#ICLR2022 invited talk round-up 2: Beyond interpretability

In the second of our round-ups of the invited talks at the International Conference on Learning Representations (ICLR) we focus on the presentation by Been Kim. Been Kim's research focusses on interpretability and explanability of AI models. In this presentation she talked about work towards developing a language to communicate with AI systems. The ultimate goal is that we would be able to query an algorithm as to why a particular decision was made, and it would be able to provide us with an explanation. To illustrate this point, Been used the example of AlphaGo, and the famous match against world champion Lee Sedol. At move 37 in one of the games, AlphaGo produced what commentators described as a "very strange move" that turned the course of the game.