Abstract: Picture this - you are at the movies waiting in line to buy popcorn. On the big, bright screen behind the counter you see multiple options. You take your time and carefully crunch all the numbers in front of you and order what you think is the optimal choice. You walk away with a big smile on your face because you just got a very good deal. However, chances are you just got tricked into buying something you didn’t even want to begin with. This is a classic example of sub-optimal human decision making that has been studied in behavioral economics. However, the penetration of these ideas into Artificial Intelligence has been fairly limited. Given that in today's world humans and machines work closely together, it’s important to design systems that can account for the fact that our decisions are heavily influenced by multiple cognitive biases. This talk is intended to be an introduction to the design of such systems. We will look at multiple biases and how they have been used in the real world. We will also look at work in Artificial Intelligence that tries to account for these biases and propose future directions for this area.

 

Short Bio: Aditya Gulati is an ELLIS PhD student. He holds a Bachelor’s and Master’s degree in Computer Science Engineering from the International Institute of Information Technology Bangalore. His research interests lie in modelling human behavior and artificial intelligence. His supervisors are Nuria Oliver (ELLIS Alicante), Miguel Angel Lozano (University of Alicante) and Bruno Lepri (Fondazione Bruno Kessler).