Black Lives Matter.

AI2 will not stand for the unequal treatment of people of color in our institute, in our communities, or in our country. We will advocate for our Black colleagues, friends, and fellow citizens, and support efforts that build a society where we can all pursue happiness without oppression. This is fundamental to our mission of working for the common good.

AI2 is matching our individual team members’ contributions to organizations backing social justice and the Black Lives Matter movement, and we are supportive of our team members’ peaceful participation in activities related to the ongoing demonstrations related to this movement. We are taking time to discuss internally the additional concrete actions we will take to proactively support the Black community going forward.

Diversity, Equity, & Inclusion

Oren Etzioni, CEO

A statement from our CEO:

“AI2’s mission to contribute to humanity through high-impact AI research and engineering can only be achieved through the inclusion of diverse perspectives. We strive to make diversity, equity, and inclusion a cornerstone of our work and culture, and we're proud of our progress to date. As with any complex initiative, we still have work to do—we're committed to listening, learning, and refining our efforts to enrich our work and our team.”

Oren Etzioni, CEO

Our commitment to diversity

At AI2, we are committed to fostering a diverse, inclusive environment within our institute, and to encourage these values in the wider research community. A diverse group of employees brings a variety of perspectives that encourage novel ideas and new approaches oriented at the data and challenges present in AI research.

team members winning an award
team members gathered outside

Supporting a diverse team

AI2 has a Diversity, Equity, and Inclusion Council that is open to any team member from across the organization. We meet regularly and make active progress across several initiatives to support DEI both internally and externally.

For our team at AI2, we offer:

  • A fair and employee-empowering review process
  • Generous tuition and professional membership reimbursements
  • Strong support for employees who need assistance attaining visa sponsorship
  • Financial support for childcare requirements during business travel
  • Paid parental and maternity leave for birth, adoption, or fostering

AI2 also supports DEI-related initiatives in the wider community

students at Grace Hopper
We sponsor the annual Grace Hopper Celebration
ADA logo
We partner with (and hire from) the Ada Developer Academy
scholarship winners
We offer the annual Allen AI Outstanding Engineer Scholarship for Women and Underrepresented Minorities

Shining a light on DEI challenges through research

AI2’s nonprofit status and unique mission of AI for the Common Good allow us to provide our team members the autonomy and support to pursue projects related to diversity and inclusion.

gender of authors in CS

Gender Trends in Computer Science

AI2’s recent study Gender Trends in Computer Science Authorship by Lucy Lu Wang, Gabriel Stanovsky, Luca Weihs, and Oren Etzioni highlighted an important diversity gap in the computer science field. If current trends continue, the gender divide among authors publishing computer science research will not close for more than a century. Fair representation of women and other minorities is crucial to the future of the field, and we want to catalyze the conversation and inspire action by making findings like these known and by providing this important data to others interested in helping to foster equity in the field.

Adversarial Removal of Gender

Mark Yatskar, a Young Investigator at AI2, has published multiple works concerning gender bias and amplification in machine learning datasets, including Adversarial Removal of Gender from Deep Image Representations by Tianlu Wang, Jieyu Zhao, Mark Yatskar, Kai-Wei Chang, and Vicente Ordonez.

Screenshots of Adversarial Removal of Gender
chart of studies by sex-bias

Quantifying Sex Bias

The Semantic Scholar team actively explores meaningful meta analyses of scientific literature, recently quantifying the problematic sex bias present in clinical studies in their study Quantifying Sex Bias in Clinical Studies at Scale With Automated Data Extraction by Sergey Feldman, Waleed Ammar, Kyle Lo, Elly Trepman, Madeleine van Zuylen, and Oren Etzioni.

Fairness

AI2’s AI & Fairness and Green AI initiatives are specifically focused on utilizing our AI expertise to make positive, tangible impacts on societal and environmental issues.

Learn More
team members working together