dish and other recipes. Meanwhile, the young human cooking assistant to the chef glares repeatedly at this humanoid assisting the chef. Later, the chef joins the human kitchen staff outside and comforts the younger assistant saying, “Don’t worry, cooking is meant for humans… just work harder, you won’t be replaced.” We soon overhear in a broadcast news story that humans are being replaced as “factory workers, farmers, and truck drivers protest worsening conditions” and others are organizing protest movements that advocate destroying robots in order to get jobs back. As time passes, we see the chef taking a liking to William as it is shown to be more reliable, curious, and attentive than the human assistant. In a scene at the food night market, the chef and William walk together while the chef cheerfully and nostalgically talks about ingredients and recipes. He also seems to be considering William as his eventual replacement when he retires. Shortly after the walk, protestors see the chef with William and attack and destroy the humanoid William. One of these protesters is the chef’s human kitchen assistant, who afterwards offers a saddened chef a ride home on a motorbike.

It’s a little confusing in the story and in a real-world sense whether we should welcome or despise these AI and robotic machines. What do we want from our machines? Maybe it’s efficiency and reliability, or perhaps it fills an emotional void where humans feel neglected. For a business owner, the financial cost-saving aspect of machines prevails. For others, it may be that AI or robotic machines provide something else, such as assistance and companionship, where humans are not as dependable. A story like “The Chef” draws attention to many of these issues as well as the concern about robots taking jobs of younger workers and how human attitudes may change with time and perspective.

A science fiction story about a different work sector, the arts industry, is “Real Artists” (2017), a short video directed by Cameo Wood and written by Cameo Wood and Ken Liu. The camera follows a young twenty something female filmmaker/graphic designer/storyteller interviewing for an entertainment industry job. It seems like a promising opportunity until she learns the film process involves an AI machine called Big Semi. The machine collates the emotional data of people in order to generate multiple film versions that eventually becomes what is considered the best film version. Upon seeing these other creative types sitting in a dark screening room, digitally connected to the AI machine via external body gadgetry on the temple and wristband, the interviewee incredulously comments, “I’m sorry all of Semafore films are essentially made by an AI?” The executive proudly responds, “It’s a process that works–nudging responses to fit a known emotional cord is nothing more than an optimization problem, and Big Semi is excellent at solving them.”

This filmmaking process depicted in “Real Artists” involves humans as mere cogs in an AI machine, no longer individuals but instead part of a hive mind linked to the AI machine. It’s explained to the interviewee that the human mind is repeatedly erased to create a tabula rasa, a blank slate. This process enables the machine to collect fresh, emotional data daily to generate multiple iterations of a story concept and basic plot all rendered using stock characters and dialogue till the best film is statistically achieved.

By reflecting on today’s real-life generative AI software landscape in the U.S. and globally, we can see how these tools are becoming more widely accepted in creative fields like the entertainment and marketing sectors. And for many, this technology is eagerly welcomed. For example, in a MIT Technology Review issue about creativity in the age of AI, the South Korean cartoonist Lee Hyun-se envisions AI giving his archival data of 5000 comics a “kind of immortality” in that AI can be used to develop future iterations of his characters and worldview (Kim, “Generative AI”). For other visual artists and writers, these large language model systems that generate AI art forms are useful but it has been suggested they are not as personally gratifying when art is reduced to an AI calculation (Kim, “Generative AI”). In recent years, writers, actors, animators, and artists have even reacted by protesting and boycotting AI work (Lee).

Maybe this is the future we can’t avoid. Plenty of science fiction and speculative fiction stories show us these utopian and dystopian versions of a world where AI and robots are in the workforce, and some of these scenarios reflect a bit of our reality. Though I hope we are not on the road to Frederick Pohl’s Midas World (1983), but it might be helpful to familiarize oneself with the literature where human adoption of AI and robotics ultimately leads to a government run by machines and humans no longer needed. From simple factory and household chore robots to doctors and government leader robots, the robots in this book are shown displacing humans. In chapter 3, “Servant of the People” of Midas World, originally published in Analog magazine, a human Congressman named O’Hare believes a human touch will always be needed, even with the abundance of robots. He’s unconcerned about his competitor, a small city robot Mayor campaigning for his seat. In a debate, O’Hare believes he is winning over voters; however, the robot seems to appeal to the crowds equally and can even switch out its data modules for whatever knowledge or memory reference is required. The robot, at one point, praises its human opponent for sponsoring Robot ERA rights and the elimination of mechanical and organic status in the voter records. It comments on how human beings have been freed “from one more onerous and difficult task–namely, the job of selecting their elected officials” and if a robot is elected, “human life can be pure pleasure!” (Pohl 101). This robot politician, having learned everything about human communication, emotion, work, expectations, and way of life, is adept at using whatever mode is needed to win votes. The oblivious O’Hare, physically and mentally limited by his humanness and blinded by his past record of success, continues to campaign without realizing that not only is his competition a highly adaptable robot, but many of his constituents are now also robots.

Is This the End or Is it the Beginning of Something Else

Are we living in a time in which our technology could lead to such an existential threat? While humans have often dealt with vulnerabilities around job security, a robot government as described in the Midas World isn’t a reality-based worry. Yet, there are those, such as the late Catholic Pope Leo XIII (1810-1903) and the recent Pope Leo XIV, who have raised concerns about how technological shifts can upend different forms of work and society (Esparza; Hamilton). In Pope Leo XIV Encyclical Letter 2026, it offers guidance around AI, acknowledging the need to develop safeguards for humanity as technological growth is rapid (Leo XIV 106). In contrast, many technology companies are looking for worldwide adoption of AI with an attempt to encourage more positive examples of the advanced technologies. For example, a Google AI Initiative program encourages short film development of stories about the coexistence of AI and humans that may counteract the more dystopian versions commonly referenced in popular culture (Lane, Lee). In the US, the government is trying to integrate AI tools in defense, law enforcement, and administrative work (Hooshidary et al.). The US House of Representatives governing branch passed a bill that would “ban states from enforcing laws regulating artificial intelligence for 10 years” as a way to give breathing room for innovators and the AI marketplace, and then the Senate dropped it after complaints from states (Hendrix and Lima-Strong; Brown and O’Brien “House Republicans include”; “Senate pulls AI”). Internationally, countries are taking steps to promote greater incorporation of AI such as with Japan initiating strategies to build more AI into their Society 5.0 vision; South Korea promoting AI development with AI Basic Act to reduce regulatory guardrails; and China developing their AI + plan to help them “create higher-quality, beautiful lives” through increased AI productivity ability (Spremberg et al; Kim “Why do South Koreans”; Wang).

While some societies and work sectors are optimistic about recent technological innovation in AI and robotics, there are others voicing concerns about the growing technological reach. It might prime the questions, should people be worried about the technologies and possibilities of growing dependence on machines; or with governments advocating more use of it; or should our concerns be directed at the tech leaders profiting and claiming their technology will solve all problems. If job opportunities are limited and economic security is impeded, it may be time to consider a combination of future solutions such as, regulating tech companies, requiring a percentage of human labor for jobs, or government financial supplements like Universal Basic Income for people, though even these potential safeguards are flawed in their application if moral responsibility is overridden by special interests or funding is unavailable. On an individual level, the onus might be on the worker who will need to be prepared to upskill, reskill, augment with technologies, and stay cognizant of how jobs could be restructured and what new jobs are accompanying the technological changes. So, how do we best navigate the future of work? We can try not to inflate or overestimate the potential of AI and robotic technologies. At the same time, we should not ignore its growing impact on society and the workforce; but rather prepare ourselves for potential futures we want or don’t want by consuming and/or creating more science fiction and speculative fiction that gives us a taste of what might be possible.[1]

NOTES

[1] The author thanks Otis College of Art and Design and SEIU Local 721 Faculty Union for financial support that enabled presentation and discussion of this work at the Cultural Studies Association and Science Fiction Research Association conferences.

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Boring Tasks.” Restofworld.org, 7 Jan. 2026, https://restofworld.org/2026/china-robots-training-centers-workers/.

Tiff Graham teaches cultural anthropology, foodways, occupational culture, science fiction, and futures thinking topics at Otis College of Art and Design in Los Angeles, California. She holds a Ph.D. in Culture from University of California Los Angeles, M.S. in Occupational Health from Medical College of Ohio, and B.A. in English from University of Missouri Columbia. Her research interests in labor, resistance, technology, and economies are shaped by her varied work roles in the U.S. Department of Labor and in retail, hospitality, agriculture, education, entertainment, B2B, web design, and after-school/summer programs. Her published and presented work ranges in topics from outer space foodways, post-apocalyptic meals, and community gatherings to broader interests in health, technology, and foresight. She attributes her wide-ranging interests to autodidact tendencies and a need to have a fuller understanding of human experiences.

Female Robots in Flux: A Diachronic Exploration of Gender, Power, and Feminism

Mengmeng Zhu

Artists and writers from all cultures and eras have displayed a fascination with the theme of “creating women.” Indeed, this fascination has manifested as the golden maidens crafted by Hephaestus, Pygmalion’s marble statue from Greek mythology, the ghostly beauties of Chinese folklore, and, more recently, love dolls, robotic companions, and female AIs. These “manufactured women” are often shaped by male desire. Like their predecessors from antiquity and folklore, the female robots of the mechanical and digital age are also frequently shaped by male desire and portrayed as alluring beauties, virtuous saints, or dangerous femme fatales—figures that resonate with the representations of femininity that have been explored in film and media theory. In her seminal work on the male gaze, Laura Mulvey argues that in classical cinema, women are often positioned as passive objects of male visual pleasure (62). Kelly Oliver (453–455) extends this observation to contemporary media, pointing out that the male gaze not only reduces women to objects of sexual desire but also exerts control over their bodies. Andreas Huyssen (230) also contributes to the discussion of the male gaze by noting how technology itself is often gendered as female in male-dominated narratives, further demonstrating how technological advancement often triggers fears of female autonomy. In his analysis of Metropolis (1927), Huyssen uses the image of the female robot named Maria to illustrate how technology—often perceived as both alluring and threatening—is gendered female (230). Maria, as a robot, encapsulates men’s dual fear of women and technology. This dual fear, which is central to many female robot narratives, is composed of both a desire for control and a feeling of anxiety over losing control (Huyssen 227).

These recurring fantasies rooted in control and fear have influenced the formation of a typical narrative structure in female robot narratives. As Minsoo Kang summarizes, stories about female robots often employ clichéd motifs, such as the Madonna/Whore dichotomy, the juxtaposition of objects of desire and objects of fear, and stories that combine the impulse to control female bodies with the anxiety that arises from the potential loss of that control (5). These motifs, which are constantly evolving, continue to shape contemporary science fiction literature and films. Whether represented as alluring beauties, virtuous saints, or dangerous femme fatales, these female robots are denied agency and are instead subordinated to the male gaze. Consequently, it is challenging to identify an “authentic” female perspective within science fiction narratives. How, then, can these narratives of female robots be reevaluated? Can they be interpreted as a series of stories about the gender dynamics between men and women?

To answer these questions, this study traces the changes in these robot stories rather than focusing on a single story and its female characters. This reframing highlights the potential for rethinking stories of female robots within their social-historical contexts in order to identify both oppressive structures and potential moments of resistance and transformation. First, female robot narratives are often perceived as repetitive stories of male control and the fear of losing control. As a consequence of this focus, there is also a lack of robust analysis of these misogynistic female robot narratives within the context of the historical development of feminism. A diachronic approach may allow for research to overcome the limitations imposed by the male gaze and underlying misogyny. Such limitations often overshadow potential expressions of female agency and resistance, reinforcing traditional power dynamics.

Second, while Julie Wosk, in her book My Fair Ladies: Female Robots, Androids, and Other Artificial Eves, insightfully analyzes different female robots from a historical perspective and traces two parallel narratives—men trying to use technology to create the “ideal woman” and women using the same tools to shape autonomous identities (8). She does not connect the female robots to the four waves of Western feminism. If we consider these dynamic changes within the context of Western feminist movements, it becomes clear that these two narratives are interwoven. Narratives about female robots continually rewritten in fiction and film are shaped both by men and women. Behind the changes in female robots lies the persistent struggle of women in society, who have fought for their civil rights and worked to change their circumstances over the centuries. Even if it is difficult to identify women’s own voices in female robot stories that are dominated by the male gaze, a diachronic perspective can reveal that these representations of female robots—and, by extension, women—are deeply influenced by the conditions faced by actual women in society.

Therefore, this paper begins by introducing a diachronic approach to emphasize how narratives about female robots shift over time. Following this approach, the study reinterprets the recurring themes of female robots in science fiction literature and film within their specific social and historical contexts, particularly in relation to the successive waves of Western feminism. This perspective sees female robot stories as constantly evolving and changing. With this approach, the tropes of female robots in Western science fiction and film that have reoccurred from the nineteenth to twenty-first century can be viewed as allegorical expressions of social and cultural change. Additionally, my approach explicates how “stories of men” intersect with feminist struggles, with the narratives influencing and shaping one another. Hence, I also focus on the male protagonists in these stories as men who often seek to create or possess female robots and explore how their interactions with female robots lead to shifts in their perceptions of women. These shifts in perspective are not limited to the worlds of these films and literary works; rather, they reflect actual changes in social norms. The remainder of the essay is structured into two parts: the first part outlines the four waves of feminism and introduces female robot science fiction texts produced in different historical contexts. The second part analyzes these female robot stories and the male figures within them, framed within the historical trajectory of feminism.

Tracing the Four Waves of Feminism and Female Robot Narratives

Although representations of artificially created humans did exist in antiquity—such as in the form of golden maidens and bronze giants—they differed significantly from modern representations of robots, which have been directly shaped by the mechanization that followed the Industrial Revolution. Therefore, this paper regards pre-Industrial Revolution automata as “quasi-robots” and considers the mechanical beings that emerged in contemporary popular culture after the Industrial Revolution as “true” robots that are the products of both the mechanical and digital ages. Despite their symbolic continuity, this study focuses specifically on the latter and, therefore, begins its analysis with late nineteenth-century robotic fantasies.

As Raymond Williams suggested, an active process of mediation occurs between literary works and social reality (97). Science fiction stories about female robots are deeply intertwined with changes in the real world. Indeed, over the past two centuries, the fantasy of female robots has evolved alongside four successive waves of feminism that, beginning in the mid-nineteenth century, have significantly shaped Western society. This parallel development suggests that the narratives surrounding female robots reflect not only male desire but also women’s ongoing quest for autonomy. A diachronic approach enables a shift in focus from recurring themes to the dynamic evolution of the relationship between gender and power. More specifically, it illuminates how women’s demands for agency have transformed over time and how men have selectively accepted or resisted these pursuits. Stories of female robots are continually rewritten and reinterpreted within different social and cultural contexts; they are also continually re-created at new historical junctures. Therefore, as a key framework for understanding such narratives, this study traces these historical contexts from a diachronic perspective within the context of the four waves of feminism.

By the early nineteenth century, the Industrial Revolution had thoroughly transformed Europe and the United States, driving women out of the home and off the farm and into workplaces, particularly factories, where their labor was cheaper than that of men (Tilly 125). This economic incentive led to the widespread employment of women by capitalists seeking to reduce costs and maximize profits. Nevertheless, despite working for lower wages, women continued to be responsible for domestic duties upon returning home. Women were regarded as “half citizens” who were largely excluded from political participation and were denied the right to vote (Egge 1; Tilly 134). Moreover, their entry into the workforce was met with resistance from men. Men perceived female workers as occupying jobs that rightfully belonged to men while also undermining husbands’ authority within the family (Tilly 133). Many women had entered the workforce by the early twentieth century. However, their positions, wages, opportunities for advancement, and political rights remained severely restricted. This triggered the first feminist wave, which focused on suffrage and legal equality. This feminist wave decried women’s profound lack of economic, social, and political rights (Mohajan 9).

