More Than A Magazine, A Movement
Many people see language models, like ChatGPT and other new machine learning technologies like Meta’s Make-A-Video, as the beginning of the end. And as a woman in tech—a field dominated by men—Gabriela de Queiroz has reason to be skeptical of AI.
But when de Queiroz talks about her efforts to make artificial intelligence more inclusive, she takes a different approach to understanding the ever more influential and pervasive role of AI in contemporary societies.
As long as the field of data science remains predominantly male and white, it will be difficult to have inclusive advancements in artificial intelligence. When data scientists do not bring diverse perspectives to their work, the science and technology they produce suffers.
While the total number of women receiving college degrees increases, what hinders the expansion of diversity in the data science field? To address this persistent gap, women working in the fields that feed into data science have been working to change the circumstances that hinders women from pursuing work in the field, as well urging society to consider the harmful consequences of a field which has historically excluded the voices of women.
Dr. Cecilia Aragon is a major contributor to these ongoing discussions. She is an award-winning author, airshow pilot and professor—the first Latina to earn the rank of full professor in the College of Engineering at the University of Washington in its 100-year history. Her interdisciplinary methods, active inclusion of diverse students with diverse academic backgrounds, and perceptive research questions, all challenge the traditional expectations of data scientists and question the false assumptions of data science.
For Tina Hernandez-Boussard, solving the inequities within our healthcare system is only possible when we ensure that the people who collect, analyze and interpret data to make decisions, are as diverse as those who will be affected by those decisions.
The Women in Data Science Conference (WiDS) was born of a problem: How can we remove the barriers to success that traditionally bar women from accessing the increasingly critical field of data science? To Margot Gerritsen, professor at Stanford University and co-founder and co-director of WiDS Worldwide, ensuring women can see other women in the field will help them destroy the myth that data science is a field exclusively for men
The WiDS conference will be held on March 7, 2022—the day before International Women’s Day. Tune into WiDS Worldwide Livestream throughout the day to watch keynotes, tech talks, panel discussions and meet-the-speaker interviews.
Clinical scientists often juggle research responsibilities, teaching and mentoring students, and caring for patients, along with their family, home and childcare responsibilities outside of work. The demands made of them only grew during the pandemic, especially for women scientists and scientists of color.
The COVID-19 Fund to Retain Clinical Scientists (or FRCS) grant is made up of $12.1 million awarded to 22 medical schools across the United States, designed to support caregivers in the workplace.
Like tech industries in general, the field of data science has a problem: Research suggests only 15 percent of data scientists are women, and fewer than 3 percent are women of color.
If data is going to serve a diverse range of citizens and consumers rather than a small subset, it’s imperative that the rules of the game change.
The WiDS Worldwide Conference encourages women in data science to establish their own national and regional networks while participating in a broader global conversation.
Of more than 900 Nobel Prize laureates, 866 have been men, while only 56 have been women. Only 16 Nobel prize winners have been Black.
Last month, Ms. had the opportunity to speak with one of these women: Dr. Andrea Ghez, who won the 2020 Nobel Prize for Physics. As only the fourth woman (all of them white) to win the award for physics, Ghez understands the Nobel also confers on recipients the responsibility of serving as an international role model for girls contemplating careers in science and for women scientists.
Despite educators’ tendency to discourage students from using Wikipedia, Wikipedia is so much more than a source or a final destination. It’s a portal into other sources. Adding to and enhancing that portal to include knowledge and perspectives hitherto suppressed or marginalized is an important political project.
Join the Women in Science Wikipedia edit-a-thon on Monday, Aug. 31, from 12p.m.-2p.m. ET—part of an effort to increase the representation of women on Wikipedia and to close the editor and content based gender gaps on the site.
