AI has revealed a gender gap in book characters – with more men than women
- Researchers have found that men outnumber women 4:1 in literary works.
- They used natural language processing, a branch of artificial intelligence, to analyze mentions of gender pronouns.
- The cumulative effect of such unconscious gender biases can contribute to the gender pay gap and fewer women in leadership positions.
“Reader, I married him. So says Jane Eyre, the eponymous heroine of Charlotte Brontë’s classic 1847 romance – a line so famous because of the obstacles she has to jump through to get to this point.
But some 175 years and all progress towards gender equality later, there are four times as many Edward Fairfax Rochesters as Jane Eyres, according to artificial intelligence (AI).
It also offered insight into the adjectives used to describe women – and for now, let’s just say Brontë wouldn’t have approved.
Gender bias in books
Researchers from the Viterbi School of Engineering at the University of Southern California (USC) used a machine learning tool to analyze 3,000 digitized books on Project Gutenberg, including novels, short stories and poetry, ranging from adventure and science fiction to mystery and romance.
Mayank Kejriwal, head of research at USC’s Institute for Information Science (ISI), is an expert in natural language processing (NLP) and has drawn inspiration from work on implicit gender bias.
In collaboration with co-author Akarsh Nagaraj, a machine learning engineer at Meta, Kejriwal used named entity recognition (NER), an NLP method used to extract gender-specific characters.
“One of the ways we define this is by looking at the number of female pronouns in a book versus male pronouns,” Kejriwal explains. They also defined how many female characters are the main characters in the book, to determine if the male characters were central to the story.
The World Economic Forum has been measuring gender gaps since 2006 in the annual Global Gender Gap Report.
The Global Gender Gap Report tracks progress in closing gender gaps at the national level. To turn this information into concrete actions and national progress, we have developed the Closing the Gender Gap Accelerators model for public-private collaboration.
These accelerators were convened in ten countries from three regions. Accelerators are established in Argentina, Chile, Colombia, Costa Rica, Dominican Republic and Panama in partnership with the Inter-American Development Bank in Latin America and the Caribbean, Egypt and Jordan in the Middle East and North Africa, and Kazakhstan in Central Asia.
All National Accelerators, as well as Knowledge Partner countries demonstrating global leadership in closing gender gaps, are part of a larger ecosystem, the Global Learning Network, which facilitates the exchange of ideas and knowledge. experiences via the Forum platform.
In 2019, Egypt became the first country in the Middle East and Africa to launch an accelerator to close the gender gap. While more women than men are now enrolled in university, women make up just over a third of professional and technical workers in Egypt. Women in the labor force are also less likely to be paid the same as their male colleagues for equivalent work or to move into leadership positions.
In these countries, CEOs and Ministers work together over a three-year period on policies that help to further reduce the economic gender gaps in their countries. This includes extended parental leave, subsidized childcare, and removing unconscious bias in recruitment, retention, and promotion practices.
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Pay attention to the gender gap of the characters
While other research has shown that women read more than men, mentions of men outnumbered women 4:1 in the USC study. Tellingly, this “gender gap” narrowed when the books were written by women.
“It made it clear to us that at that time, women would represent themselves much more than a male writer,” Nagaraj says.
NLP technology has also allowed researchers to find associations of adjectives with gender-specific characters, which they believe has deepened their understanding of prejudice and its pervasiveness in society.
“Even with misattributions, the words associated with women were adjectives like ‘weak’, ‘lovable’, ‘pretty’ and sometimes ‘stupid’,” Nagaraj explains. “For the male characters, words describing them included ‘leadership’, ‘power’, ‘strength’ and ‘politics’.”
Kejriwal hopes the study will underscore the importance of interdisciplinary research and, specifically, the use of AI technology to shed light on social issues and inequalities.
Why Fair Representation in Literature Matters
As Jessica Nordell told the World Economic Forum in an interview for her book The End of Bias: “We live in a culture and absorb information from that culture about relevant categories, salient categories, and the meaning of those categories. And we absorb a lot of associations and stereotypes and types of cultural knowledge about these categories. »
“Gender bias is very real, and when you see four times fewer women in literature, it has a subliminal impact on the people who consume the culture,” says Kejriwal. “We have quantitatively revealed an indirect way in which prejudice persists in culture.”
Over time, the cumulative effect of unconscious gender bias can add up, Nordell says — contributing to the gender pay gap and fewer women in leadership positions.
It will take 135.6 years to close the gender gap globally, according to the Forum’s 2021 Global Gender Equality Report, which does not fully reflect the impact of the COVID-19 pandemic.
It found “a persistent lack of women in leadership positions,” with women accounting for just 27% of all leadership positions.
Seeing women equally represented in literature might just be one way to reduce unconscious bias and help close the gender gap.
“Our study shows us that the real world is complex, but there are benefits for all the different groups in our society who participate in cultural discourse,” Kejriwal notes. “When we do that, we tend to have a more realistic view of society.”