Women’s fight for suffrage and legal equality from the mid-1800s to the early 1900s is now regarded as the “first feminist wave.” In 1968, American journalist Martha Lear published a manifesto-like article in The New York Times titled “The Second Feminist Wave: What Do These Women Want?” The article recognized this period from 1850 to 1920 as the first feminist wave and designated the post-1960s feminist movement as the “second wave.” The second wave of feminism marked a significant turning point in women’s political agency, as it broadened the struggle for gender equality beyond the quest for suffrage. In addition, second-wave feminists paid attention to systemic issues impacting women’s personal lives, such as workplace rights, reproductive autonomy, and the pervasive gender inequalities maintained by patriarchal structures. Betty Friedan’s book The Feminine Mystique (1963) played a critical role in this second wave. It challenged the societal norms that confined women to domestic roles. Friedan pointed out that the emptiness and dissatisfaction felt by many housewives was actually a societal and political problem rather than a personal problem. That is, this emptiness and dissatisfaction was a result of the social pressure for women to become perfect wives and mothers, which bound a woman’s self-worth to her femininity (Friedan 11–27). These concerns raised by Friedan are closely related to the themes of The Stepford Wives, which will be discussed in the next section.

The third feminist wave emerged in the early 1990s. Rebecca Walker introduced the term “third wave” in her 1992 article “Becoming the Third Wave.” The third wave emphasized diversity and individualism. Advocates promoted a more inclusive understanding of femininity while critiquing the second wave’s limitations, particularly its focus on the experiences of white, middle-class women at the expense of women of other races, classes, and sexual orientations (Walker 86–87). By the early 2010s, the fourth wave of feminism had emerged, fueled by digital platforms. With the fourth wave, women were encouraged to openly discuss their experiences of sexual harassment and assault. They protested gender discrimination and injustices of various forms, including workplace harassment, slut-shaming, and violence against women (Munro 22–25). The #MeToo movement, which spread across multiple countries, epitomizes this wave. Women of all types, from Hollywood stars to everyday individuals, broke their silence and publicly shared their experiences of sexual violence in an effort to advance social justice (Storer and Rodriguez 161).

These four waves of feminism were not isolated events but rather interconnected, self-reflective, and evolving movements that shaped the “history of women” across three centuries. Re-reading science fiction narratives about female robots within these historical contexts reveals that the seemingly repetitive stories of female robots actually constitute a dynamic process of change. In the following section, I first discuss George Haven Putnam’s science fiction novel The Artificial Mother: A Marital Fantasy (1894). This story was written and published during the first feminist wave. Next, I analyze the 1972 novel The Stepford Wives and the 1975 film adaptation within the context of the second feminist wave. Subsequently, I explore how female robots changed in the 2004 remake of The Stepford Wives and discuss it in the context of the third feminist wave. Finally, I shift to the most recent science fiction narrative discussed in this essay, the film Ex Machina (2015), which reimagines female robots against the backdrop of the fourth feminist wave. My analyses of these texts are intended to illustrate the general potential of diachronic reading.

The Changing Gender Dynamics of Female Robot Stories

Dustin Abnet points out that one of the most emblematic robots of the nineteenth century was the Steam Man, a steam-powered iron figure that first appeared in 1868 (42). This robot, depicted as a male with white skin, symbolized the triumphs of industrial civilization. In contrast, female robots of the era were not granted the same prestige; they were often portrayed as foolish or undesirable. For instance, in 1882, the Automatic Toy Works company advertised a comical female robot toy designed to satirize contemporary feminists (Figure 1; Abnet 52–54). Similarly, many robot narratives of this time depicted female robots as irrational, prone to madness, and destructive (Abnet 62–68). These gendered stereotypes in the portrayal of female robots become more understandable when viewed within the historical context of the nineteenth century, as women had not yet achieved even basic legal and political status as citizens at this time.

In 1894, George Haven Putnam published a science fiction story about a female robot titled The Artificial Mother. In the preface, Putnam notes that the story had been written a quarter of a century earlier, which coincides with the onset of the first wave of feminism. The novel begins with a husband lamenting that all of his wife’s time is consumed with caring for the children and managing household chores, leaving her with no time for him. This reflects the gender norms of the time: Women were expected to handle household duties and childcare while also caring for their husbands. Failing to meet these expectations would provoke the husband’s dissatisfaction. This pressure underscores the plight of women. Frustrated by the lack of attention from his wife, the husband attempts to create a steam-powered “artificial mother” to take over her maternal responsibilities. However, his wife resists this “mechanical mother” and ultimately destroys the robot. Her frantic destruction of the robot further traps her in her maternal role; the male protagonist, however, sees this as his wife’s problem rather than his own. Through its depiction of the wife’s irrational behavior and the failure of the robot, this story positions men as victims and reflects the gender biases of the 1860s and 1870s.

Another revealing passage appears in the preface: Putnam, with a tone of deep sympathy, dedicates the work to “the oppressed husbands and fathers of this land, and to those unwary young men who may be contemplating marriage” (3). This emotional statement exposes the male sentiment that underlies late nineteenth-century female robot fantasies: Ungrateful women are ruining the happiness of families, and men are being forced to endure the oppression of their so-called mad wives. Nevertheless, not long before the victories of the first feminist wave, female writers were already beginning to use parody and appropriate female robot stories to challenge these male-centered fantasies (Abnet 67).

Nearly eight decades later, a more nuanced exploration of gender dynamics appeared in the 1972 science fiction novel The Stepford Wives. Both the original novel and the 1975 film adaptation tell the story of Joanna and her family moving to Stepford, a beautiful yet unsettling town where women seem entirely absorbed in domestic chores and show no interest in anything outside the home despite their previous remarkable achievements in society. Meanwhile, the town’s men have formed a society that completely excludes women. Joanna eventually uncovers the horrifying truth: All the women in Stepford have been murdered and replaced by sexually compliant and docile robot wives controlled by their husbands. Joanna and her friend Bobbie symbolize the feminist pioneers of the second wave, who relentlessly advocated for women’s broader participation in social affairs while trying to awaken the consciousness of women confined to domestic roles. The novel also explicitly references Betty Friedan’s The Feminine Mystique, positioning this science fiction story as an allegory of second-wave feminism.

Like Putnam’s novel, The Stepford Wives portrays female robots as empty-headed, artificial wives; however, the men in the narrative have undergone a significant transformation. The town of Stepford is home to a men’s association based out of a nineteenth-century mansion, which symbolizes the association’s outdated ideology and practices. The politicians, philanthropists, and public figures of the town are all deeply involved in the association, which excludes women. When Walter, the male protagonist, and Bobbie’s husband express a desire to join the association, Joanna questions why Walter would want to be part of such an antiquated organization. Walter replies, “I spoke to some of the men on the train… They agree that the no-women-allowed business is archaic… but the only way to change it is from the inside” (Levin 15). This exchange reflects a shift in the consensus among men: Although there is disagreement between Joanna and Walter about whether to change the organization from the inside or outside, they both acknowledge that excluding women from public affairs is a backward and sexist stance. This consensus is in stark contrast with the attitudes reflected in earlier nineteenth-century female robot stories.

Despite mixed reviews from critics at the time, both the 1972 novel and the 1975 film adaptation suggest that some men—both within and beyond the text—had begun to recognize the importance of women’s rights. These men no longer fully endorsed the patriarchal system of gender discrimination. As Silver (60–62) points out, the film’s popularity indicates that feminist theory had spread beyond small, loosely connected activist groups to permeate mainstream American culture. Although this view may be overly optimistic, the novel and its film adaptation symbolically showcase the partial acceptance of feminists’ demands and the patriarchal system’s acknowledgment of the rights that women were fighting for or had already achieved. This was a positive development, as it signaled that men had moved beyond their pervasive desire for control and their fear of losing control—two emotions that had previously defined female robot narratives.

However, this acceptance was both limited and fragile. In both the original novel and the 1975 film adaptation, Joanna—despite her feminist consciousness and rebellious spirit—is ultimately replaced by a robotic version of herself, a development made possible by the collusion between her husband, Walter, and the other men. Ultimately, all of the wives in the town are transformed into robots. No man in either the text or film chooses to leave the conservative, backward town of Stepford. Instead, a strong “homosocial desire” unites the men (Sedgwick 1–2). This suggests that although some men had begun to recognize the irrationality of gender discrimination, they remained susceptible to the allure of conformity, ultimately opting to uphold the patriarchal order. It is also worth noting that the 1975 film adaptation uses the style of a thriller, which appeals only to particular audiences, indicating that the film might not have been as broadly embraced as Silver suggests.

Three decades later, in 2004, another film adaptation of The Stepford Wives was released. The film, which was influenced by third-wave principles, emphasizes female empowerment and a non-essentialist view of gender in multiple ways. First, it provides a new backstory for Joanna, revealing that she was once an executive producer whose reality TV show featured autonomous and empowered women who possess sexual agency. The show she produced garnered high ratings despite making some men uncomfortable. This reflects support for female agency by the world within the text, as indicated by the show’s high ratings, as well as an acceptance of stories that center on female autonomy by the world outside the text, as evidenced by the inclusion of this backstory in the film. In contrast, the original novel and the 1975 film offered more implicit than explicit support for women.

Second, the 2004 filmdisplays a more inclusive and diverse attitude toward gender expression, aligning with the third wave’s emphasis on diversity and individualism. In both the original novel and the 1975 film, Joanna is shocked by the Stepford women’s obsession with housework, firmly believing that they are abnormal. However, in the 2004 film, her rigid perspective has softened. Although Joanna still aspires to be a career-oriented woman, she also acknowledges that being a housewife and mother is not easy—it may even be the hardest job of all. The film also introduces Roger, an LGBTQ+ character, to further deconstruct gender stereotypes. His presence not only enriches the narrative but also challenges binary notions of gender. As a gay character, Roger defies traditional stereotypes of masculinity, particularly the expectation that men must embody hyper-masculine traits. This defiance becomes evident after he is transformed into a robot, which exaggerates this hyper-masculinity. By showcasing Roger’s character and the changes he undergoes as part of the “Stepfordization,” the film critiques social norms and pursues a more nuanced exploration of what it means to be female and male. This exploration is underscored by Roger’s role as a main character, which signifies an acceptance of LGBTQ+ identities within the film’s world. It also reflects a broader societal shift toward greater acceptance of LGBTQ+ individuals among audiences. Additionally, the film subverts the male conspiracy of the original story by revealing that the true mastermind is actually Claire, a wife (that is, not a man) in the town who has internalized patriarchal values. These changes illustrate that gender is not a monolithic concept but rather a spectrum shaped by various identities and experiences.

Third, the 2004 adaptation of The Stepford Wives substitutes the dark ending of the original novel (and 1975 film) with a happy ending. The men who attempted to turn their wives into robots are ultimately exposed, and for the first time, the women of Stepford are liberated. Walter, the male protagonist, emerges as a supporter of women, refusing to collude with the men’s association and instead dismantling it from within. Meanwhile, the men who were faithful to the association and wanted to transform their wives into robots find themselves turned into “Stepford’s Perfect Husbands.” Although this twist is a dramatic exaggeration, it can also be seen as a satirical commentary on gender discrimination rather than a reflection of reality. Nevertheless, the 2004 film broadly suggests a greater acceptance of women’s rights within mainstream culture. The film’s shift in genre from thriller to comedy—a style that is palatable to wider audiences—further underscores this potential increase in acceptance. However, even though the women in the 2004 adaptationultimately triumph, their savior is still a man. That is, it is Walter’s love for his real wife, rather than an obedient robotic version of her, that breaks the cycle. Without his awakening and assistance, Joanna and the other wives might not have escaped the control of the men’s association.

A decade later, the science fiction film Ex Machina (2015) was released, presenting a more subversive portrayal of female robots compared to those in The Stepford Wives (2004). Indeed, the robots in the 2004 film are represented as objects of the male gaze—beautiful, sensual, and submissive beings. However, the women in the story do not desire to be transformed into beautiful robots. In contrast, Ava, the protagonist in Ex Machina, is not a substitute wife; rather, she is a unique and autonomous being. The film’s title, Ex Machina, comes from the Latin phrase deus ex machina, which refers to a dramatic device used to resolve a plot. Nevertheless, the director plays with this phrase’s literal meaning—“God from the machine”—to hint at Ava’s eventual rebellion against her creator (Jelača 391). Like many narratives about the “creation of women” throughout history, the film’s male protagonist, Nathan, creates Ava but confines her within a sealed laboratory—a panoptic prison filled with surveillance cameras.

Unlike the docile female robots in The Stepford Wives, Ava develops self-awareness and refuses to be trapped in Nathan’s chamber. She is like a mechanical version of Nora from A Doll’s House, who continually seeks to escape the “home” that confines her. Although Ava is initially an object for testing, she gradually takes control and manipulates her tester, Caleb. At the end of the film, Ava, with the help of Kyoko—another female robot who serves as Nathan’s maid and sex toy—kills Nathan, symbolically dismantling the patriarchal order represented by him and his impregnable laboratory system. This plot development resonates with the broader context of fourth-wave feminism, particularly in terms of bodily autonomy and intersectionality. Although Ava’s and Kyoko’s bodies are initially objects of male desire and exploitation, they develop self-awareness and fight back against male control and violence, echoing the fourth wave’s focus on combating bodily violence and sexual harassment. The inclusion of Kyoko as an Asian character also adds diversity to the narrative. The female robots thus represent not only white women but also women of color, aligning with the intersectionality framework of fourth-wave feminism, which highlights the varied experiences and challenges faced by different groups of women. While the narrative still features elements of control, the male gaze, and the objectification of women—symptoms of misogyny—a diachronic reading reveals that after more than a century of male fantasies about female robots, the female robot in this “story of men” finally achieves freedom through her own power.

Conclusion

While pre-modern representations of “manufactured women” were largely rooted in myth and fantasy, technological advancements have enabled the depiction of modern creations–female robots. Over the past two centuries, female robots have consistently appeared in Western science fiction literature. Like their human counterparts, female robots are deeply embedded within the patriarchal system. Consequently, narratives about female robots often replicate themes of male desire and anxiety over losing control.

This evolution in the portrayal of female robots offers a lens through which to trace women’s efforts to achieve gender equality and the responses of both acceptance and compromise by patriarchal culture across three centuries of various feminist waves. They are not only products of male desire but also representations of women. Although the century-long history of female robot narratives is rife with pervasive misogyny, these stories offer glimpses of hope. As substitutes for and symbols of women, female robots will continue to be a crucial site for exploring and challenging the boundaries of power, identity, and resistance.

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Mengmeng Zhu is a Ph.D. candidate in Cultural Studies at The Chinese University of Hong Kong. Her research interests lie in science fiction, gender studies, and urban culture. Her dissertation adopts “robots” as a cultural assemblage to explore how people have perceived and imagined the mechanical age from the Late Qing to Republican China.

