Earlier this year, Libratus – an artificial intelligence system developed by Carnegie Mellon University – conquered four of the world’s top professional poker players in a Head’s-Up No-Limit Texas Hold’em tournament (one of the most complicated forms of poker). This might not sound all that surprising to those recalling Gary Kasparov’s defeat at the ‘hands’ of IBM’s supercomputer, Deep Blue, but Libratus’ victory goes one step further. The system was programmed with only basic knowledge of poker rules and, over time, developed winning strategies independently from any human influence. Now imagine that Libratus was playing a different ‘game’, the aim of which would be the long-term maximisation of profit. What if, in pursuit of this goal, the system engaged in interdependent pricing with other machines of its kind to ‘optimise’ profitability for mutual benefit? Are competition authorities ready to deal with a new age of ‘robot-enhanced’ price setting?
This article was originally published on Kluwer Competition Law Blog.