New WiDS Research Addresses Barriers Women Face Pursuing Graduate Studies in Data Science and AI

Women are significantly underrepresented in the booming fields of Data Science and AI in the United States, as well as in the graduate school programs that prepare students for careers in this field. Women in Data Science (WiDS), with support from Pivotal Ventures, conducted an in-depth research study to understand the barriers women face and identify potential approaches to increase the participation of women in this vital field.

Increasing the representation of women in DS/AI is critical because of the opportunities for impact on society and wealth creation that should be accessible to all, as well as the need for a diversity of perspectives to reduce bias and increase equity in products and solutions.
 
Through our research into the gender gap in data science and AI professions, we learned about the importance of a graduate degree as a pathway to these professions, and the significant and interrelated barriers that women can face to pursue and complete these graduate degrees.
 
The WiDS white paper, Identifying and Removing Barriers for Women to Pursue Graduate Studies in Data Science and AI, examines current trends in education and the workplace, common barriers, and existing programs and interventions designed to lower those barriers. We then synthesized these insights into recommendations for potential approaches to increase participation of women in DS/AI graduate studies.
 
Here are some of the key findings from our research:

• Currently, more than 80% of US-based data scientists hold graduate degrees. This seems to imply that successfully completing a DS/AI-focused graduate degree program is helpful for a career in these fields.
• U.S. women represent approximately 7% of master’s students in Computer Science graduate programs, which currently provide a substantial talent pool for DS/AI. Overall, between 55-65% of the women earning DS/AI-related advanced degrees are international students. 
• The barriers women face in the pursuit and completion of DS/AI-related advanced degrees are significant, wide-ranging, and interrelated. They include: low awareness of data science pathways, value of graduate degree, and societal impact
• Challenges related to self-efficacy, self-identity, and imposter phenomenon
  • Lack of (effective) faculty mentorship to pursue and thrive in graduate study
  • Insufficient skills development to prepare for graduate program admissions
  • Lack of family, peer, and community support
  • Perpetuation of gender bias and significant gender gaps in academia and the workplace
• The interdisciplinary nature of DS/AI provides a great opportunity to reach women across a wide range of undergraduate programs to broaden the DS/AI talent pool.
• The potential student pipeline from a broader range of undergraduate degrees is six times larger than the pipeline from engineering, computing, applied math, and statistics.  

 
Our experience at WiDS indicates a theory of change where 30% representation of women is the threshold for creat­ing a sense of belonging, full participation, and acceptance. WiDS aims to help increase the representation of women in DS/AI-related graduate programs to at least 30% by 2030 (30x30).

Proposed WiDS Academy: Building awareness, consideration, and preparedness
Inspired by our research and the existing programs and interventions, we propose a suite of potential programmatic approaches called WiDS Academy that we believe can reduce barriers and increase women’s participation to a critical threshold of 30%.

The WiDS Academy concept is designed to achieve high impact in a relatively short time by increasing the percentage of women successfully completing the graduate programs that are pipelines to the DS/AI workforce. The concept is a cross-university program in which partner colleges and universities would deliver program elements to their students with central support from WiDS. It would provide programming that intervenes early, reaches a broad population, and addresses barriers throughout a student’s undergraduate years.

We propose eight WiDS Academy elements that together provide programming to build Awareness, promote Consideration, and increase Preparedness for DS/AI-relevant graduate study. The program elements provide a progression of experiences that match the increasing level of interest, engagement, and challenge as students progress through their undergraduate years, with all program elements designed to attract and be accessible to students from a variety of undergraduate disciplines.

Through this research, WiDS wants to provide insights and a vision for potential paths forward. WiDS welcomes collaborators and partners to further develop and deploy programs and address outstanding research questions to remove barriers that women face to joining, thriving in, and leading in the DS/AI fields. We hope you will join our efforts. Please reach out to us via email to widsacademy@stanford.edu. The opportunity is too great, and the stakes too high to not take action.

To learn more, you can download the full report here.