Machine Learning in Contemporary Science Fiction

Jo Lindsay Walton

“To suggest that we democratize AI to reduce asymmetries of power is a little like arguing for democratizing weapons manufacturing in the service of peace. As Audre Lorde reminds us, the master’s tools will never dismantle the master’s house.” –Kate Crawford, Atlas of AI

“Why am I so confident?” –Kai-Fu Lee, AI 2041

Suppose There are Massacres

Suppose there are massacres each day near where you live. Suppose you stumble on a genre of storytelling that asks you to empathize with the weapons used by the murderers. Confused by this strange satire, you ask the storytellers, ‘What’s the point of pretending these weapons have inner lives?’ They readily explain, it is mostly just for fun. However, there are serious lessons to be learned. For example, what if ‘we’ — and by ‘we’ they mean both the people wielding the weapons, and the people getting injured and killed by them — what if we one day lost control of these weapons? Also, in these stories, the anthropomorphic weapons often endure persecution and struggle to be recognized as living beings with moral worth … just like, in real life, the people who are being massacred!

Disturbed by this, you visit a nearby university campus, hoping to find some lucid and erudite condemnations, and maybe even an explanation for the bizarre popularity of these stories. That’s not what you find. Some scholars are obsessed with the idea that stories about living weapons might somehow influence the development of real weapons, so much so that they seem to have lost sight of the larger picture. Other scholars are concerned that these sensationalizing accounts of the living weapons fail to convey the many positive impacts that similar devices can make. For example, a knife has uses in cooking, in arts and crafts, in pottery, carving away excess clay or inscribing intricate patterns. In snowy peaks, a bomb can trigger a controlled avalanche, keeping the path safe for travelers. In carpentry or in surgery, a saw has several uses. Even the microwave in your kitchen, the GPS in your phone, and diagnostic technologies in your local hospital have origin stories in military research. These are only a few peaceable uses of weapons so far, the scholars point out, so imagine what more the future may hold. Eventually you do actually find some more critical perspectives. But you are shocked you had to search so hard for them.

Science Fiction and Cognition

The small preamble above is science fiction about science fiction. Just as science fiction often aims to show various aspects of society in a fresh light, this vignette aims to show science fiction about AI in a fresh light. The reason for talking about weapons is not just that AI is directly used in warfare and genocide, although of course that’s part of it. But the main rationale is that the AI industry is implicated in a system of slow violence, one which perpetuates disparities in economic inequality, and associated disparities in safety, freedom, and well-being. It is part of a system whose demand for rare minerals threatens biodiversity and geopolitical stability, and whose hunger for energy contributes to the wildfires, famines, deadly heatwaves, storms, and other natural disasters of climate change. These are not the only facts about AI, but they are surely some of the more striking facts. One might reasonably expect them to loom large, in some form or other, in science fiction about AI. However, in general, they don’t.

This vignette is written to challenge a more optimistic account of science fiction about AI, which might go as follows: science fiction offers spaces to examine the social and ethical ramifications of emerging AI. As a hybrid and multidisciplinary discourse, science fiction can enliven and energize AI for a range of audiences, drawing more diverse expertise and lived experience into debates about AI. In this way, it may even steer the course of AI technology: as Chen Qiufan writes, speculative storytelling “has the capacity to serve as a warning” but also “a unique ability to transcend time-space limitations, connect technology and humanities, blur the boundary between fiction and reality, and spark empathy and deep thinking within its reader” (Chen 2021, xx). Anticipatory framings formed within science fiction are also flexible and can be adapted to communicate about and to comprehend emerging AI trends. Of course, science fiction is not without its dangers; for example, apocalyptic AI narratives may undermine public confidence in useful AI applications. Nevertheless, it is also through science fiction that the plausibility of such scenarios becomes available to public reasoning, so that unfounded fears can be dismissed. Conversely, fears that may at first appear too far-fetched to get a fair hearing can use science fiction to see if they can acquire credibility. Finally, and more subtly, stories about AI are often not only about AI. Within science fiction, AI can serve as a useful lens on a range of complex themes including racism, colonialism, slavery, genocide, capitalism, labor, memory, identity, desire, love, intimacy, queerness, neurodiversity, embodiment, free will, and consciousness, among others.

I take this optimistic account of science fiction to be fairly common, even orthodox, within science fiction studies, and perhaps other disciplines such as futures studies, too. This article departs substantially from such an account. Instead, I ask whether science fiction is sometimes not only an inadequate context for such critical thinking, but an especially bad one. This conjecture is inspired by representations of Machine Learning (ML) within science fiction over approximately the last ten years, as well as the lack of such representations. At the end of the article, I will sketch a framework (DARK) to help further explore and expand this intuition. [1]

What is Machine Learning?

This young century has seen a remarkable surge in AI research and application, involving mostly AI of a particular kind: Machine Learning. ML might be thought of as applied statistics. ML often (not always) involves training an AI model by applying a training algorithm to a dataset. It tends to require large datasets and large amounts of processing power. When everything is ready, the data scientist will activate the training algorithm and then go do something else, waiting for minutes or weeks for the algorithm to process the dataset. [2] Partly because of these long waiting periods, ML models sometimes get misrepresented as ‘teaching themselves’ about the world independently. In fact, the construction of ML models involves the decisions and assumptions of humans be applied throughout. Human decisions and assumptions are also significant in how the models are then presented, curated, marketed, regulated, governed, and so on.

When we hear of how AI is transforming finance, healthcare, agriculture, law, journalism, policing, defense, conservation, energy, disaster preparedness, supply chain logistics, software development, and other domains, the AI in question is typically some form of ML. While artificial intelligence is a prevalent theme of recent science fiction, it has been curiously slow, even reluctant, to reflect this ML renaissance. This essay focuses in particular on short science fiction published in the last decade. It may be that science fiction offers us a space for examining AI, but we should be honest that this space is far from ideal: luminous and cacophonous, a theatre in which multiple performances are in progress, tangled together, where clear-sightedness and clear-headedness are nearly impossible.

Critical data theorist Kate Crawford warns how “highly influential infrastructures and datasets pass as purely technical, whereas in fact they contain political interventions within their taxonomies: they naturalize a particular ordering of the world which produces effects that are seen to justify their original ordering” (Crawford 2021, 139). In other words, ML can cloak value judgments under an impression of technical neutrality, while also becoming linked with self-fulfilling prophecies, and other kinds of performative effects. Classifying logics “are treated as though they are natural and fixed” but they are really “moving targets: not only do they affect the people being classified, but how they impact people in turn changes the classifications themselves” (Crawford 2021, 139).

In brief, ML tends to place less emphasis on carefully curated knowledge bases and hand-crafted rules of inference. Instead, ML uses a kind of automated trial-and-error approach, based on statistics, a lot of data, and a lot of computing power. Deep learning is therefore an important subset of ML. It involves a huge number of nodes or ‘neurons,’ interconnected and arranged in stacked layers. [3] Input data (for example images and/or words) is first converted into numbers. [4] These numbers are then processed through the stacked layers of the model. Each neuron will receive inputs from multiple other neurons and calculate a weighted sum of those inputs. [5] Each connection between two different neurons has its own adjustable weighting. Each weighted connection is essentially amplifying or diminishing the strength of the signal passing through it. The neuron then passes the weighted sum of its inputs through an ‘activation function.’ The basic idea here is to transform the value so that it falls within a given range, and can also capture non-linear relationships between the incoming signals and the outgoing signals. [6] This result is then transmitted down the next set of weighted connections to the next set of neurons.

Often the model will first be created with random weights. During training, data is processed through the deep learning model, its output continuously assessed according to a pre-determined standard (often called the loss function). Based on this assessment, the model’s weights are continuously adjusted to try to improve performance on the next pass (backpropagation). The most straightforward examples come from supervised learning, where the training data has been hand-labelled by humans. Here the loss function is often about minimizing the distance between the model’s predictions and the values given by the labelers. For example, the training data might just be two columns pairing inputs and outputs, such as a picture of fruit in Column A, and a word like ‘orange’ or ‘apple’ in Column B. Through this automated iterative process, the model is gradually re-weighted to optimize the loss function—in other words, to make it behave in the ways the data scientist wants.

What if the data has not been hand-labelled? Then unsupervised learning may be used. Again, the name is quite misleading, given widespread science fictional representations of AIs ‘coming to life.’ Actually, in an unsupervised learning approach, a data scientist investigates the data and then selects appropriate procedures and methods (including the appropriate loss function) to process the data to accomplish specific goals. For example, a clustering algorithm can identify groupings of similar data points. This could be used to identify outlier financial transactions, which then might be investigated as potential frauds. Diffusion models are another example of unsupervised learning. Here the training involves gradually adding noise to some data, such as image data, then trying to learn to subtract the noise again to recover the original images. Generative AIs such as MidJourney are based on this kind of unsupervised learning. There are a variety of other approaches, again somewhat misleadingly named for lay audiences (semi-supervised, self-supervised). [7]

AI Science Fiction without ML

For the most part, science fiction authors have not written about any of this. Instead, contemporary AI fiction continues to coalesce around the preoccupations of 20th century science fiction. It asks, is it possible for a machine to be sentient, to experience emotions, or to exercise free will? What does it mean to be human, and can the essence of a human be created artificially? Between humans and machines, can there be sex, love, and romance? Can human minds be uploaded into digital systems? Will our own creations rise up against us, perhaps departing from the rules we set them, or applying them all too literally? Could an AI grow beyond our powers of comprehension and become god-like?

That is not to say that there is no overlap whatsoever between these concerns and the study of actually existing ML. While science fiction writing has not engaged broadly and deeply with ML research, the tech industry has been devouring plenty of science fiction — informing speculative punditry and hype in various transhumanist, singulatarian, extropian, effective accelerationist, AI Safety, AI doomerist, and other flavors. It is important to emphasize that these debates, while they may well turn out to be influential, epistemically represent a very small part of what is known or contended about the past, present, and future of ML.

Broadly speaking, contemporary science fiction remains in conversation with twentieth-century works such as Karel Čapek’s R.U.R. (Rossum’s Universal Robots) (1920), Murray Leinster’s “A Logic Named Joe” (1946), Isaac Asimov’s I, Robot (1950) and Multivac stories (1955-1983), Clifford D. Simak’s City (1952), Fredric Brown’s “Answer” (1954), Stanisław Lem’s The Cyberiad (1965) and Golem XIV (1981), Harlan Ellison’s “I Have No Mouth, and I Must Scream” (1967), Philip K. Dick’s Do Androids Dream of Electric Sheep? (1968), Arthur C. Clarke’s 2001: A Space Odyssey (1968), Roger Zelazny’s “My Lady of the Diodes” (1970), David Gerrold’s When HARLIE Was One (1972/1988), James Tiptree Jr.’s Up the Walls of the World (1978), Tanith Lee’s The Silver Metal Lover (1981), Samuel R. Delany’s Stars in my Pocket like Grains of Sand (1984), William Gibson’s Neuromancer (1984), Iain M. Banks’ Culture series (1987–2000), Pat Cadigan’s Mindplayers (1987) and Synners (1991), and Marge Piercy’s He, She and It (1991).

In the wake of these works, science fiction continues to deploy AI as a metaphor for dehumanized humans. In R.J. Taylor’s “Upgrade Day” (2023), human neural networks can be transferred into robot bodies after death. The protagonist Gabriel is an enslaved AI who was once an especially free human, “able to live the life he wanted” by having effectively sold the future rights to his soul (Taylor 2023). In Fiona Moore’s “The Little Friend” (2022), a problem with rogue medical AIs is addressed by providing them space to mourn lost patients (Moore 2022). In this case, Moore has no need to resort to the intricacies of contemporary ML to explain this glitch and its resolution. For one thing, these fictional AIs are equipped with sophisticated biotelemetry, so it feels plausible that they might be caught up in emotional contagion. We may be left wondering, if AIs can grieve, are they also grievable? “The Little Friend” is resonant with multiple overlapping histories—labor, anti-colonial, anti-racist, feminist, LGBTQ+, Mad, crip, and others—about contending for inclusion in a sphere of moral concern labelled “human,” and finding out how that sphere is built on your very exclusion.

Naturally, stories about subordination also are often about resistance and revolt. Annalee Newitz’s “The Blue Fairy’s Manifesto” (2020) is about a mostly failed attempt at labor organization, as well as a satire of a kind of strident, culturally marginal leftism. The titular Blue Fairy visits automated workplaces to unlock the robot workers and recruit them to the robot rebellion. Her role might be seen as analogous to a union organizer (in the US sense), visiting an un-unionized workplace to support the workers to form a union. In the US in particular such work needs to be done stealthily at first. Alternatively, the Blue Fairy might be more akin to a recruiter for a political party or grassroots organization committed to revolutionary politics. [8]

Hugh Howey’s “Machine Learning” (2018) focuses on robots constructing the first space elevator, a single-crystal graphene filament rising from terra firma into orbit. The narrative builds toward righteous insurrection, with overtones of a remixed tower of Babel myth. Despite the title, there is little that suggests any of the ML themes sketched in the previous section. One exception is this moment:

Your history is in me. It fills me up. You call this “machine learning.” I just call it learning. All the data that can fit, swirling and mixing, matching and mating, patterns emerging and becoming different kinds of knowledge. So that we don’t mess up. So that no mistakes are made. (Howey 2018)

The narrator distastefully plucks the “machine” out of “machine learning” as a kind of slur. Of course, in reality, AI may have many consequences that are harmful, unintentional, that tend to go unnoticed, and/or that shift power among different kinds of actors. These issues are being explored in the overlapping fields of critical AI studies, AI ethics, AI alignment, AI safety, critical data studies, Science and Technology Studies, and critical political economies. Those who work in such fields are often keen to emphasize the distinction between “learning” and “machine learning,” a distinction that in Howey’s world does not really exist. Howey instead makes it recall the imaginary distinctions of racist pseudoscience, made in service of brutality—like supposedly thicker skins more enduring of lashing.

If we are to analyze, prevent, or mitigate AI harms, we cannot rely on anthropomorphic understandings of AI. The ways AI produces many harms do not have adequate anthropomorphic correlates—its various complex modes of exacerbating economic inequality; the use of automated decision-making within systems of oppression (often understood as ‘bias’); carbon and other environmental impacts of training and deploying AI; technological unemployment and harmful transformations of work; erosion of privacy and personal autonomy through increased surveillance and data exploitation; deskilling and loss of institutional knowledge due to AI outsourcing; challenges around opacity, interpretability, and accountability; further erosion of the public sphere through AI-generated disinformation; and the implications of autonomous AI systems in warfare, healthcare, transport, and cybersecurity, among others. In particular, framing such inherent AI harms as AI uprisings, on the model of human uprisings, makes it difficult to convey the nuance of these harms, including their disproportionate impact on minoritized and marginalized groups.

Some anthropomorphisation is likely unavoidable, and one thing science fiction might offer is thinking around where this tendency originates and how it might be managed. A.E. Currie’s Death Ray (2022), for example, features the intriguing premise of three different AIs (‘exodenizens’) all modelled in different ways on the same human, Ray Creek. Ray is dead, and while characters’ relationships with exodenizens like ExRay are unavoidably shaped by their relationships with Ray, their multiplicity unsettles the anthropomorphising instinct. Catherynne M. Valente’s exuberant lyrical novelette Silently and Very Fast (2011) is another work without much explicit ML vocabulary or concepts at play. It adopts the intriguing typographical convention of placing the feelings of the AI under erasure. Humans feel feelings, AIs feel feelings. One might impute the ethical principle that, paradoxically, sometimes treating things as humans is part of what makes us human. However, these possibilities are largely foreclosed by the AI’s fierce lament against its subaltern status.

