# Delegate Pricing Decisions to an Algorithm? Experimental Evidence

arXiv: https://arxiv.org/abs/2510.27636 · HTML: https://mlsanity.com/paper/2510.27636/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Oct 2025.

## Built on by (most cited first, 1 of 1)

- [Individualized Algorithmic Advice as a Strategic Signal on Competitive Markets](https://mlsanity.com/paper/2511.09454/) (2025)

## Abstract (arXiv)

We analyze the delegation of pricing by participants, representing firms, to a collusive, self-learning algorithm in a repeated Bertrand experiment. In the baseline treatment, participants set prices themselves. In the other treatments, participants can either delegate pricing to the algorithm at the beginning of each supergame or receive algorithmic recommendations that they can override. Participants delegate more when they can override the algorithm's decisions. In both algorithmic treatments, prices are lower than in the baseline. Our results indicate that while self-learning pricing algorithms can be collusive, they can foster competition rather than collusion with humans-in-the-loop.