- Computational Social Science
- Critical Data Studies
- Data Science
- Economics and Information
- Education Technology
- Ethics, Law and Policy
- Human-Computer Interaction
- Human-Robot Interaction
- Incentives and Computation
- Infrastructure Studies
- Interface Design and Ubiquitous Computing
- Natural Language Processing
- Network Science
- Social Computing and Computer-supported Cooperative Work
- Technology and Equity
Please join Information Science Department and The Legal Information Institute (LII) for colloquium guest, Jacob Rosen (MIT, MITRE). He explores ways to help tax law policy-makers thwart potential evaders with predictive computational models, the topic of his internationally acclaimed research paper, Tax Non-Compliance Detection Using Co-Evolution of Tax Evasion Risk and Audit Likelihood.
Theme: Articifical Intelligence and Predicting Tax Evasion
Abstract: As the U.S. tax code becomes increasingly complex, particularly in the realm of partnership taxation, various laws are often implemented without considering their effects on the overall tax system. Such laws not only create confusion among well-meaning taxpayers, but can be exploited by highly paid tax professionals in order to create perverse results not anticipated by policy-makers.
This event is open to all students, faculty and staff. Please RSVP at events.cornell.edu. Complimentary refreshments will be available after the presentation.
Can't make it in person? Stream the event live at: law.cornell.edu/lii/events/rosen.