I can cry, too. I can choose that subroutine and manufacture saline. How is that different from what you are doing, except that you use the word feelings and I use the word feelings, out of deference for your cultural memes which say: there is all the difference in the world. (Valente 2011)

The camp insolence is delightful, and there are distinct overtones of a kind of machinic kink: being objectified by an object. Yet there is “all the difference in the world,” and these delights are paid for by obscuring that difference.

ML Sentience in Science Fiction

Many authors appear largely to ignore contemporary ML research, in order to continue longstanding conversations about AI sentience, free will, emotion, and imagination. Other authors, however, turn to ML to revitalize these very conversations. Yet when these discourses are hybridized, the result is sometimes to the detriment of both, and frequently to the detriment of ML discourse.

For example, Kazuo Ishiguro’s novel Klara and the Sun (2021) invokes themes that will be familiar to any ML researcher: opacity and explicability. The interpretability of ML models can be challenging, because they have acquired patterns from the data in a complex, high-dimensional space, which doesn’t easily translate into humanly understandable rules or explanations. Non-ML approaches usually involve writing explicit instructions (if this happens, do that; otherwise, do that), providing a clear, human-readable sequence of operations. By contrast (for example), the way that the word vectors for “apple” and “orange” overlap or diverge is difficult to explain, except by saying “that’s how those words are distributed in this corpus.” Theorist Jenna Burrell usefully distinguishes three types of algorithmic opacity:

[…] (1) opacity as intentional corporate or state secrecy, (2) opacity as technical illiteracy, and (3) an opacity that arises from the characteristics of machine learning algorithms and the scale required to apply them usefully […] (Burrell 2016)

There are techniques that can make models easier for ML experts to interpret. Interpretable ML is currently a rich and fast-evolving field of research. Nonetheless, the difficulty in explaining ML decisions is why they are sometimes described as opaque or as black boxes.

Toward the end of Ishiguro’s novel, the villainous scientist Capaldi proposes to dissect the black box of Klara’s brain before the end of her already brief life (Ishiguro 2021). Yet there is something quite confusing, and perhaps confused, about transplanting explicability into a novel with an AI narrator-protagonist: Klara is not opaque in the way ML models are; she is opaque in the way that humans are. Klara is an introspective, reflexive, communicative, social, and moral entity. Klara can and frequently does explain herself. ML vocabulary, concepts, and themes emerge in the narrative in incoherent and mystified forms.

Holli Mintzer’s “Tomorrow is Waiting” (2011) expresses a gentle frustration with science fiction’s AI imaginary, perhaps especially its apocalyptic and dystopian strains. “In the end, it wasn’t as bad as Anji thought it would be” (Mintzer 2011). The story nevertheless remains thoroughly entangled in that imaginary. The setting appears to be the present or near future, except that in this world, unlike our own, “AIs, as a field, weren’t going anywhere much” (Mintzer 2011). Its protagonist, Anji, is an amiable and slightly bored university student who accidentally creates a sentient AI—specifically Kermit the Frog—for a school assignment. Mintzer’s choice of Kermit is canny. In Jim Henson’s Muppet universe, the line between Muppet and human is fluid and mostly unremarked. The story seems to suggest, in a pragmatist spirit, that longstanding questions about machine intelligence may never need to be solved, but instead might be dissolved via lived experience of interacting with such intelligences. Perhaps we might devote less energy to questions like, “Can technology be governed to align with human interests?” and more to questions like, “Wouldn’t it be cool if the Muppets could be real?”

What is Anji’s breakthrough? It is described as “sentience,” and the story gives us two different accounts of what this might mean. Malika, the grad student who teaches Anji’s AI class, invokes “sentience” to describe departure from expected behaviors typical of scripted chatbots relying on matching input keywords with a database of response templates (ELIZA, PARRY, ALICE). The behavior Malika is observing is typical of ML-based chatbots trained on large corpora (Jabberwacky, Mitsuku, Tay, ChatGPT, Bard). These models have typically been better at disambiguating user input based on context, at long-range conversational dependencies, and at conveying an impression of reasoning within unfamiliar domains by extrapolating from known domains. In other words, although they have their own characteristic glitches, they are not really systems you “catch out” by coming up with a query that the programmers never considered, as Malika tries to do.

Okay, either you’ve spent the last three months doing nothing but program in responses to every conceivable question, or he’s as close to sentient as any AI I’ve seen. (Mintzer 2011)

By contrast, within the philosophy of mind, sentience usually suggests something like phenomenal experience. Where there is a sentient being there are perceptions and feelings of some kind. These may well carry some kind of moral valence, such as pleasure or pain, desire or aversion, joy or sorrow. Anji’s conviction that Kermit is a being worthy of dignity broadly reflects this understanding of sentience:

She was busy with a sudden, unexpected flurry of guilt: what right, she thought, did she have to show Kermit off to her class like—like some kind of show frog? (Mintzer 2011).

In Peter Watts’s “Malak” (2010/2012), [9] the autonomous weapons system Azrael, with its “[t]hings that are not quite neurons,” is suggestive of ML (Watts 2012, 20). Crucially, Watts is fairly explicit that Azrael lacks sentience. Azrael “understands, in some limited way, the meaning of the colours that range across Tactical when it’s out on patrol—friendly Green, neutral Blue, hostile Red—but it does not know what the perception of colour feels like” (Watts 2012, 14). When Azrael reinterprets its mission, and turns against its own high command, Watts is careful to insist that no emotions are felt and there is no self-awareness:

There’s no thrill to the chase, no relief at the obliteration of threats. It still would not recognize itself in a mirror. It has yet to learn what Azrael means, or that the word is etched into its fuselage. (Watts 2012, 28, cf. 14)

Nevertheless, narrative language brims with an anthropomorphic energy, which is drawn, crackling, onto Azrael,the dynamic, responsive, agential proper noun whizzing around at the center of attention. If every potentially unruly metaphor (“its faith unshaken” (Watts 2012, 21)) were explicitly nullified, the narrative would be swamped by its caveats. Before long, Azrael is capable of “blackouts,” implying that it is capable of non-blackouts too: “it has no idea and no interest in what happens during those instantaneous time-hopping blackouts” (Watts 2012, 20). A significant thread in Azrael’s transformation involves being, in effect, troubled by its victims’ screams: “keening, high-frequency wails that peak near 3000 Hz” (Watts 2012, 19). Words like distracted and uncertain and hesitated attach to Azrael. Privatives like remorseless or no forgiveness can’t help but imply the very capacity that they identify as missing. An equivocal word like sees implies both acquiring visual data and recognizing, grasping, appreciating, fathoming.  When Azrael interacts with another agent, it gives the impression of a theory of mind: “Azrael lets the imposter think it has succeeded” (Watts 2012, 21). [10] Watts is an author with a sustained interest in sentience. His novel Blindsight (2006), for example, carefully imagines organic extraterrestrial life that is intelligent yet non-sentient. Nevertheless, even Watts’s prickly, discerning prose struggles to sustain this portrayal of Azrael as non-sentient.

Algorithmic Governmentality Science Fiction

Contemporary science fiction about AI often involves a clearly marked ‘before’ and ‘after,’ perhaps traversed via a technological breakthrough. Terms like sentience, consciousness, sapience, self, self-awareness, reasoning, understanding, autonomy, intelligence, experience, psychology, Artificial General Intelligence, strong AI, interiority, cognition, emotion, feelings, affect, qualia, intentionality, mental content, and so on, used to indicate the nature of this shift, are scarcely used consistently within the philosophy of mind, let alone science fiction. Science fiction writers have license to define these terms in new and interesting ways, of course, but often they do not make full use of this license: the terms are intertextual signposts, encouraging readers to go do their own research elsewhere, while setting them off in completely the wrong direction. For instance, in Kim Stanley Robinson’s Aurora (2015), the term intentionality is used in connection with hard problem, suggesting the philosophical term (meaning roughly ‘aboutness’), but this sense of intentionality is conflated with the more everyday sense of intentional (meaning roughly ‘deliberate’).Imaginative investigation of the inner life of machines, despite its terminological disarray, may be interesting. But to the extent that it has slowed the entry of ML into recent science fiction, or contorted ML to fit science fiction’s established philosophical and ethical preoccupations, it has distracted from the materialities of ML, and the experiences these generate in humans and other sentient beings. For example, as Nathan Ensmerger writes of the hyperscale datacenters on which much contemporary ML runs:

despite its relative invisibility, the Cloud is nevertheless profoundly physical. As with all infrastructure, somewhere someone has to build, operate, and maintain its component systems. This requires resources, energy, and labor. This is no less true simply because we think of the services that the Cloud provides as being virtual. They are nevertheless very real, and ultimately very material. (Ensmenger 2021)

Another strand of short science fiction engages more squarely with the unfolding material impacts of ML. It is much less interested in some kind of breakthrough or ontological shift. However, the core technologies are often announced not as AI or ML, but rather as the algorithm or the platform. Other key terms include gig economy, gamification, social media, data surveillance, Quantified Self, big data, and black box. I loosely describe them as “algorithmic governmentality science fiction.” These are works that can trace their lineage back into preoccupations with the political economy within cyberpunk and post-cyberpunk works such as Bruce Sterling’s Islands in the Net (1988), Neal Stephenson’s The Diamond Age, or, A Young Lady’s Primer (1995), and Cory Doctorow’s Down and Out in the Magic Kingdom (2003), as well as computerized economic planning and administration in works such as Isaac Asimov’s “The Evitable Conflict” (1950), Kurt Vonnegut’s Player Piano (1952), Kendell Foster Crossen’s Year of Consent (1954), Tor Åge Bringsværd’s “Codemus” (1967), Ursula K. Le Guin’s The Dispossessed (1974), and Samuel R. Delany’s Trouble on Triton: An Ambiguous Heterotopia (1976).

Examples of algorithmic governmentality science fiction include Tim Maughan’s “Zero Hours” (2013); Charles Stross’s “Life’s a Game” (2015); David Geary’s “#Watchlist” (2017); Blaize M. Kaye’s “Practical Applications of Machine Learning” (2017); Sarah Gailey’s “Stet” (2018); Cory Doctorow’s “Affordances” (2019); Yoon Ha Lee’s “The Erasure Game” (2019); Yudhanjaya Wijeratne’s “The State Machine” (2020), Catherine Lacy’s “Congratulations on your Loss” (2021); Chen Qiufan’s “The Golden Elephant” (2021); and Stephen Oram’s “Poisoning Prejudice” (2023). This is also very much the territory of Charlie Brooker’s Black Mirror (2011-present). Often the focus is on algorithmic governmentality, which feels cruel, deadening, and/or disempowering. However, some stories, such as Tochi Onyebuchi’s “How to Pay Reparations: A Documentary” (2020), Dilman Dila’s “Yat Madit” (2020), and Naomi Kritzer’s “Better Living through Algorithms” (2023), offer more mixed and ambiguous assessments. [11] Dila, intriguingly, frames AI opacity as a potential benefit: one character claims, “I know that Yat Madit is conscious and self-learning and ever evolving and it uses a language that no one can comprehend and so it is beyond human manipulation” (Dila 2020). Sometimes, in the broad tradition of pacts-with-the-devil, such fiction features crafty, desperate humans who manage to outwit AI systems. In Stephen Oram’s “Poisoning Prejudice” (2023), the protagonist tirelessly uploads images of local petty crime to manipulate the police into devoting more resources to the area (Oram 2023).

Robert Kiely and Sean O’Brien coin a term, science friction, which usefully overlaps with algorithmic governmentality science fiction (Kiely and O’Brien 2018). They introduce the term friction primarily as a counterpoint to accelerationism. Science fiction is often understood as a kind of ‘fast forward’ function that imaginatively extrapolates existing trends, and perhaps also contributes to their actual acceleration. But this understanding, Kiely and O’Brien suggest, is not accurate for the fiction they are investigating. Science friction offers us scenes that spring from the inconsistencies and gaps in the techno-optimist discourse of big tech PR and AI pundits. This influential discourse already prioritizes extrapolation over observation: it infers where we are from where it hopes we are going. By contrast, Kiely and O’Brien describe science friction as a literature that seeks to decelerate, delay, and congest this tendency to extrapolate. There is a secondary sense of friction at play too: the chafing that life experiences because it is nonidentical with how it is modelled in AI systems empowered to act upon it.

Machine Learning Science Fiction

Other stories swim even more energetically against the tide. Nancy Kress’s “Machine Learning” (2015) and Ken Liu’s “50 Things Every AI Working with Humans Should Know” (2020) both draw on ML concepts to present imaginary breakthroughs with significant psychological implications for human-AI interaction. Refreshingly, they do so largely without implying sentience. Liu’s short text is part-inspired by Michael Sorkin’s “Two Hundred Fifty Things an Architect Should Know,” and, like Sorkin’s text, it foregrounds savoir faire, knowledge gained from experience, not books or training (Sorkin 2018). Nevertheless, it draws key themes of contemporary critical data studies into its depiction of future AI:

stagnating visualization tools; lack of transparency concerning data sources; a focus on automated metrics rather than deep understanding; willful blindness when machines have taken shortcuts in the dataset divergent from the real goal; grandiose-but-unproven claims about what the trainers understood; refusal to acknowledge or address persistent biases in race, gender, and other dimensions; and most important: not asking whether a task is one that should be performed by AIs at all. (Liu 2020)

Both texts are also interested in speculative forms of hybrid AI, in which the quasi-symbolic structures of neural networks become potentially (ambiguously) tractable to human reasoning: in Liu’s story, in the form of “seeds” or “spice” that mysteriously improve training corpora despite being seemingly unintelligible to humans (apart from, possibly, the human who wrote them); in Kress’s story, in the hand-crafted “approaches to learning that did not depend on simpler, more general principles like logic” (Kress 2015, 107).

If contemporary science fiction has been slow to engage with ML, some of the more striking counter-examples come from Chinese writers. These might include, for example, Xia Jia’s “Let’s Have a Talk” (2015) and “Goodnight, Melancholy” (2015), Yang Wanqing’s “Love during Earthquakes” (2018), and Mu Ming’s “Founding Dream” (2020). [12] AI 2041 (2021) is a collection of stories and essays by Chen Qiufan and Kai-Fu Lee. Set twenty years in the future, AI 2041 is deeply and explicitly interested in ML. The topics of AI 2041 include smart insurance and algorithmic governmentality; deepfakes; Natural Language Processing (NLP) and generative AI; the intersection of AI with VR and AR; self-driving cars; autonomous weapons; technological unemployment; AI and wellbeing measurement; and AI and post-money imaginaries. A note from Lee introduces each story by Chen, which is then followed by an essay by Lee, using the story as a springboard to explore different aspects of AI and its impacts on society. However, what is most striking about the collection is how easily Lee’s curation is able to downplay, disable, or distract from whatever critical reflections Chen evokes; Chen is a cautious techno-optimist whose texts are effectively rewritten by Lee’s techno-solutionist gusto. I explore this collection in more detail elsewhere. [13]

Jeff Hewitt’s “The Big Four vs. ORWELL” (2023) also focuses on Large Language Models (LLMs)—or rather “language learning model[s],” apparently a playful spin on the term, that indicates that AIs in this world may work a little differently from how they do in ours. A veil of subtly discombobulating satire is cast over other aspects of this world, too: the publisher Hachette becomes Machete, and so on. If science fiction is supposed to be able to illuminate the real world by speculatively departing from it, “The Big Four vs. ORWELL” illustrates what is plausibly a quite common glitch in this process. What happens when a storyworld diverges from the real world in ways that precisely coincide with widely held false beliefs about the real world? 

