Data Science

This post outlines how I am thinking about how governance and community work together to support a Berkeley AI strategy, aligned with the University of California’s AI Guiding Principles. I’m making the case for a first layer of foundational governance needed to get the ball rolling— establishing basic contracts, security and data reviews, baseline risk assessments— and then getting the tools into peoples’ hands to learn and experiment. We created the UC Berkeley AI Community to leverage the strength of our diverse population and perspectives, to tap the community to accelerate the development and exchange of ideas and information towards building a more sophisticated institutional understanding of AI. Community engagement speeds the path to effective functional governance; ie, having the right existing decision-making bodies and roles making intentional choices about where and when Berkeley uses and does not use AI.

Artificial intelligence is just beginning to come of age. The latest wave of new AI capabilities has transformed what's possible in meaningful ways, reminiscent of the rise of the internet or the inception of public cloud and mobile computing. These technological advances along with an acceleration of new capabilities will deeply impact core functions of teaching, learning, research and administration at all universities. Advances are occurring across many domains of AI-- and the UC Berkeley AI Community encompasses this wider interpretation-- from machine learning, natural language processing, robotics, including generative AI and also inquiry into AI ethics, explainable AI and knowledge representation.