[FLAIR seminar] The Relative Value of Prediction
Event details
| Date | 10.10.2024 |
| Hour | 13:15 › 14:15 |
| Speaker | Juan Perdomo (Harvard) |
| Location | |
| Category | Conferences - Seminars |
| Event Language | English |
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 enhance social welfare. However if maximizing welfare is the question to what extent is improving prediction the best answer?
In this talk I will discuss various attempts to contextualize the relative value of algorithmic prediction in allocation problems through both theory and practice. The goal of the first part will be to formally understand how the welfare benefits of improving prediction compare to those of expanding access when distributing social goods. In the latter half I will present an empirical case study illustrating how these issues play out in the context of a risk prediction system used throughout Wisconsin public schools.
Practical information
- Informed public
- Free
Organizer
- Lénaïc Chizat (FLAIR)