CITP Lecture: Aligning Machine Learning, Law, and Policy for Responsible Real-World Deployments
Attendance restricted to Princeton University faculty, staff and students.
Attendance restricted to Princeton University faculty, staff and students.
Foundation models (ChatGPT, StableDiffusion) are transforming society: remarkable capabilities, serious risks, rampant deployment, unprecedented adoption, overflowing funding, and unending controversy. In this talk, we will center our attention on their societal impact.
The emergence of large language models (LLMs) represents a major advance in artificial intelligence (AI) research. However, the widespread use of LLMs is also coupled with significant ethical and social challenges.
The proliferation of social media has given rise to widespread study and speculation about the impact of digital technologies on politics, activism, and social change. Key among these debates is the role of social media in shaping the contemporary public sphere, and by proxy, our democracy.
Algorithms make predictions about people constantly. The spread of such prediction systems has raised concerns that machine learning algorithms may exhibit problematic behavior, especially against individuals from marginalized groups.
In the United States, financial institutions leverage personal data for countless decisions impacting individual wellbeing, ranging from managing access to existing accounts to deciding who to offer credit and on what terms.
Please register here to attend in person.
In collaboration with the Department of Computer Science and the Department of Electrical and Computer Engineering
Does conversation online often lead to deeper understanding of important issues? In this talk, research will be presented in the School of Interactive Computing at Georgia Tech about understanding and supporting online discussion of difficult issues.