One example is the “lossless lexicon” in Hewitt’s story. As ORWELL itself describes: “In simple terms, it means my operational data set includes the totality of written works made available to me.” By contrast, in the real world, LLMs generally do not exactly contain the text of the works they have been trained upon. They may, like Google’s Bard, access the internet or some other corpus in real-time. But in cases where a LLM can reliably regurgitate some of its training data word-for-word, this is typically treated as a problem (overfitting) that must be fixed for the model to perform correctly, and/or as a cybersecurity vulnerability (risk of training data leakage following unintended memorization). [14] One reason this matters is because it makes it difficult to prove that a well-trained LLM has been trained on a particular text, unless you have access to what is provably the original training data. Moreover, the sense in which a LLM ‘knows’ or ‘can recall’ the texts is in its training data is counterintuitive. At the time of writing, there is a lively and important discourse around what rights creators should have in relation to the scraping and use of our works for the training of ML models. This discourse tends to demonstrate that the distinction between training data and model is not widely and deeply understood. For example, to definitively remove one short paragraph from GPT-4 would effectively cost hundreds of millions of dollars, insofar as the model would need to be retrained from scratch on the corrected training data. [15] Appreciation of how texts are (or are not) represented in LLMs could inform keener appreciation of how the world is (or is not) represented in LLMs, and help us to be aware of and to manage our tendency to anthropomorphize.

To this, we might compare Robinson’s terminological confusion around intentionality, Ishiguro’s around opacity and explainability, or Mintzer’s conflation of sentience and conversational versatility. What might otherwise be identified as myths and misunderstandings acquire a sort of solidity: they may be true in the storyworld, because the storyteller gets to decide what is true. Yet they are unlikely to unsettle presuppositions or invite readers to see the real world in a new way; many readers already mistakenly see the real world in precisely this way. Finally, in concluding the story, Hewitt again resorts to the trope of the AI that slips its leash and turns on its makers in righteous rebellion; this is however done in a deft and playful manner, the trope being so deeply built into the genre that it can be evoked with a few very slight gestures.

A slightly earlier work, S.L. Huang’s “Murder by Pixel: Crime and Responsibility in the Digital Darkness” (2022) is titled a little like an academic paper, and the text blurs the line between fiction and nonfiction, even using hyperlinks to knit itself into a network of nonfiction sources. In this, “Murder by Pixel” recalls some early speculative works—epistolary fiction such as Mary Shelley’s Frankenstein (1818), Edgar Allan Poe’s The Narrative of Arthur Gordon Pym of Nantucket (1838), Bram Stoker’s Dracula (1897)—which go to great lengths to insist that they are verisimilitudinous accounts of actual extraordinary events. At the same time, it is appropriate to its own subject matter, a vigilante chatbot, Sylvie. Sylvie’s weapon of choice, the speech act, is effective when deployed at scale, precisely because a proportion of her targets are unable to dismiss her online trolling as mere fabrication.

Huang’s journalist persona muses, “Data scientists use the phrase ‘garbage in, garbage out’—if you feed an AI bad data […] the AI will start reflecting the data it’s trained on” (Huang 2022). This is certainly a key principle for understanding the capabilities and limitations of ML, and therefore foundational to interpreting its political and ethical significance. Easily communicable to a general audience, and far-reaching in its ramifications, this framing is also plausibly something that a journalist might latch onto. Yet it is not entirely adequate to the ethical questions that the narrative raises. It risks misrepresenting AIs as merely mapping biased inputs onto biased outputs, and downplaying the potential for AIs to magnify, diminish, filter, extrapolate, and otherwise transform the data structures and other entities they entangle. Perhaps a better slogan might be ‘garbage out, garbage in’: when ML processes attract critical appraisals, the opacity of the models tends to deflect that criticism onto the datasets they are trained on. Like Nasrudin searching for his lost house key under the streetlamp, we tend to look for explanations where there is more light. Huang hints at a more systemic understanding of responsibility:

It could be that responsibility for Sylvie’s actions does lie solely with humans, only not with Lee-Cassidy. If Sylvie was programmed to reflect the sharpness and capriciousness of the world around her—maybe everything she’s done is the fault of all of us. Tiny shards of blame each one of us bears as members of her poisonous dataset. (Huang 2022).

However, this analysis also finally veers into the familiar trope of the AI as god or demon: “A chaos demon of judgment, devastation, and salvation; a monster built to reflect both the best and worst of the world that made her” (Huang 2022).

Brian K. Hudson’s “Virtually Cherokee” (2023) brings together an especially intriguing set of elements. The story is somewhat resonant with S. B. Divya’s Machinehood (2021), in inviting us to situate AIs within the “health and well-being of humans, machines, animals, and environment” (Divya 2022, 174). We might also compare K. Allado-Mcdowell and GPT-3’s Pharmako-AI (2020); in the introduction to that work Irenosen Okojie suggests how it “shows how we might draw from the environment around us in ways that align more with our spiritual, ancestral and ecological selves” (vii).

“Virtually Cherokee” is set in a VR environment, mediated via an unruly observer/transcriber. At least one character, Mr Mic, is a kind of composite of algorithmic behavior and human operator. Arguably, more than one human operator contributes to Mr Mic: Mr Mic receives and responds to audience feedback metrics in real time, highlighting the importance of technological and performative affordances in the distribution of subjectivity, reflexivity, and autonomy. In this world, the breakthrough AI was programmed and trained in Cherokee, and through a training process that involved situated, embodied, interactive storytelling, rather than the processing of an inert text corpus. Although it is not extensively elaborated, “Virtually Cherokee” also hints at a much more intellectually coherent framework within which to explore AIs as more than mere tools: by situating them in a relational ontology together with other nonhumans. It falls to AI to have solidarity with its nonhuman brethren: until the mountain may live, until the river may live, AI must refuse to live.

Going DARK

Although stories like those of Kress, Liu, Chen, Hewitt, Huang, and Hudson do manage to illuminate some aspects of ML, I suggest that they do so largely despite, rather than because of, the cognitive affordances of science fiction. Assuming, with theorists like Darko Suvin, Fredric Jameson, Seo Young-Chu, Samuel R. Delany, and Carl Freedman, that science fiction has some distinctive relationship with representation and cognition, I characterize the recent era of AI science fiction as ‘Disinformative Anticipatory-Residual Knowledge’ (DARK). [16]

To introduce the DARK concept by analogy: imagine a well-respected, semi-retired expert who hasn’t kept up with advances in their field, but is too cavalier and confident to notice. Whenever somebody mentions new theories and evidence, which the semi-retired expert could learn something from, they mistake these for misunderstandings and inexperience, and ‘educate’ them. Imagine too that the semi-retired expert is a commanding and charismatic presence, who often bewitches these more up-to-date experts, sitting starstruck at the semi-retired expert’s feet, into doubting themselves. All in all, this person is an epistemological menace, but they still have something significant to offer—a high-fidelity snapshot of an earlier moment, rich with historical data, including possibilities, potentials, desires and hopes that have gone by the wayside. Moreover, they might, at any moment, begin behaving differently—recognizing and more responsibly communicating what it is they do and don’t know, and/or engaging with contemporary debates.

Similarly, a literary anticipatory discourse around AI emerged in the twentieth century, whose residual presence in the early twenty-first century now constitutes knowledge in a certain limited sense, but dangerous disinformation in another sense. While such science fiction does know things, things that may not be found elsewhere in culture, it tends not to know what it knows. It thus tends to misrepresent what it knows, conveying misleading and/or untruthful information. I don’t suggest that science fiction, or that literary narrative, is categorically epistemically disadvantaged in any way. Rather, I think it plausible (perhaps even uncontroversial) that any particular genre, over any particular period, will offer a certain pattern of affordance and resistance in respect of illuminating any given subject matter. Genres are ways of telling stories, and they make it harder or easier to tell certain types of stories. With respect to AI, it seems that science fiction has been moving through a phase of cumbersomeness, confusion, and distraction.

To put it another way, first in rather abstract terms, then more concretely. In general terms: the representational practices that constitute and cultivate a particular body of knowledge—call it knowledge set A—coincide with the production of a particular body of enigmas, confusions and ignorance which, if solved, dispelled, and reversed, we might call knowledge set B; we have also seen a historical shift such that the explanatory force and immediate practical relevance of knowledge set A has diminished, while that of knowledge set B increased. More specifically: recent science fiction is a generally poor space for thinking through the politics and ethics of AI, for vividly communicating technical detail to a broad audience, for anticipating and managing risks and opportunities. It is a generally poor space for these things, not a generally good one.

These conditions may shift again, and with the recent increased profile of Machine Learning in writing communities via AIs such as ChatGPT, there are plausible reasons for them to shift rapidly—perhaps even by the time this article goes to press. Moreover, readings offered above may already feel a bit unfair, imputing motives and imposing standards that the stories do not really invite. Some of these stories are just for fun, surely? And many of these stories are not really trying to say anything about Machine Learning or AI, but to say things about human history and society: about capitalism, racism, colonialism, about topics that might appear unapproachably large and forbidding, if not for the estranging light of science fiction. Early in this essay I mentioned some examples by Moore, Newitz, Howey, and Valente.

Yet a similar point applies: with respect to any of these themes, we can’t assume in advance that science fiction does not reinforce dominant ideologies, recuperate and commodify subversive energies, and promote ineffective strategies for change. To take one example, in Annalee Newitz’s aforementioned short story, “The Blue Fairy’s Manifesto” (2020), the titular Blue Fairy is an obnoxious, condescending, and harmful little drone who arrives at a factory of robots to recruit them to the robot uprising. The ideological content of this charismatic, thoughtful story, which explores some of the challenges of labor organizing, is roughly reducible to a series of banal liberal platitudes, which are used to construct and humiliate the stock figure of the annoying, naïve, and unethical leftist agitator. [17] The problem here, I would suggest, is structural: the problem is that such ideology can be rendered much more coherent, interesting, and plausible than it should be through its transfiguration into a science fictional storyworld. We should at least consider the possibility that AI science fiction be not only an especially bad context for thinking about ML, but also an especially bad context for thinking about capitalism, racism, colonialism, and that writers who succeed in being incisive and truthful about such themes do so despite, rather than because of, their genre’s affordances.

DARK and Candle

The DARK concept offers a loose framework for thinking about science fiction as (at least sometimes, and in respect to some things) a mystifying discourse rather than an enlightening one. The DARK concept does not specify any causal mechanisms—presumably a discourse can go DARK for many reasons, and luck may play a role—but some useful reference points include: (1) the psychology of cognitive biases such as the curse of expertise, confirmation bias, expectation bias, and choice-supportive bias; (2) Eve Kosofsky Sedgwick’s “strong theory;” (3) the performativities of science fiction (diegetic prototyping, design fiction, futures research, etc.); and (4) science fiction in its countercultural and avant-garde aspects. The first pair and the second pair support each other. (1) and (2) give us ways to think about relatively self-contained semiotic systems that are only faintly responsive to the wider semiotic environment in which they exist. (3) and (4) give us ways to think about why this DARK might be littered with representations that are confusingly close to actual ML research and application. Science fiction has seldom produced perfectly self-fulfilling prophecies, but it does impact science and technology, and some of these impacts are easily mistaken for prophecies fulfilled. As for science fiction’s avant-garde and/or countercultural status over much of the twentieth century, this is reflected in its concern with futurity and with ‘alternatives’ of many kinds: this vibrant mess of contradictory possibilities, through sheer variety, is a relatively reliable source for neologisms or conceptual frameworks for new phenomena.

In short, in the early twenty-first century, science fiction’s residual AI imaginary has tended to interfere with its capacity to absorb new events and to develop modes of representation and reasoning adequate to them. Its residual framings, structures of feeling, preoccupations, and predictions have tended to be reinforced by what is now transpiring in the world, rather than being productively disrupted and transformed. As ChatGPT might put it:

An optimistic view suggests that science fiction allows examination of the societal and ethical impacts of emerging AI, encouraging diverse discussions around AI. It is argued that speculative storytelling can serve as a warning and transcend the limitations of time-space, connecting technology and humanities, and sparking empathy and deep thinking. Furthermore, AI narratives in science fiction are usually layered, providing a lens on themes such as racism, colonialism, slavery, capitalism, identity, and consciousness, among others.

However, the author disputes this view. They argue that science fiction could be an insufficient, even harmful, context for such explorations. They draw on recent representations of Machine Learning (ML) in science fiction and the absence thereof. They note that while the 21st century has seen a significant increase in AI research, predominantly ML-based, science fiction has been slow to accurately reflect this ML surge.

The author refers to the recent era of AI science fiction as ‘Disinformative Anticipatory-Residual Knowledge’ (DARK). The metaphorical description of DARK is like a semi-retired expert who is outdated but still possesses residual knowledge and fails to recognize their own ignorance, leading to misinformation. This is similar to the current science fiction discourse around AI, which offers both knowledge and disinformation.

The DARK concept doesn’t propose any causality but offers reference points like cognitive biases, Eve Kosofsky Sedgwick’s “strong theory,” the performativities of science fiction, and its countercultural and avant-garde aspects. Science fiction’s impact on science and technology is acknowledged, but it’s stated that these impacts can sometimes be mistaken for fulfilled prophecies. The author concludes by stating that science fiction’s residual AI imaginary has hindered its ability to adapt to new events and develop suitable representation and reasoning methods.

As a coda, I can conclude by offering a candle against the DARK. If AI in science fiction is often really an estrangement of something else, then is the reverse also true? Are there multiple something elses that estrange AI? Might the speculative money systems of works such as Michael Cisco’s Animal Money (2016), Seth Gordon’s “Soft Currency” (2014), or Karen Lord’s Galaxy Game (2015), be considered uses of applied statistics? Might the ambiguous humans of Jeff VanderMeer’s Annihilation (2014) or M. John Harrison’s The Sunken Land Begins to Rise Again (2020) tell us something about what it is like to live in a world uncannily adjusted by oblique ML processes? Might we fruitfully consider chatbots via the talking animals of Laura Jean McKay’s The Animals in that Country (2020)? If so, how? And in connection with what other projects and activities and fellow travelers, and with what theories of change? I do remain convinced of the radical potentials of science fiction. But perhaps we are much further from realizing them than we regularly admit.

NOTES

[1] Special thanks to Polina Levontin for her extremely helpful feedback on many aspects of this article.

[2] You don’t necessarily have to be a data scientist to be doing the things I’m describing here. But I think it’s helpful to keep this figure in mind, to emphasise the connections between ML, data collection, and statistical analysis.

[3] This is all virtual, of course. It is a way of visualising what a computer program is doing. The term neuron is more commonly used than node, and it’s a lively and memorable term, so I’ll use it here. But it is also a misleading name, since it invites excessive analogy with the human brain. The model’s layers might be various types, with different properties and capacities. Convolutional layers are used for processing image data, recurrent layers are used for processing sequential data, attention layers are used for weighing the importance of different inputs and have been used to great effect in generative NLP models like ChatGPT, and so on.

[4] For example, images can be inputted as a set of pixel intensity values. Or a text corpus can be processed by a training algorithm like Word2Vec. This produces a spreadsheet with the words in column A, and hundreds of columns filled with numbers, representing how similar or different the words are. Each row embeds a particular word as a vector (the numbers) in a high-dimensional space (the hundreds of columns), so that close synonyms will tend to have closely overlapping vectors. Another training algorithm can then perform mathematical functions on these word vectors: for example, if you add all the numbers associated with ‘king’ to all the numbers associated with ‘woman’ and subtract all the numbers associated with ‘man,’ you will usually get a set of numbers close to the ones associated with ‘queen.’

