Review of Kapczynsky (part 1 of 2)

Happy 2/2/22! Last week, I reviewed two of three essays published by the Knight First Amendment Institute on the marketplace of ideas, one by David Pozen; the other by Yochai Benkler. In summary, both Pozen and Benkler blame social media and Big Tech for the problem of misinformation, but Pozen’s dystopian solution basically boils down to censorship, while Benkler’s wishy-washy solution is to call for more “inclusive social democracy,” whatever that means. (For the record, my critique of Pozen’s misguided call for Internet censorship is available here, and my critique of Benkler’s magical thinking is here.)

Today, however, I will review Amy Kapczynsky’s thoughtful contribution to the Knight Institute’s three-part series. To the point, her main critique of the marketplace of ideas is that the online version of this “market” is not really a competitive one; instead, it is dominated by Big Tech firms like Facebook, Google, and Amazon. (Me: She left out Microsoft!) In other words, so long as misinformation is profitable, and so long as lies and fake news attract more attention and sell more ads than truth, the problem of misinformation will not be solved through the free exchange of ideas on the Internet.

So, what is to be done? To her immense credit, Kapczynsky, a law professor at Yale (my alma mater!) is not calling for Internet censorship the way that David Pozen and many others are. (Kevin Roose, I’m looking at you!) Nor does she conjure up some magical solution like “social democracy” the way Yochai Benkler does. Instead, her main policy recommendations are as follows:

  1. First off, my fellow Yalie recommends legislators to enact new “data publicity” laws and courts to scale back the scope of trade secret law in order to require the disclosure of Big Tech algorithms to the public. (Under existing law, such algorithms are protected as trade secrets.) As an aside, if I were Kapczynsky I would use a catchy slogan like “release the algorithms” to popularize her intriguing “data publicity” idea.
  2. Next, Professor Kapczynsky recommends anti-trust regulators to go after Big Tech firms by either “regulating their size” (i.e. breaking them up into smaller companies) or “restricting certain types of profit-seeking data gathering and use” (perhaps by preventing Internet platforms from sharing user data with third parties). (Me: where have we heard this before?) In other words, Facebook, Google, and Amazon (again, what about Microsoft?) are too big for our own good and their data policies need to be publicly regulated directly and not left up to private user agreements.
  3. Lastly, Professor Kapczynsky concludes her essay by suggesting that “we must explore the possibility of public data trusts and figure out new ways to support public media and intermediaries.” In plain English, Kapczynsky is calling for a government-run social media platform (me: uh, no thanks) and for NPR and PBS to receive more public funding (me: hmm).

I will respond in greater detail to these policy proposals in my next post, but in the meantime, notice how Kapczynsky — along with Pozen and Benkler, to be fair — has missed the most obvious and appealing way of making “the marketplace of ideas” more competitive: the creation of an actual market, which is precisely what I propose in my forthcoming paper “The Gödel Conspiracy“. That is, if social media misinformation were really a unique or serious problem (and I agree with Benkler that it is not), then why not create an actual information market and allow people to place bets on the truth values of fake news and conspiracy theories? Any takers?

A Tour of Machine Learning Algorithms | by Claire D. Costa | Towards Data  Science

About F. E. Guerra-Pujol

When I’m not blogging, I am a business law professor at the University of Central Florida.
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2 Responses to Review of Kapczynsky (part 1 of 2)

  1. Pingback: Three-headed monsters? A critique of Kapczynsky’s Internet-regulation proposals | prior probability

  2. Pingback: Global reply to Pozen, Benkler, and Kapczynsky: the optimal level of misinformation is not zero | prior probability

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