AI Pricing Algorithms Drive Up Prices Without Explicit Collusion, New Study Reveals
Summary
New research reveals that AI pricing algorithms automatically drive up consumer prices through learned retaliation against competitors without any explicit collusion, creating a regulatory nightmare as traditional anti-trust laws cannot address this algorithmic price-fixing that requires no communication between companies.
Key Points
- Researchers discover that simple pricing algorithms can drive up prices even without explicit collusion, as algorithms learn to retaliate against competitors who cut prices through trial and error
- A new study proves that seemingly benign 'no-swap-regret' algorithms can still yield high prices when competing against basic nonresponsive strategies that randomly set prices
- Regulators face challenges addressing algorithmic price-fixing since traditional anti-collusion laws target explicit agreements, but algorithms can achieve the same results without communicating or making threats