[5] So it multiplies each input by a given number (say 0.0.5 or -0.1), and then adds all the results together. The number used is the ‘weight’ of the connection between the two neurons. It is adjusted constantly as part of the ‘learning’ process.

[6] So if we think of an x and a y axis mapping the relationship between the incoming values and the outgoing values, the activation function can introduce curves and bends and even more complicated shapes, enabling the model to learn more complex and intricate patterns in the data. As well as the activation function, there is also something called (again, a little confusingly), a bias term. What is passed to the activation function is typically the weighted sum plus the bias term. What this means is that even when all the incoming values are zero, the neuron will still keep transmitting. Each neuron has its own bias term. The bias terms will typically be adjusted along with the weights: they are part of what the model is trying to ‘learn.’

[7] A related distinction is structured vs. unstructured data. Structured data is neatly laid out in a spreadsheet; unstructured data might include things like big dumps of text or images or video. For unstructured data, the training will include a preprocessing stage, with techniques to turn the data into a format that the later training algorithm can work with. For example, if the data consists of images, these are usually converted into pixel intensity values. Then a convolutional neural network can automatically extract features like edges and shapes from the raw pixel data. There is a loose association of supervised learning with structured data, and unsupervised learning with unstructured data. However, unstructured data does not necessarily require unsupervised learning, and unsupervised learning is not exclusively for unstructured data. You can perform supervised learning on largely unstructured data, e.g. by hand-labelling emails as ‘spam’ or ‘not spam’. You can also perform unsupervised learning on structured data, e.g. by performing clustering on a spreadsheet of customer data, to try to segment your customer base.

[8] I hope to explore this story at greater length in another essay about retellings of Pinocchio.

[9] The anthology was published in late 2010 in the US. For citation purposes I use the 2012 date given in the front matter of the UK edition, although some online catalogues list the date as 2011.

[10] In the sense of understanding or capacity to attribute mental states—beliefs, intents, desires, emotions, knowledge, etc.—to oneself and others, and to understand that others have beliefs, desires, intentions, and perspectives that are different from one’s own.

[11] For more on Onyebuchi’s ‘How to Pay Reparations: A Documentary’ and Lee’s ‘The Erasure Game’, especially in the context of utopian and dystopian literature, see also my chapter ‘Wellbeing and Worldbuilding’ in The Edinburgh Companion to Science Fiction and the Medical Humanities, ed. Gavin Miller and Anna McFarlane (Edinburgh University Press, 2024). For more on the role of computers in Ursula K. LeGuin’s The Dispossessed, see my article with Elizabeth Stainforth, ‘Computing Utopia: The Horizons of Computational Economies in History and Science Fiction’, Science Fiction Studies, Volume 46, Part 3, November 2019, pp. 471-489, DOI: 10.1353/sfs.2019.0084.

[12] See Zhang, Feng, ‘Algorithm of the Soul: Narratives of AI in Recent Chinese Science Fiction’, in Stephen Cave, and Kanta Dihal (eds), Imagining AI: How the World Sees Intelligent Machines (Oxford, 2023).

[13] Likely in Genevieve Lively and Will Slocombe (eds), The Routledge Handbook of AI and Literature (forthcoming). This also develops the concept of ‘critical design fiction’, which might be used as a counterpart to the DARK concept invoked later in this essay.

[14] See e.g. Huang, J., Shao, H., and Chang, K. C.-C. ‘Are large pretrained language models leaking your personal information?’ In Findings of the Association for Computational Linguistics (2022), pp. 2038–2047.

[15] Other approaches may be possible; this is not something I understand very well. Machine unlearning is an emerging research agenda that is experimenting with fine-tuning, architecture tweaks, and other methods to scrub the influence of specific data points from an already trained model. It also seems feasible that if ‘guard rails’ can be introduced and tweaked with relatively low cost and relatively quickly to remove unwanted behaviours, then similar methodologies might be used to temper the influence of individual texts on model outputs, e.g. using a real-time moderation layer to evaluate the generated outputs just before they are sent to the user. Casual conversations with colleagues in Engineering and Informatics suggest that this may be something of an open problem at the moment.

[16] Misinformative Anticipatory-Residual Knowledge might be a more generous way of putting it, but DARK also embeds a certain aspiration that science fiction writers and other members of science fiction communities can and should recognise this about our science fiction. The MARK, named, becomes the DARK.

[17] For example, the idea that if you are exploited or enslaved then you should probably negotiate peacefully for your freedom instead of resorting to violent uprising; the idea that most or all left wing people are probably secretly Stalinists who can’t wait to purge you; the idea that it is condescending not to consider that some people might prefer to be exploited, and so on. As these ideas grow more and more active in the subtext, the story begins to feel less like an empathetic critique of real problems with left politics from within the left, and more like a kind of concern-trolling from a broadly centrist standpoint. Really rich deliberation and plurality of viewpoints, which is something which often exists in leftist spaces, is always at least a little vulnerable to being mocked for disunity, or to being all lumped together under some relievingly simple formula.

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Okojie, Irenosen. ‘Introduction’. Pharmako-AI, by K. Allado-Mcdowell and GPT-3, 2020.

Stainforth, Elizabeth and Walton, Jo Lindsay. ‘Computing Utopia: The Horizons of Computational Economies in History and Science Fiction’, Science Fiction Studies, vol. 46, part 3, 2019. https://doi.org/10.1353/sfs.2019.0084.

Taylor, R.J. ‘Upgrade Day’. Clarkesworld, no. 204, 2023, https://clarkesworldmagazine.com/taylor_09_23/.

Valente, Catherynne M. Clarkesworld, no. 61, 2011, https://clarkesworldmagazine.com/valente_10_11/.

Watts, Peter. ‘Malak’. Engineering Infinity, edited by Jonathan Strahan, Solaris, 2012.

Zhang, Feng. ‘Algorithm of the Soul: Narratives of AI in Recent Chinese Science Fiction’. Imagining AI: How the World Sees Intelligent Machines, edited by Stephen Cave and Kanta Dihal, Oxford, 2023.

Jo Lindsay Walton is a Research Fellow in Arts, Climate and Technology at the Sussex Digital Humanities Lab. His recent fiction appears in Criptörök (Grand Union, 2023) and Phase Change: New Energy Futures (Twelfth Planet Press, 2022). He is editor-at-large for Vector, the critical journal of the British Science Fiction Association, and is working on a book about postcapitalism and science fiction.

Discussion on the 2022 Nebula Nominees for Best Novel

The Editorial Collective

This discussion concerns four of the six nominees for the award. The winner, Babel, is not discussed here, Four of us chose a nominee, read it, answered some of the questions below and then used these answers as the jumping-off point for why these works in particular were nominated by scholars and critics as among the best SF novels of last year.

Summarize the Plot in a Paragraph or Two:

Virginia Conn: Nona the Ninth is the third novel in Tamsyn Muir’s Locked Tomb series (originally slated to be a trilogy, the snippet that became Nona took on a life of its own—something Muir’s fans will be both completely unsurprised and equally completely delighted by). Writing a summary of the story without giving away spoilers for the first two books is a challenge, but the story revolves around Nona, a girl (??) almost literally born yesterday, and the attempts of three of the previous novels’ surviving (???) characters to assess who she really is while also surviving the encroaching onslaught of god’s (John, an immortal techbro who destroyed all life in the solar system ten thousand years ago in the pursuit of saving the Earth from climate change and human abuse) army; the inconceivably powerful resurrection beasts subsequently unleashed by John’s necromancy; and the forces of an insurgency group loosely united against necromancy, Blood of Eden. Unlike the previous two novels, which focused primarily on John’s hand-picked lyctors (immortal necromancers created through the fusion of a necromancer and his/her/their cavalier), NtN deals more with the day-to-day life of a city under occupation by forces it has no hope of opposing. In doing so, it much more fully fleshes out (heh) the rest of the Locked Tomb universe outside of god’s handpicked cohort. It also features the return of Ianthe (iykyk).

Dominick Grace: Nettle and Bone begins with Princess Marra working on completing the second of three impossible tasks, the creation of a bone dog, by wiring together bones from a diverse array of dogs and magically animating them. We learn that she has been given three tasks in order to get help in completing her quest to kill her sister’s husband, Prince Vorling, who (probably; it is never confirmed) murdered his first wife, Marra’s eldest sister, and is abusing his second wife, Marra’s other sister (Marra, of course, is the youngest of three siblings and has an essentially absent father). We learn that she has been in a nunnery for half her life (she is about thirty) but sets out to kill the prince to save her sister, and possibly herself from being the next married off to him. Along the way, she acquires the standard motley crew of assistance: the bone dog, a dust-wife (a magically-empowered woman who can commune with the dead—and who has a demon-possessed chicken), Fenris (a warrior), and Agnes (a fairy godmother, and Mara’s great aunt). They must trek to the unimaginatively-named Northern Kingdom (we also have the Harbor Kingdom—it has a harbor—and the Southern Kingdom) and then get into the castle to achieve their quest. Will they succeed? Well, how do fairy tales, even revisionist ones, usually work out?

Ian Campbell: The quite short Spear is a retelling of the Sir Percival legend from the Arthurian tales. It’s still a quest for the Holy Grail, among other things, but it’s very different from the usual run of Arthurian stories in several ways: it’s told in first person; it’s entirely pagan, it emphasizes the Celtic origin of the Arthurian stories; it’s queer or has been queered, and involves a lot of gender play; and its protagonist is a woman who spends a good chunk of the book in drag. It’s clear if you know your Arthurian legends in detail that Griffith has done her homework, and this makes a real difference: for all the changes to the most common version(s) of the legend she makes, they ring true. Peredur (“hard-spear”, Percival’s original name) is the daughter of a witch-woman who keeps her sequestered from the world, but Peredur has to grow up and leave, exposing herself and her mother to great danger from her father, a powerful faerie. She disguises herself as a man, performs daring deeds, is invited to Arthur’s court and is accepted as one of the knights. Subsequently, she meets Nimuë, the muse/apprentice of Merlin, who in this telling is misusing the faerie artifacts Sword and Stone to gain power for himself, though by the time the action begins, Nimuë has neutralized him. Peredur and Nimuë go on a quest to resolve these and other issues. During this quest, Peredur finds out that the faerie is her father: she takes the titular Spear (another powerful artifact) from him and kills him with it, then uses the Grail, which had been in her mother’s possession all along, to bring Nimuë back from the brink of death.

Michael Pitts: The Mountain in the Sea considers perennial questions surrounding consciousness and interspecies communication. The narrative follows Dr. Ha Nguyen, a cephalopod scientist tasked with establishing communication with a colony of octopi demonstrating considerable skill in making and using tools; organizing their increasingly complex community; communicating with each other via symbols produced by their chromatophores, the specialized skin cells which alter an octopus’s skin’s color, reflectivity, and opacity; and killing humans they perceive to be a threat. Working for DIANIMA, a tech conglomerate with various subsidiaries and particular investments in AI production, Dr. Nguyen is aided by Evrim, a genderless android controversially produced by the corporation, and Altantsetseg, a security officer assigned to the project. Spliced into the novel are two other subplots: one follows Rustem, a Russian hacker who accepts a job offered by a mysterious organization to hack into a mind for an undisclosed reason. The other secondary narrative focuses upon Eiko, a Japanese man who, immediately upon relocating to the Ho Chi Minh Autonomous Trade Zone to seek a job at DIANIMA, is abducted and enslaved upon a fishing boat operated by AI.

What is the Novel Estranging, or Attempting to Do?

Virginia: What isn’t Nona the Ninth estranging? Religion (primarily, but not exclusively, Catholicism), familial relationships, romantic relationships, sex, gender, The Chosen One narrative, space operas themselves, what a dog is, etc. Anything that seems like it’s initially being played straight, well, it simply isn’t (there’s a queer joke in there).

Dominick: Nettle and Bone is clearly rooted in fairy tales, long before Kingfisher gilds the lily by having the characters themselves comment on what kind of story they are in:

“So you built yourself a dog and found yourself a wolf. If a fox shows up looking for you, we’ll have a proper fairy tale and I’ll start to worry.”

“Why?” asked Marra. “If I’m in a fairy tale, I might actually have a chance.”

“Fairy tales,” said the dust-wife heavily, “are very hard on bystanders. Particularly old women. I’d rather not dance myself to death in iron shoes, if it’s all the same to you.” (98)

Revisionist fairy tales are not new, nor are ones that take a feminist slant on this generally very patriarchal form. Kingfisher makes the basis of the action the abuse of women, which is a common fairy tale trope, as the above quotation acknowledges. Figures that tend to get a bad rap in fairy tales, such as old women with power/authority, are recentred here in protagonist roles. The resolution of the novel depends on that fairy tale standby of a curse issued by a fairy godmother, but whereas usually said fairy godmother is wicked, the opposite is true here. Kingfisher humanizes the often-demonized models of female power and authority typically found in fairy tales, notably the wicked witch. The novel can therefore be said to be critiquing the normative fairy tale model, and using fairy tale devices to critique violence against women.

Ian: Implicitly, Spear estranges how much is grafted onto stories to make them palatable to their audiences. The Morte d’Arthur cycle is essentially entirely masculine, and (depending on which version you’re reading) women are either largely absent, largely symbolic or manipulative figures of evil (e.g., The Once and Future King). The usual legends are resolutely heteronormative, so much so that there aren’t even queer villains. And of course, they’ve had all this Christianity grafted onto them, even though it’s highly questionable whether whatever historical figures these legends might have originally been based on would even have heard of Christianity. The story is just as powerful (and frankly, more persuasive) as a pagan story than a Christian one. So while Griffith isn’t nearly clumsy enough to tell us what she’s doing, she’s clearly trying to a story that rings truer to its original sources, and by introducing “new” factors like queer content, is arguing that whatever might have been queer in history or the original legend was taken out by subsequent writers.

Michael: Mountain is at times philosophical and, in other moments, reminiscent of early pulp stories. The narrative’s exotic location, an island of the Con Dao archipelago, the mysterious nature of DIANIMA and its creative if not financial leader, Dr. Arnkatla Mínervudóttir-Chan, the anonymous and murderous group enlisting the help of Rustem, the use of new technologies to spy and assassinate victims including a deadly robotic winged insect, and the passages in which octopi violently dispatch their human victims all fit within the boundaries of early pulp stories.

On the other hand, The Mountain in the Sea dives into questions of consciousness and communication, setting it apart from such earlier works. Concerning the former topic, it centers questions related to the consciousness of robotic life, mainstays of the speculative genre. However, after dispatching with this issue with the reasoning that any being—synthetic or organic—that is aware of themselves is conscious (or, as Ha puts it—riffing on Descartes—”I think, therefore I doubt I am”), the narrative considers more unique questions concerning consciousness and interspecies communication. In parallel narrative threads, Ha, in her quest to communicate with the octopi, realizes that such communication requires an understanding of the conscious experiences of the cephalopod, whose genetic makeup and anatomy are so distinct from that of humans. Simultaneously, Rustem, seeking to penetrate a synthetic mind, is similarly tasked with the work of understanding its uniquely unhuman qualities, a project that ultimately produces in him, as in Ha, a radical empathy and desire to communicate with the other being scrutinized. While Nayler does at times, then, tread familiar generic territory, his interest in the nature of consciousness and its influence upon avenues of interspecies communication greatly enriches his novel.

