Previous business/academic article Next business/academic article
Business Articles Awards > Economics

4 Reasons We May Not See Colluding Robots Anytime Soon

Ai Deng, Law360, October 3, 2017

See Ai Deng's resume

Vote for this articleHelp

* Average
** Interesting
*** Good
**** Excellent
***** Must receive an Award!

Please note that the star(s) appearing on the article page before you have voted reflect the status of all votes registered to date.

Readers’ vote will close on February 9, 2018. Readers’ vote will allow you to nominate 1 article for each of the Awards, i.e., 10 Academic articles, 10 Business articles, and the best Soft Laws. The readers’ short-list of Academic and Business Articles will be communicated to the Board together with the 20 articles nominated by the Steering Committees. The Board will decide on the award-winning articles. Results will be announced at the Awards ceremony to take place in Washington DC on the eve of the ABA Antitrust Spring Meeting on April 10, 2018.

Click here to read the full article online

Many concerns have been raised in the antitrust community about algorithmic collusions. I summarized some of the views and concerns in a recent article titled “When Machines Learn to Collude.” In that article, drawing lessons from a recent artificial intelligence research, I highlighted several observations, including the lack of empirical evidence that the singular goal of profit maximization would lead to collusion by machines. Instead, to design successful colluding algorithms, learning to collude likely has to be an explicit design feature. If a firm adopts such a computer algorithm, however, the question of antitrust liability seems to be less complicated by the use of robots. In this note, I summarize some additional reasons why algorithmic collusion, even if possible, could be limited in its scope.

Download our brochure