Petra Stock
When artificial intelligence (AI) scientists are depicted in film, the characters are more likely to be male robots or aliens, than human women.
Analysis of 142 of the most influential films featuring AI, across 100 years of cinema, found women are underrepresented in fictional roles, just as they are in real life.
Researchers from the University of Cambridge analysed the 116 AI researcher or engineer characters depicted. They found 88 were male characters, 10 were male robots or aliens, 7 were female characters and 2 were female non-humans.
The research, published in Public Understanding of Science found overall, only 8% of AI scientists in film were women.
“Our cinematic stock-take shows that women are grossly underrepresented as AI scientists on screen. We need to be careful that these cultural stereotypes do not become a self-fulfilling prophecy as we enter the age of artificial intelligence,” says co-author Dr Kanta Dihal from the University of Cambridge.
On the few occasions when female AI scientists were depicted, around half were presented as inferior or subservient to a man.
The first film to feature a female AI researcher is the character of Frau Farbissina in Austin Powers: International Man of Mystery.
Other women AI scientists included: Shuri in Avengers: Infinity War (2018), Evelyn Caster in Transcendence (2014), Ava in The Machine (2013), Dr Brenda Bradford in Inspector Gadget (1999), Dr Susan Calvin in I, Robot (2004), and Dr Dahlin in Ghost in the Shell (2017).
Non-human female AI scientists included Alien Quinterra in Transformers: The Last Knight and the female emoji ‘Smiler’ in The Emoji Movie.
The research shows the proportion of AI scientists and engineers portrayed as men in mainstream films (92%) is even higher than the percentage of men in the AI workforce (78%).
While there are many contributing factors to the low representation of women in STEM fields, a range of research suggests cultural representations of scientists and engineers can play a role in perpetuating or disrupting gender stereotypes.
Greater workforce diversity is considered essential to address the bias and stereotypes that pervade AI technologies.
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“This is not just about inequality in one industry. The marginalisation of women could contribute to AI products that actively discriminate against women – as we have seen with past technologies. Given that science fiction shapes reality, this imbalance has the potential to be dangerous as well as unfair,” says co-author Dr Eleanor Drage.
A 2018 report Portray Her, looked at gendered representations of women in STEM fields across film, TV, and streaming media for all ages between 2007 and 2017. The report found while 37% of STEM characters were women, women made up only 8.6% of fictional computer scientists and an astonishing 2.4% of engineers.