Who makes AI? Better popular films for a better gendered world
The results were striking: we found that only nine out of 116 (8%) AI professionals in influential films were female – that’s less than half the real world statistic (22%). In fact, AI creators are more likely to be depicted as male robots than human women. So, while women are already under-represented in AI in real life, Hollywood is making the problem worse.
On-screen portrayals matter as they shape our view of who makes a good AI scientist. Women in Tech UK found that 18% of women cite ‘perceptions’ as the most important reason why they did not want to work in the technology sector.
But positive perceptions also have the power to instigate the inverse effect. A study by the Geena Davis Institute on Gender in Media found that “nearly two-thirds (63%) of women that work in STEM say [X-Files scientist protagonist] Dana Scully served as their role model”, proving that positive portrayals of women scientists also instigate real world change.
Unfortunately, Scully is in the minority. This matters because sexist portrayals not only put women off working in the tech sector, but also foster misogynistic attitudes towards women and their work if they do try to enter.
The exclusion of women from tech has harmful effects for all women. Studies show that the marginalisation of women in the field (and a lack of diverse teams more generally) is more likely to result in AI products that do not work for women or actively discriminate against them.
Tropes of masculinity in AI films
While the numbers of male and female AI scientists in films themselves are stark and telling, films about AI scientists also contain several recurring plot elements (‘tropes’) that contribute to perceptions of the field of AI as masculine:
• Every Frankenstein’s an Einstein: Many films stereotype AI scientists as anti-social geniuses creating artificial life in their private basement laboratories. Out of the 116 AI scientists, 38 (33%) were depicted as geniuses, and 14 (12%) of the AI engineers, scientists or researchers were explicitly represented as child prodigies. However, the idea of ‘genius’ is deeply shaped by gendered and racialised concepts of intelligence that have historically been claimed by a white male elite.
• Womb man: In the early days of AI, when Freudianism was still current, it was considered almost a cliche that (at least some of) the researchers involved were motivated by ‘womb envy’ – the desire to create new life in their image.
Of the films in our corpus, 22% (19) featured Frankenstein-esque figures who aim to create new life in their image. This suggests that the association between AI and masculinity might be further exacerbated by this association between men and the capacity to create new (AI) life.
• Guns and bots: Our study also revealed other ways that AI is masculinised on-screen. One of these is the significant connection between AI and the military – 10 of the films feature AI made in military contexts. Given that the military is also a predominantly masculine space, we also need to be attentive to associations between AI, masculinity, warfare and violence.
• Sweet C-Suite dreams: Another masculinised trope across our corpus was the ‘corporate creator’. In 32 films (37%), AI was made by a corporation. All but one of the on-screen CEOs were male.
Again, this appears to be a worse reflection of women’s exclusion from the real world C-Suite (only 5.4% of Fortune 500 companies had female CEOs in 2017). Studies suggest that this is in part because stereotypes of corporate leaders overlap with stereotypical male attributes, such as ambition and dominance.
Women AI scientists: Submissive, but not subversive
Unfortunately, in the few cases that women do appear on-screen as AI scientists, their status and plot lines leave much to be desired. In three films in our corpus, the female AI scientist is the lower ranked employee of a man.
Worse, death is often on the horizon for women AI scientists in popular films. Three out of the nine female scientists either sacrifice themselves or are sacrificed as part of the film’s plot – The Machine, Ghost in the Shell and The Emoji Movie.
Another reason for the prominence of these tropes in AI films is likely to be the lack of women directing these films. Of 161 directors, we found that only two presented as women at the time of the film’s release – and they were co-directing with men (or a person presenting as a man at that time). This means that only 1% of popular AI movies are directed by women, and none solely by a woman.
Better films, better worlds
We therefore call for greater research into understanding and mapping the problem of gendered representations of AI scientists, and also better portrayals of female AI characters. Only then can we shift the landscape of who does and does not ‘count’ as an AI scientist in the cultural construction of the AI engineer.
In telling better and different stories, we also need to support more diverse writers, filmmakers and directors. There are plenty of inventive depictions of women as AI scientists out there, but more of them need to be made into films (like Aliette de Bodard’s stories), and more women need to be in charge of telling those stories.
Stephen Cave is director of the Leverhulme Centre for the Future of Intelligence at the University of Cambridge in the United Kingdom; Kanta Dihal is a senior research fellow at the Leverhulme Centre for the Future of Intelligence; Eleanor Drage is a researcher at the Leverhulme Centre for the Future of Intelligence; and Dr Kerry McInerney is a research associate at the Leverhulme Centre for the Future of Intelligence. The Who Makes AI? report is available here. To learn more see this article.