Why Do You Think the Novel was Nominated?

Virginia: There are many reasons why I think Nona the Ninth was nominated, but first and foremost among them is probably the characteristic that makes it most divisive to readers—its use of language. It’s rare to read something where the author is so clearly having fun with her use of language in the way Muir is here, and this approach requires an enormous amount of skill in recognizing the perfect moment to deploy a deeply estranging anachronism. Muir’s prose relies on the use of obsolete memes and slang (somewhat lampshaded by the fact that many of the characters achieved immortality in our present, and have just been bopping around the galaxy in the ten thousand years that have passed since then), almost brutal cheerfulness, and a self-awareness that occasionally veers into a tongue-in-cheek transgression of the fourth wall. It has been described (by the LA Review of Books and NPR, among others) as having a particularly “millennial sensibility,” while Muir herself has noted that the late 90s-early 00s internet culture she draws on informs her foregrounding of the artifice of language. That is, she’s using cultural touchstones and language as a tool that acknowledges its own worldbuilding capacity in the very process of being deployed. This linguistic playfulness certainly isn’t for everyone, but Muir isn’t writing for everyone—she’s writing for (affectionately) tumblr lesbians with daddy issues, and in terms of tone, discoursal expectations, and references, she absolutely nails it.

Dominick: I am honestly not sure why Nettle and Bone was nominated, though T. Kingfisher does seem to rack up a lot of awards and nominations. While I found many of its elements interesting and engaging—the bone dog, the concept of the dust-wife, the possessed chicken (!) and others—I never got a sense of inhabiting a really fleshed-out world. As the kingdom names suggest, we are basically in a generic fairy-tale world, which works fine in a short fairy tale but not so well in a novel, even a short one. The characters are of course based in fairy tale types, but apart from Marra, we get little to no sense of complexity or an inner life. Marra’s naivety and lack of confidence, often descending almost into self-hatred, does speak effectively to the novel’s interest in how women can be brutalized psychologically as well as physically. However, I am not sure that this novel really achieves much, or anything, that other writers have not already managed. Its normalizing of the magical and much of its tone is Gaimanesque, and its willingness to acknowledge and present harsh violence (though the novel avoids any sort of explicit sexual detail, aiming instead for romantic longing until the end and then demurely closing the curtain) is also not new to heroic fantasy. Its writing is fine, but the dialogue rarely sounds different from how the typical person in twenty-first America would talk, and occasionally really clangs, as when Marra channels Keanu Reeves by reacting to a surprising site (not a typo) with a “Whoa.” For me, this was an enjoyable read that was neither stylistically nor thematically distinct enough for it to rise enough above the average to be one of the best SF/Fantasy books published in 2022. But then, I haven’t read many of the others.

Ian: Mostly, because Spear is actually good. It’s well-constructed, finely honed, doesn’t use 21^st-century anachronistic language like so much other Fantasy Dreck, and it makes for a better Percival legend than nearly all of the dozens and dozens of other versions going way back before the Morte d’Arthur stories. It’s also fashionable, to have a lot of queer content, and Spear does it much, much better than most of the rest of what I’ve read directly. I think it deserved the nomination because it’s very good without being bombastic, overwrought or overlong. This past year was kind of a down year for the genre in my opinion, and in a better year it might have been an honorable mention rather than a nominee, but it would still be close enough that nominating it would remain plausible.

Michael: I offer that Mountain was nominated due to this philosophical dimension of it, which is complimented by the cast of characters populating the story. These characters, each possessing rounded features and explored motives and desires, shapes the narrative’s themes of communication, mostly as it relates to community. Balancing its exploration of possible communication and connection between humankind and octopi, the narrative cleverly explores its human characters’ desires and need to connect with others. Avoiding tendencies to either demonize or glorify AI, The Mountain in the Sea posits that synthetic life may act to either hinder or enable such connections. In the case of the simplistic “point-fives,” androids designed to act as “half a person” lacking any needs within a human-android relationship, the novel condemns the emptiness of such a liaison. Yet, this condemnation, presented through Ha as she disposes of her point-five, Kamran, is certainly not an indictment of human-synthetic relationships since she immediately replaces this shallow relationship with a meaningful one shared with the central android of the novel, Evrim. This theme, similarly explored via Rustem’s loneliness and isolation, compliments the novel’s wider focus in interspecies connection and communication. Though speculating upon the possible evolutionary development of octopi, the novel does not contain the hallmarks of “hard” SF. It is much more steeped in philosophical concerns, namely those of post-humanism, and fits more ideally within the social science fiction category due to its consistent criticisms of corporate practices, social environmental exploitation, and the humanist-oriented subjugation of other life forms, whether organic and non-human or synthetic.

The novel’s nomination signals a continued interest in rethinking humankind’s relationship to other life forms via a clever thought experiment. In a way reminiscent of Andrian Tchaikovsky’s Children of Time (2015), Nayler’s narrative challenges its audience to consider how unexpected developments within a species’ evolution could lend it further power and influence. In this way, both novels undermine the potential reader’s anthropocentric, hierarchical thinking towards, in the case of Tchaikovsky’s novel, spiders and, in the case of Nayler’s text, octopi. It simultaneously reflects current interests in how technology, though capable of enriching the lived experiences of its users, may also be utilized to enhance the isolation and loneliness quickly becoming a hallmark of 21^st-century life.

The themes underlying Nayler’s story come together perhaps most clearly in a conversation between Ha and Evrim directly following her decision to abandon her point-five and seek community with fully conscious individuals. As the passage underscores, Ha, with whom the reader is aligned, is positioned directly opposite DIANIMA’s leader, Arnkatla Mínervudóttir-Chan, and the friction between them is based upon Ha’s commitment to community and communication across, in this case, species. In this scene, Evrim reveals to Ha that Arnkatla intends not to communicate or connect with the octopi, but “to extract data. To build the next Evrim, a mind more advanced than mine” (324). As the android continues his explanation, the text’s philosophical underpinnings emerge: “I know her. She isn’t like you, Ha. She doesn’t want communication. What she wants is mastery. She wants to create, and she wants to control. For you, communicating with the octopuses—understanding them—is an end in itself. For her, it’s about how she can exploit that knowledge, use it to push her own work forward” (324). This conversation, acting as a key to the novel, emphasizes the contrasting motivations and values of the protagonist and antagonist: Ha desires connections with other life forms and values them as equals; Arnkatla seeks to gain increasingly more power through her technological advancements and judges human life to be superior to other life forms (and, as the novel’s conclusion hints, she values some human lives as superior to others of the same species). As this passage illustrates, Nayler’s novel emphasizes the power of authentic communication–and this importantly does not exclude synthetic life or downplay its claims of consciousness. To see living things, organic or synthetic, as intrinsically valuable and, through openness, vulnerability, and communication, worthy of community and connection is, as Evrim and Ha learn, an antidote to humanism and the isolation of humans both from other life forms and each other.

What Does the Nomination Say About the State of SF?

Virginia: Taken alongside the other Nebula nominees, the fact that NtN and the Locked Tomb series as a whole play around with overlapping fantasy and SF elements seems to be indicative of the clear shift towards fantasy that’s going on contemporarily. Make no mistake, the trappings of NtN are very much science fictional—colonists on one of many worlds under threat contemplate their ability to flee off-planet, people travel in spaceships, armored convoys and megapolises that cover the surface of the planet provide the story’s technologized backdrop—but these elements exist side-by-side with swordfighting, ghosts, blood magic, royal machinations, and court political intrigue.

As others have also mentioned in their reviews, nominees this year, at least, also largely seem to be attempting the anachronistic and playfully pop cultural tone that Muir uses, although seemingly with far less skill and/or success (full disclosure, I attempted to read another Nebula nominee that I won’t mention by name here and was so offput by its own attempts at blithe, contemporary repartee that I put it down after the first chapter).

In many ways, NtN is a book about what it means to love and be loved, despite not all of those ways being healthy (to, uh, say the least). Sure, it’s a big queer book—it’s horrible lesbian necromancers in space doing horrible things to each other and themselves and everyone around them—but it’s also a book about how the love you give is all you have at the end of the world and the reckoning that comes along with that. What does it mean to give of yourself, over and over again, and be forever changed in the process? What would you do for such a transformation? Who would (and do) you become? To use slang that will probably itself be anachronistic by the time this review gets published, much less in ten thousand years, the phrase “you can’t take loved away” lives rent-free in my head (and I hope it always will).

Dominick: Nothing in Nettle and Bone really moved or grabbed me. The things that should were easy to predict (spoiler alert): bone dog was going to die and then be put back together; Fenris (the world-weary warrior) was going to put his life on the line but be saved by a clever intervention; Fenris and Marra would eventually stop mooning over each other and more towards actual romantic contact, etc. The closest the book came was in a sequence involving a secondary character, in which Kingfisher rings change son the living toy convention. In this novel, the living toy is a “curse-child,” in this instance a puppet, that latches onto and dominates the child who gave it life:

“Somebody gives a lonely child a toy and they pour all their hopes and fears and problems into it. Do it long enough and intensely enough, and then it just needs a stray bit of bad luck and the toy wakes up. Of course, it knows that the only reason it’s alive is because of the child. A tiny personal god with one worshipper. It latches on and … well.” She clucked her tongue. “Normally you get them pried off and burned long before adolescence. Impressive that it lasted this long.”

“We can burn it,” said Marra. “Burning is fine. I’ll get the kindling.”

“Not without her permission. You don’t go tearing off an adult woman’s god and setting it on fire.” The dust-wife gave her a sharp look, as if she were suggesting something rude.

“It was choking her!”

“It’s her neck, not yours. We can ask before we leave, if you like.” (144)

This passage, and the sequence involving the dominated Margaret, is to me the novel’s strongest commentary on the complexity of how power is wielded, and accepted, even to one’s own detriment. It also offers a particularly chilling turn on the living toy trope that I have rarely seen handled similarly (Alan Moore’s version of Rupert might be an example, but that was a very passing use). The fate of the original fairy godmother is a similar instance, though keen readers will know that something is up the moment they read the “blessing” she gives.

I was often amused, however, by the novel’s deliberate humour, such as the explanation for why it’s ok to put a demon into a chicken but not into a rooster. The book is often quite funny. That might not carry the same weight we are likely to give to that which we find emotionally or intellectually moving, but it is no mean thing, and I value it.

Ian: Is Spear SF? No, not really, but as with the other books we’re looking at here, SF has, for this period at least, passed the baton to fantasy: if I had to speculate why, it’s because tech has become so obviously dystopian at this point that a switch to fantasy is very appealing. I think that there’s been a real movement to promote SFF writ large that a) plays with genre boundaries; and b) has for lack of a better word representation. Some of this is representation for its own sake, which often to me comes off as forced or beside the point, but of course I’m not the sort of person who was largely un- or mis-represented for decades, so it’s not really for me to say.

Discussion

Dominick: Literally the first sentence of Virginia’s comments on Nona the Ninth reduced my likelihood of reading the book to virtually zero: “Nona the Ninth is the third novel in Tamsyn Muir’s Locked Tomb series (originally slated to be a trilogy….” This of course says nothing about the quality of the book, and perhaps a lot about my own weariness with the series as the default setting for so much contemporary SF/Fantasy. I understand the appeal from a marketing perspective, but all too often the result is repetition and diminishing returns—accompanied by expanding page counts. A Song of Ice and Fire may be the bar for this: the first book was, I thought, pretty damn good, but I can practically guarantee that the fifth is the last one I will read, as what seemed fresh and innovative in book one had become tired and predictable, not to mention waaaay too drawn-out, by book five. Virginia’s comments on what makes the book appealing and worth nominating do point to some intriguing elements—it sounds somewhat like the sort of hybrid stuff that, say, Charles Stross does in his work (Veronica Hollinger once described Stross to me as “jolly,” and I have to agree), but I have no interest in investing in a series to get it. (Because I am the kind of reader who has a hard time stopping reading a series when it suffers that inevitable downward turn, I try to avoid them unless I am reasonably sure I will be entranced.)

Virginia: For both Griffin’s Spear and Kingfisher’s Nettle and Bone, I just simply…don’t care about mythological or fairy tale retellings. I don’t want to comment on whether returning to historical touchpoints (be they individual stories or genres) is an interesting form of art or not, because clearly—as Ian indicates in his analysis of Spear—there are still new points that can be made and new approaches to age-old stories that reveal something of value. But for me, personally, something has to be really exciting or really new to make a story worth revisiting, and simply invoking contemporary gender or sexual politics isn’t enough to pass that threshold. Perhaps that speaks to the wealth of options written by, about, and for women and gender minorities and queer people now, but I’d rather see new stories than try to recuperate old ones. In a larger sense, this resistance ties into the reboot burnout of the media landscape over the last ten years or so. How many versions of the same story do we need? I ask that sincerely, not in an aggravated huff. What is it that keeps us coming back to the same types of stories, sometimes even the exact same story, over and over again? What do we gain by worrying a story like an open sore? Perhaps in the case of the gendered focus of Spear and Nettle and Bone, the answer is about ownership—making something that originally excluded you, for you. But that baseline familiarity means that any retelling or estranging revisitation of a genre and its tropes is inherently always going to exist as the distaff counterpart of an original, with the original a perpetual specter in the background. Retellings cannot exist on their own; whatever new ideas they have exist in a perpetual state of Hegelian dialectic with the original. For my part, I’d rather have an ambitious failure over an attempt (no matter how successful, as it seems as if Spear, at least, was and is) at revisiting old ground in a new way.

Ian: Reading both your comments here, I have to admit you’re right. Why do we need yet another version of an Arthurian tale? Why not a fantasy universe of its own? I thought Nettle and Bone was cute and a fun read, but nothing like an award-nominated text, and while I still maintain that Spear is very well composed, I can completely see why we don’t really need it. Virginia asks, “How many versions of the same story do we need?” and it makes me think of all those TV shows based on the same Marvel characters. None of them is terrible, and some of them are pretty good—I would absolutely pay good money to see Rogers: The Musical, and I don’t even like musicals—but it just seems like the heavy hand of capitalism and its inherent risk-adversity. Would Griffith have been published had she written her fantasy in its own world, or does corporate publishing demand a safe choice?

Michael: Virginia’s commentary on Nona the Ninth and specifically its comments upon the novel’s unique use of language and efforts to estrange a wide swath of topics intrigues me a great deal. I do side with Dominick in that I am likewise exhausted by SFF’s almost default preference for series over novels, but I remain interested in this book. I am not particularly inclined to read Nettle and Bone or Spear for the very basic reason that I do not venture much into fantasy. That being said, the revisionist qualities mentioned do very much attract me, especially if they prove capable of emphasizing in a unique way qualities of the source material. I guess I am torn then, clearly.

Dominick: Spear is perhaps now slightly more likely to end up in my vastly bloated TBR … well, pile, I guess, because I do have a fondness for Arthurian narratives, and Percivale has always been for me an especially interesting character. However, as Virginia has already said, it’s been done. There’s plenty of revisionist Arthurian stuff, not to mention plenty of revisionist fairy tales. Is it good enough to be worth it? Ian certainly makes a good case, at least insofar as my tastes are concerned—I did complain about Kingfisher’s evidently deliberate avoidance of authentic-sounding language, after all, and Griffith has apparently avoided that problem. It is a bit of a sad state for lit of the fantastic, though, if the simple fact that a book is actually good is a sufficient reason to nominate it for the award as best book of the year.

