Algorithmic predictions are increasingly used to inform the allocations of goods and services in the public sphere. In these domains, predictions serve as a means to an end. They provide stakeholders with insights into the likelihood of future events in order to improve decision making quality, and ...
A complex tax code places burdens on taxpayers to navigate a myriad of rules, as well as on bureaucrats to correctly enforce these rules. Often, tax code complexity is the unwanted collateral of many laws enacted over prolonged periods that make sense at the time but lack overall coherence. In this ...
Social scientists frequently perform statistical decompositions of wage gaps, attributing group differences in wages to group differences in worker characteristics. Since the survey datasets used to estimate these decompositions are small, the included characteristics are typically low-dimensional, e.g. summary statistics about job history. These low-dimensional summaries risk ...
AI agents have become an active area of research. But to be useful in the real world and at scale, agents need to be accurate, reliable, and cheap. Learn how to do that in this workshop.
Policy making should be informed by evidence, especially scientific evidence. But exactly how is a surprisingly tricky question. In this talk Narayanan will take a close look at the science-policy interface: how it works and how it should work. The talk will diagnose structural reasons why he believes ...
We are at a transformational junction in computing, in the midst of an explosion in capabilities of foundational AI models that may soon match or exceed typical human abilities for a wide variety of cognitive tasks, a milestone often termed Artificial General Intelligence (AGI). Achieving AGI ...