The gender gap in computer science research will not close for 100 years
SAN FRANCISCO – Women won't reach parity with men who write published computer science research this century if today's trends hold, according to a study released Friday.
The lasting gender gap is most likely a reflection of low number of women now in computer science, researchers at the Allen Institute for Artificial Intelligence, a research laboratory in Seattle who produced the study, said. It can also partly reflect a male pretense in the community of editors who manage scientific journals and conferences.
Large technology companies are facing increased pressures to solve workplace problems such as sexual harassment and lack of representation of women, as well as minorities among technical staff.
The growing dependence on data algorithms in areas that vary in terms of hiring and artificial intelligence has also raised concerns that the technology industry's dominant white and male workforces build conditions in technology that underpin these systems. [19659005] The Allen Institute study analyzed more than 2.87 million computer science papers published between 1970 and 2018, using first names as a proxy for the gender of each author. The method is not perfect – and it does not consider transgender authors – but it gives a statistical indication of where the field is heading.
In 2018, the number of male writers in the collection of computer science papers was approximately 475,000 compared to 175,000 women.
The researchers tracked the change in the percentage of female writers each year and used this information to statistically predict future changes. There is a wide range of possibilities. The most realistic possibility is gender parity in 2137. But there is a chance parity is never reached, the researchers said.
Other fields of science went better. In biomedicine, for example, gender parity is expected to arrive around 2048, according to the study. About 27 percent of the researchers in computer science are women, compared with 38 percent in biomedicine, according to the study.
While the study focused on research published in academic journals, trends may apply to both the technology industry and academia. Companies like Google, Facebook and Microsoft working with A.I. Publishes much of their most important research in the same journals as academics.
Academia is also where the next generation of technological workers are taught.
"This definitely affects the field as a whole," said Lucy Lu Wang, a researcher with the Allen Institute. "When there is a lack of leadership in computer science departments, it affects the number of female students trained and the number entering the computer science industry."
The study also showed that men grow less likely to cooperate with female researchers – a particularly worrying trend in a field where women have long felt unwelcome and because studies have shown that different layers can produce better research.
Prepared by Mrs Lu and several other researchers at the Allen Institute, the study is in line with similar studies published by academics in Australia and Canada. While gender parity is relatively close in many of life sciences, these studies showed that there is at least a century away in physics and mathematics.
"We hoped for a positive result because we all sensed that the number of female writers grew," said Oren Etzioni, former Washington University professor who oversees the Allen Institute. "But the results were genuinely shocking."
Other Research has shown that women are less likely to enter computer science – and stick to it – if they do not have female role models, mentors and partners.
"There is a problem with retention," said Jamie Lundine, researcher at Institute of Feminist and Gender Research at the University of Ottawa. "Even when women choose computer science, they can end up in school and work environments that are inhospitable." Quantities of data, like thousands of images of faces, researchers in the researchers can easily be introduced into the technology, and reinforce the importance of diversity among those who work with it.
"This is a problem not only in choosing data, but in choosing the projects we want to tackle," Wang said.
The Allen Institute study adds a growing collection of research that points to the challenges women face in tech. A recent study by scientists exploring "natural language understanding" – A.I. The field involving conversation systems and associated technologies – shows that women are less likely to reach leadership positions in the field.
"It's still a glass ceiling," says Natalie Schluter, professor at the IT University of Denmark, who specializes in natural language understanding and the author of the study.