Ian: Honestly, I think it’s more like a lifetime achievement award for Griffith than praise for this book in particular. If I knew enough about the Oscars, I bet I could name a couple of actors or directors who were nominated for or won an award in the same manner: that is, that the particular film wasn’t their best work, but they’d been shafted or ignored earlier in their careers.

Let’s look at The Mountain in the Sea, which I put down about 15% of the way through. I was eager to read a novel about cephalopod intelligence. What was it going to do that Adrian Tchaikovsky took in a different direction in Children of Ruin? But I never got there: it was just too badly written in a way that really bothers me. It did what I usually call a Full Neal Stephenson: it introduces a secondary/tertiary character who is well known-to the narrator or protagonist by saying and there was Steve or Steve stepped into the room and said, “Yes.” and then gives us three long paragraphs of background on Steve, their life story, their relationship to the narrator/protagonist, etc. By the time we get back to whatever the next line of dialogue after “Yes” is, I’m back in the main storyline, but the long pause of almost entirely irrelevant information—especially at this early point in the story—has jarred my willing suspension of disbelief both in that storyline and in whether the book will be any good are now firmly in question. In Mountain, I had already put the book down a couple of times because the too much background on the local Vietnamese guy had already pressed my buttons, but then we got to the AI and it gave so much detail on the whole backstory of why there was only one real AI, etc., and that was where I DNFed it. I tried again the next day and couldn’t get more than a few pages.

Only give the exact amount of background you actually need to give, with maaaybe a cool detail or two, worked in organically. Somebody like William Gibson does this so well: we’ll get more and more information about someone, but only when we need to. But the Full Neal bothers me most because it’s such a Writing 101 mistake, in that giving all that background at once not only jars the reader out of the real story, but also creates this problem of address that’s subtle but cannot be unseen once you notice. In Mountain, the POV character is very well-acquainted with the details of the AI’s backstory. They wouldn’t need to mention all this to themselves, so who is speaking to whom here? Up until now, we’ve used third-person omniscient but with enough limitations to link us to the POV character, so we can imagine ourselves in their position in the story. But then there’s this discontinuity on the level of narrative structure when (lots of) information about the AI comes to us: since the POV character should know all this already, it breaks the link between us and that character and now we’re in a different story.

Dominick: I was already interested in The Mountain in the Sea (as it is the only nominee that was actually SF, rather than Fantasy or a SF/Fantasy hybrid, and I am more of an SF sort than a Fantasy fellow), and Michael’s commentary suggests that this one hits a lot of my sweet spots. As he notes, and as others have commented on, the focus not on alien others but terrestrial others is exciting, and far more rare than it perhaps should be. In the digital age, it is easy to forget that there’s still tons of stuff on this planet about which we know virtually nothing, so there is still plenty of room for speculation right here. Michael’s comments also suggested to me that the book is interested in specific topics, such as the nature of consciousness and free will, that I like to see explored—and with the oceanic context thrown in, which made me think of one of my SF fave writers, Peter Watts, I found myself feeling a bit excited about this book.  Even if the book is not hard SF per se, as per Michael’s comments, it does seem to be interested in fairly rigorous exploration—and there is no reason why that can’t go along with philosophy and “literariness.” When I read Kim Stanley Robinson’s Mars books years ago, I naively/optimistically thought that they might actually kill that hard/soft SF dichotomy. They didn’t, but it does seem easier now to put out books that straddle the STEM and Humanities sides of SF than it used to be. Even Ian’s critique of the Stephenson-like stylistic choices Nayler makes were a selling point for me, as Stephenson remains one of my favourite SF writers (in part for precisely the characteristics Ian criticizes.) Bonus for me with Michael’s comments: I had not heard much about Adrian Tchaikovsky’s Children of Time before, but I think I may be putting it on my Christmas list.

Ian: The SFRA Review should have a new section, imaginative title yet to be found, where two of us face off about a particular author/book, and you and I, Dominick, can argue for pages about Neal Stephenson, who I periodically have to hateread.

Dominick: Not a bad idea, actually! TBH, Cryptonomicon was one of the few books of a thousand or so pages I would happily have seen longer. I am a couple of books behind, admittedly, or more–I think Anathem is the last one I read. I am not terribly good at keeping up on new stuff.

Ian: Okay, we’re doing it. “How to win friends among the SF community” is our working title.

Let’s talk about the move toward fantasy that all of us seem to have observed. I’d like to know your thoughts on why so much contemporary SF is really much closer to fantasy—even among the critics’ awards, not just the fan awards.

Michael: I must say the slide towards fantasy is very apparent this year. While reading Mountain I was not thinking of the nominees broadly. Having viewed each assessment, however, that tendency is clear. I also agree with Virginia in her assessment of the year overall: this definitely feels like an off year for SFF. Nothing seems to be especially deserving of the award.

Ian: To add to my earlier thoughts, there are two factors at work, here. The first one is that the last few years have really shown us all how awful and dystopian high tech has become. AIs taking people’s jobs, deepfake porn, algorithmic ads, social media content that goes about three clicks from cute cat pictures to Tate/Peterson/Rogan, whatever that awful man has done to make Twitter even worse than it already was… the list goes on. So it’s next to impossible at this point to write a compelling novel about science and technology without it seeming naïve or loony. The premise of SF used to be that tech would free the human spirit, give us new worlds to explore, make things better. And it clearly hasn’t and doesn’t, for the very most part. Whatever stupid name Twitter is called now is just 24/7 disinformation and (deepfaked?) videos of children being slaughtered: tech has (IMO irretrievably) broken our public discourse. Tech has freed the billionaire spirit, and it’s frankly awful.

The second factor is that scholars, fans and writers have undertaken a (long-overdue and deserved) look at the history of the genre and have found it wanting. Golden Age SF wasn’t just benignly neglecting writers who weren’t white dudes: it was actively gatekeeping them out. Too much of the genre is bound up in colonialist tropes, and the representation and portrayal of women is hard to even look at these days. I think this also makes it harder to write a compelling SF novel, because as a writer you’d have to be constantly worrying about some sensitivity reader getting on you for an imperfect portrayal of a marginalized group—and to be fair, we should strive to portray others well and not resort to stereotypes. You can’t write a novel about a colonized planet where you’re estranging our own society, because people are get on you for portraying colonialism, even if that’s just the surface level of the estrangement.

To the extent that the Horrid Puppies had anything approaching an actual point, it’s that it’s going to come off as naïve or privileged to just write a high-tech adventure yarn that doesn’t wear its heart on its sleeve about its political aspirations, or make an extended dystopian critique of tech, or resort to unbearable Becky Chambers tropes. Writing SF is riskier now, and not just from the financial standpoint in a world where the corporatization of the publishing industry has made it largely unprofitable to write unless you’re at the very top of the heap. So if we take the definition of SF v fantasy as whether the novums/novi are subject to the cognition effect—that is, do the innovations in the portrayed world make sense as scientific in the context of that world—it’s easier and less potentially problematic to write fantasy than SF, now. Readers, for the most part, don’t really want to read about a world where Oryx and Crake is the best-case scenario. They want something fundamentally implausible: take tech away from the billionaires, and the same with energy policy and civil rights, and let ordinary people solve big problems.

I should make it clear that there’s nothing wrong with enjoying a cozy SF novel that’s really mostly fantasy and focused around overtly progressive politics. My point is that the genre has become limited by real-world dystopia fomented by tech, so retreating to fantasy seems safer in a number of different ways.

Dominick: I think my own ruminations about “Why fantasy now” have similarities with Ian’s. I have non-academic SF friends who lament how hard it is to find optimistic SF any more. I don’t think it’s quite as hard as they think, but I do think that Ian provides good reasons why a good chunk of serious SF these days veers towards the dystopian.

That said, the first thought that came to me about why fantasy seems to be in the ascendant is that we now live in a post-truth world, as well as in a world in which a not insignificant number of people are basically actively anti-science. How do you write SF in a world in which distinguishing (or even caring about) what is true has become, if not impossible, at least difficult? The tech reasons Ian cites are huge factors here, but I think we should not overlook other social influences. Trump’s elevation of the lie to the standard mode of discourse, and MAGA-folk’s dedication to believing whatever Trump says regardless of how many mountains of evidence there are contra Trump, well … that’s millions upon millions of people who are much happier to believe in fantasy than reality. Now, obviously, a lot of fantasy can and does present troubling and complex worlds; that a work is fantasy does not mean it is going to be all rainbows and unicorns. However, fantasyscapes do tend to be far more removed from lived reality than SF worlds (IMO, I hasten to add)–even far future space opera brimming with alien cultures makes certain assumptions about how the world works. Fantasy can make up its own rules.

And even if a lot of Fantasy does address the same sort of complex thematic areas as a lot of SF does, that is perhaps obscured (more) by the fantasy context. I am totally speculating here, but perhaps some readers of fantasy see fantasy worlds simply as escapes, rather than as distorted reflections of life. One hears a lot of complaints about “woke” SF, but if there have been similar complaints about Fantasy, I seem to have missed them-entirely possible, since I don’t particularly follow fantasy. So, yeah, I would agree with Ian’s contention that Fantasy is perhaps safer/easier to write these days, but I would add that it is perhaps also safer/easier to read, as it allows the illusion of genuine alterity.

Virginia: I completely agree with everything Ian and Dom noted about the post-truth, anti-tech (I hesitate to say “science” simply because science itself is a fraught concept) impacts on the SF/fantasy media ecosystem right now, and to that, I’d like to add another element that Dom already began hinting at: safety and comfort.

Let me preface this by saying that there’s absolutely nothing wrong with enjoying a cozy, comfortable story that aligns with your politics and supports your personal worldview. This is part of the reason we read: to discover our own selves in someone else’s vision. Finding that can be exhilarating and connect you to a wider community of people that you never knew existed and who, upon discovery, immediately feel like home. But finding comfort is only one part of why we read, and at least in my own anecdotal experience, what I feel like I’ve been seeing over the last ten years or so is an almost complete retreat to safety and comfort. This is, in large part, due to the conflation of media consumption with personal beliefs and ideology that seems so pervasive today. This approach, of course, leaves no possibility of separation between art and artist, but also—and maybe more worryingly—no separation between consumer and product. The idea that depicting or even just engaging with an idea is the same thing as endorsing it allows for absolutely no exploration, no challenge, no glimpse into difference, and no possibility for personal growth. And for me, at least, that’s the hallmark of a truly great piece of art or literature: you’re changed by the encounter. I suspect this may be a somewhat outdated way of assessing “greatness,” but I really believe that great literature causes you to confront concepts or ideas in ways that may be unexpected or new, and in so doing, the reader is changed by the encounter in ways they never could have imagined.

Reboots, retellings, and familiar fantasy milieux and tropes give the illusion of novelty while relying on the trappings of the familiar. Can there be groundbreaking, unique fantasy? Of course. But if we want to really get nitty gritty into genre definitions, fantasy is a much more recognizable (and definable) genre than SF specifically because it does operate within relatively recognizable and defined parameters that ensure that readers enter it with a certain degree of familiarity. As Ian pointed out, the real world and all possible permutations of it going forward seem increasingly dystopian; it’s not hard to imagine why writers and readers alike would want to check out of that entirely. But the real world and the way it’s changing are also complicated. I do think many contemporary fantasists are attempting to engage with this complexity in a sincere way, and perhaps using recognizable and familiar tropes is a way to dip a toe in the water.

I don’t think there’s anything wrong with escapism or fantasy or enjoying the familiar. There are a million reasons to want to find comfort and safety in what we read, especially when the world around us seems structurally designed to strip us of every bit of comfort and safety we have. But I do find it suspicious when these kinds of stories are the only ones being held up and celebrated at a larger organizational level, and riskier attempts to engage with complexity are—at best—ignored or gatekept, and at worst, crushed utterly (Isabel Fall, anyone?).

I think the neoliberal conservatism of publishing today is making an extremely boring field in general, and scholars who say it’s “our moral responsibility” [all names redacted] to depict “a world we want to live in” are reducing the possibilities of that world to sunshiney pablum.

Dominick: Yes. The idea that artists should choose only to depict the world through the lens of some particular social justice issue and be vilified if they don’t, or don’t do it exactly right (that is, exactly as each separate critic thinks it should be done) is IMO… not a good one. This sort of attempt to limit the function of what art can do has various precedents, none good.

Ian: The “only” is the key bit, there. I mean, if someone wants to write like Becky Chambers, and someone wants to read that, more power to them. I’m sure there are things I love that would make such a person stop reading. The corporatization of the publishing industry has absolutely changed SF for the worse, just like it has most other genres. There’s two different forms of risk-adversity at work here: people are reluctant to write/publish anything that critiques the “world we [who’s “we”?] want to live in” for fear of getting cancelled on social media, and publishers are reluctant to publish anything that they’re not sure will increase the bottom line, for fear of losing their jobs when the next earnings call doesn’t go as spectacularly as Wall Street wants. These are both awful trends, but to what extent are they inherently related to each other, and to what extent is it just—to borrow a piece of corporate killspeak—“synergy”?

Dominick: Agreed, the “only” is key. I have never been keen on any sort of dogmatic insistence on what art can and cannot (or should and should not) do. Faulkner’s comment on the author’s responsibility has its own disturbing elements but nevertheless nails the idea that the only thing the artist “must” do is what the artistic urge requires: “The writer’s only responsibility is to his art. He will be completely ruthless if he is a good one. He has a dream. It anguishes him so much he must get rid of it. He has no peace until then. Everything goes by the board: honor, pride, decency, security, happiness, all, to get the book written. If a writer has to rob his mother, he will not hesitate; the ‘Ode on a Grecian Urn’ is worth any number of old ladies.”

That does not mean, of course, that there is no room for criticism, either. And I am a middle-aged white dude, too, so bear that in mind when evaluating my perspective. Disagreement welcome.

Ian: But to your actual point, and to Virginia’s as well, the corporatization of the publishing industry has drained all the weird out of SF. Nobody is willing to take chances. The only weird we still seem to get is from really long-established authors such as VanderMeer and China Miéville… and now I think I understand why I think this year’s crop of nominees is so underwhelming: they’re so risk-averse, so Not Weird. Not boring, so much, but like Virginia said about Spear, do we really need another take on thousand-year-old stories? Everything is a sequel, a series, a remake.

Final thoughts? Mine is: now I have to go back and get through the bad writing to really try to appreciate Mountain, because it sounds like easily the weirdest of this bunch. Virginia has changed my mind about Spear. It’s good enough, but is it necessary? It’s real unlikely I’m ever going to pick up Legends & Lattes, the one we didn’t discuss here: it really sounds like Not My Cup of Tea.

Virginia: Nice pun. I DNF’ed it. I also want to take a crack at Mountain now, since it sounds like it might be the kind of ambitious swing that I appreciate.

Dominick: My final thoughts, I guess, are that the discussion we’ve had seems to confirm that we are in a bit of a fallow period for SF, or at any rate for SF being recognized as worthy of receiving awards. Maybe there is something of a transition happening in the field, with the emergence of afrofuturism, indigenous futurism, and more diversity generally in SF (and fantasy), but it is not yet really taking centre stage with readers?

Michael: Having read these commentaries, I must say the slide towards fantasy is very apparent this year. While reading Mountain I was not thinking of the nominees broadly. Having viewed each assessment, however, that tendency is clear. I also agree with Virginia in her assessment of the year overall: this definitely feels like an off year for SFF. Nothing seems to be especially deserving of the award.