Model AI Assignments 2020

  • Todd W. Neller Gettysburg College
  • Stephen Keeley Princeton University
  • Michael Guerzhoy Princeton University, University of Toronto, Li Ka Shing Knowledge Institute
  • Wolfgang Hoenig California Institute of Technology
  • Jiaoyang Li University of Southern California
  • Sven Koenig University of Southern California
  • Ameet Soni Swarthmore College
  • Krista Thomason Swarthmore College
  • Lisa Zhang University of Toronto
  • Bibin Sebastian University of Toronto
  • Cinjon Resnick New York University
  • Avital Oliver Google
  • Surya Bhupatiraju Massachusetts Institute of Technology
  • Kumar Krishna Agrawal Indian Institute of Technology, Kharagpur
  • James Allingham University of Cambridge
  • Sejong Yoon The College of New Jersey
  • Jonathan Chen Washington University in St. Louis
  • Tom Larsen Washington University in St. Louis
  • Marion Neumann Washington University in St. Louis
  • Narges Norouzi University of California, Santa Cruz
  • Ryan Hausen University of California, Santa Cruz
  • Matthew Evett University of California, Santa Cruz

Abstract

The Model AI Assignments session seeks to gather and disseminate the best assignment designs of the Artificial Intelligence (AI) Education community. Recognizing that assignments form the core of student learning experience, we here present abstracts of nine AI assignments from the 2020 session that are easily adoptable, playfully engaging, and flexible for a variety of instructor needs. Assignment specifications and supporting resources may be found at http://modelai.gettysburg.edu.

Published
2020-04-03
Section
EAAI Symposium: Model AI Assignments