By Stephen Cave, Kanta Dihal, Eleanor Drage and Kerry McInerney
Women are even
less likely to appear as AI scientists in film than in real life – and when
they do, they’re low-status and likely to get
What do the films Metropolis (1927), AI: Artificial Intelligence (2001) and Ex Machina (2014) have in common? They feature male AI scientists in Frankenstein-esque roles, intent on masterminding the creation of new life. In our paper ‘Who Makes AI?’, we analyze 100 years’ worth of popular AI films to see who makes AI on screen. The results are striking: only 9 out of 116 (8%) AI professionals in influential films are female. This is even lower than the 22% of female AI professionals in real life. This dearth of women AI scientists on screen, coupled with the way male AI scientists are represented as anti-social geniuses with God complexes, is likely to be discouraging women from entering the profession.
AI is one of the most impactful and lucrative technologies of our age. As its global market size - already valued at $93.5 billion in 2021 - increases further, AI scientists will increasingly be among the most valued scientists in the global economy. And yet, women in the AI field are also often confined to lower-paid, lower-status roles such as software quality assurance, rather than prestigious sub-fields such as machine learning.
This is also how women are portrayed in AI films: as subservient, disposable, and lower-status. Of the 9 female AI engineers we found in a century of cinema, 3 are the subordinate employees of a man (I, Robot, The Machine, and Austin Powers); and a further 2, in Transcendence and Inspector Gadget, are respectively the wife and daughter of a male genius AI creator. Only 4 of them are not of lower status than a man. Furthermore, 4 out of the 9 either sacrifice themselves or are sacrificed as part of the film’s plot (Transcendence, The Machine, Ghost in the Shell, and The Emoji Movie).
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| Image by Kerry McInerney |
Therefore, we are not simply calling for more AI scientists on-screen, but for an end to on-screen misogyny. Women must be depicted as leaders in AI. This is crucial, because research shows that gendered stereotypes about who is likely to succeed in computer science and related fields affect women and girls’ willingness to enter the field of AI. PwC found that the lack of female role models affects female students’ uptake of STEM subjects, while Women in Tech UK found that 18% of the 1000 women surveyed cited “perceptions” as the most important reason why women are put off working in the technology sector.
Popular film plays a central role in creating and enforcing these perceptions. In a leading research study on portrayals of STEM characters on screen, Professor Jocelyn Steinke found that images of STEM professionals in popular media have both created and perpetuated the stereotype that women are less present, talented and successful than men in STEM fields. But the effect can also be reversed by positive portrayals: as the Geena Davis Institute on Gender in Media discovered, the ‘Scully Effect’ is more than merely anecdotal: nearly 2/3 (63%) of women that work in STEM say The X Files scientist Dana Scully was a reason they went into science.
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| Image by Kerry McInerney |
The exclusion of women from the field of AI is not only unfair to the excluded, but can have far-reaching negative consequences. Studies show that the marginalization of women in the field may be resulting in products that do not work for women or actively discriminate against them. It is therefore crucial that more women enter the AI industry.
Who decides these on-screen depictions of AI scientists? Part of the answer can be found in the information we collected on directors' gender (where 'gender' referred to the directors' self-presentation at the time of the film's release). Only 1% of directors in our corpus are women (2 films out of 142) and in both instances the women were co-directing with men. Not a single influential AI film has been directed solely by someone presenting as a woman.
This may also be a reason why films perpetuate the association between well-worn tropes such as ‘the genius’ and male AI creators. Out of the 116 AI scientists, we coded 38 (33%) as geniuses and 14 (12%) as child prodigies. Only 1 was female. This is unsurprising, given that the idea of ‘genius’ has historically been claimed by a white male elite. Numerous studies demonstrate that people across different age groups continue to associate brilliance and exceptional intellectual ability with men, a phenomenon called the ‘brilliance bias’. The coding of AI scientists as geniuses therefore risks entrenching the belief that women are less ‘naturally’ suited for a career in the field of AI.
Another masculinised trope across our corpus was the ‘corporate creator’. In 32 films (37%), AI was the product of a corporation. All but 1 of the on-screen CEOs were male. Again, this reflects and exacerbates women’s exclusion from the real-world C-Suite (only 5.4% of Fortune 500 companies had female CEOs in 2017).
A similar set of masculinised associations arises from the trope of AI as a military product. Our corpus contained 10 films in which the AI was produced by military organizations. Needless to say, the military is strongly associated with stereotypical male attributes, therefore further amplifying the perceived masculinity of the field of AI.
We are calling for greater research into understanding and mapping the problem of gendered representations of AI scientists, and also further investigation into solutions to this problem. 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.
For more, see the original article: Who makes AI? Gender and portrayals of AI scientists in popular film, 1920–2020
If you are interested in knowing more, or our paper has impacted your work, or you’re making a film or TV show about AI, please get in touch at: ed575@cam.ac.uk
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Stephen Cave is Director of the Leverhulme Centre
for the Future of Intelligence at the University of Cambridge. His research
currently focuses on the ethics of AI and life extension technologies.
Kanta Dihal is Lecturer in Science Communication at Imperial
College London. Her research focuses on the role narratives play across
cultures in making sense of disruptive new developments in science and
technology.
Eleanor Drage is a Research Fellow at the
Leverhulme Centre for the Future of Intelligence. Her research investigates how
AI relates to structural inequality, including systems of race and gender.
Kerry McInerney is currently a Research Fellow at the Leverhulme Centre for the Future of Intelligence. She researches AI from the perspective of gender studies, critical race theory, and Asian diaspora studies.