Below is a post by valued guest contributor, Ai Deng, PhD. of Bates White Economic Consulting.
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There has been growing interest in the legal community in artificial intelligence (AI), and more specifically in machine learning (ML). This recent interest in AI is at least in part driven by concerns about algorithmic collusion, i.e., the possibility that computer algorithms could ultimately collude on their own, without human facilitation.
There is no question that the antitrust community is largely playing catch-up when it comes to the technical subject matters of AI and ML. As the Acting Chair of the Federal Trade Commission Maureen K. Ohlhausen noted, “The inner workings of these tools are poorly understood by virtually everyone outside the narrow circle of technical experts that directly work in the field.”
While there is no point to antitrust attorneys understanding the nuts and bolts of AI and ML technology, a basic understanding is necessary to better understand and assess the implications of the AI/ML research on antitrust and related legal and economic issues. That is the motivation behind my latest article. Through a series of simple examples, I introduce some fundamental concepts in ML. Along the way, I also discuss a wide variety of ML applications in the law and economics field. I conclude with a brief discussion of the hot topic of algorithmic collusion.
You can download the paper here https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3082514
As always, I appreciate your thoughts and comments. You can reach me at [email protected] or connect with me on LinkedIn [here].
Ai Deng, PhD
Principal
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