About the Talk: Much of the value of labor in industrialized economies derives from the scarcity of expertise rather than from the scarcity of labor per se. In economic parlance, expertise denotes a specific body of knowledge or competency required for accomplishing a particular objective. Human expertise commands a market premium to the degree that it is, first, necessary for accomplishing valuable objectives, and second, scarce, meaning not possessed by most people. Will  AI increase the value of expertise by broadening its relevance and applicability? Or will it instead commodify expertise and undermine pay, even if jobs are not lost in net. Autor will present a simple framework for interpreting the relationship between technological change and expertise across three different technological revolutions. He will argue that, due to AI’s malleability and broad applicability, its labor market consequences will depend fundamentally on how firms, governments, NGOs, and universities (among others) invest to develop its capabilities and shape its applications.  

Using the imaging of black holes as a case study, this talk highlights the key requirements for AI to make meaningful contributions to astrophysical research. Dr. Chan introduces several pioneering projects that are integrating AI into astrophysics, covering aspects such as instrumentation, simulations, data processing, and causal inference. He also discusses an innovative project aimed at enabling AI to gain scientific insights independently.

Informative session about OpenAI's Research Residency program, perfect for anyone interested in forging a career in AI, but without extensive experience in the domain. Our 6-month residency helps technical researchers from diverse fields transition into AI. Led by the program manager, Jackie Hehir, this session offers insights into the program's structure, benefits, and application process.The residency is an excellent way for people who are curious, passionate, and skilled to sharpen their focus on AI and machine learning and contribute to OpenAI’s mission of building AGI that benefits all of humanity. Learn more about the residency program and discover research blogs published by residents at the bottom of this page here.

OpenAI and nine national labs bring together leading scientists for first-of-its kind event.

The Data Science for Social Justice Workshop (DSSJ), organized in partnership between UC Berkeley’s Graduate Division and D-Lab, is an 8-week program aiming to provide an introduction to data science for graduate students, grounded in critical approaches of data feminism, data activism, ethics, and critical race theory. Attendees receive training in natural language processing and leverage their skills to conduct discourse analysis on social media data in an interdisciplinary project. This workshop, about to conclude its third year, has trained over 75 graduate students across 20 disciplines. These students form a community of interdisciplinary scholar-activists who uphold a values-driven approach to data science and machine learning. In this event, Claudia von Vacano, Ph.D., Executive Director of D-Lab, introduces the Data Science for Social Justice Workshop, highlighting its goals, structure, and outcomes. Then, three students who have participated in the workshop – with diverse and rich personal and academic backgrounds – present lightning talks on their experience with DSSJ, highlighting their personal journeys, the projects they worked on, and what they gained from the workshop. The event will conclude with a Q&A and discussion on how workshops like DSSJ present novel opportunities to train a generation of interdisciplinary, diverse data-driven scientists who center values and social justice at the forefront of their work.

Hear from research leadership first hand about the significance of expert trainer contributions to the OpenAI mission.

The session featured several nonprofit organizations that utilize AI to drive social impact, emphasizing their long-standing involvement with the community. The discussion was facilitated by Nathan Chappell, a notable figure in AI fundraising, and included insights from a diverse group of panelists: Dupe Ajayi, Jodi Britton, Allison Fine, Anne Murphy, Gayle Roberts, Scott Rosenkrans, and Woodrow Rosenbaum. Each speaker shared their experiences and perspectives on integrating AI into their operations, illustrating AI's transformative potential in various sectors. The event highlighted the importance of AI in amplifying the efficiency and reach of nonprofit initiatives, suggesting a significant role for AI in addressing global challenges. The conversation also touched on the ethical considerations and the need for responsible AI use, ensuring that technological advancements align with human values and contribute positively to society. This gathering not only served as a platform for sharing knowledge and experiences but also fostered networking among community members with similar interests in AI applications. The dialogue underscored the critical role of AI in future developments across fields, advocating for continued exploration and adoption of AI technologies to enhance organizational impact and effectiveness.