The profit motive encourages companies to punch the gas on emerging tech instead of braking for reflection and study, says Fei-Fei Li, who was the director of Stanford's AI Lab from 2013 to 2018 and now codirects HAI. "Industry is working fast and hard on this, but we cannot let them be the only people who are working on this model, for multiple reasons," Li says. "A lot of innovation that could come out of these models still, I firmly believe will come out of the research environment where revenue is not the goal." Part of the reason for all the concern is that foundation models end up touching the experience of so many people. In 2019, researchers at Google built the transformational BERT (Bidirectional Encoder Representations from Transformers) natural language model, which now plays a role in nearly all of Google's search functions.

The U.S. Intelligence Community faces a moment of reckoning and AI lies at the heart of it. Since 9/11, America's intelligence agencies have become hardwired to fight terrorism. Today's threat landscape, however, is changing dramatically, with a resurgence of great power competition and the rise of cyber threats enabling states and non-state actors to spy, steal, disrupt, destroy, and deceive across vast distances -- all without firing a shot. The Intelligence Community (IC) faces a moment of reckoning. If the IC cannot adopt AI and other emerging technologies successfully, it risks failure.

Rapidly developing technologies can be an unprecedented force for good, but too often codify and amplify existing forms of racial inequality, discrimination, and bias. This free, online conference brings together researchers, policymakers, technologists, and advocates to address technology's new threats to racial equity and new tools for a more just future. The conference is sponsored by the Stanford Center for Comparative Studies in Race & Ethnicity (CCSRE), Digital Civil Society Lab (DCSL) at the Stanford Center on Philanthropy and Civil Society, the Stanford Institute for Human-Centered Artificial Intelligence (HAI), and the Stanford Program in African & African American Studies, with support from the Public Interest Technology University Network. If you are experiencing any technical difficulties, please contact Rebecca Lapeña.

Dr. Fei-Fei Li is the inaugural Sequoia Professor in the Computer Science Department at Stanford University, and Co-Director of Stanford's Human-Centered AI Institute. She served as the Director of Stanford's AI Lab from 2013 to 2018.

Dr. Sarah H. Bana is a postdoctoral fellow at the Stanford Digital Economy Lab. Her research is primarily focused on measurement of new tasks and new technologies, and their effect on the labor market.Dr. Bana's research uses novel methods to measure skills, tasks, and technologies, with an emphasis on uncovering fine distinctions using big datasets. Her most recent work uses state-of-the-art natural language processing techniques to better characterize how jobs have changed over time.She has been published by the Journal of Policy Analysis and Management and the Sloan Management Review, and spoken at events such as California State Assembly's Rising Tide Summit on Economic Security. In 2019, she was awarded Honorable Mention for her dissertation, "Three Essays on Vulnerable Workers," by the Upjohn Institute.Prior to joining HAI, she received her Ph.D. in Economics from the University of California, Santa Barbara, and was a Postdoctoral Associate at MIT's Initiative on the Digital Economy.