Two Robots Passing in the Night …

Rebecca Gu

In a future of widespread algorithmic pricing, inadvertent cooperation between algorithms is easier than ever, resulting in coordinated price rises. While governments have clear cut laws to assess and deter traditional collusion, automated pricing poses interesting questions as to what will or will not be allowed.

We build and demonstrate how a Q-learner algorithm, even under extremely innocent conditions, can reach a collusive outcome in a virtual marketplace. We also discuss which industries are in the most danger of finding themselves subject to greater restrictions or scrutiny, where “safe harbours” might exist, and what future digital regulation might look like.

Objective of the talk

The audience will understand:

  • How have pricing algorithms changed the digital marketplace
  • Why governments are currently worried about these changes
  • The ethics and legal challenges of regulating algorithms
  • What makes an algorithm more concerning, less concerning.

Required audience experience

Reinforcement learning

Track 2
Location: Date: October 1, 2019 Time: 2:30 pm - 3:15 pm Rebecca Gu Rebecca Gu, Baringa Partners Cris Lowery, Baringa Partners Cris Lowery, Baringa Partners