That is the new title of my newly revised work-in-progress, which I will be presenting this Friday (17 November) at a daylong symposium on “Free Speech and the U.S. Constitution” (see here) at the University of St. Thomas School of Law in Minneapolis. Below is an excerpt from the introduction to my paper; my footnotes are below the fold:
What is the free speech dilemma? On the one hand, if we adopt a laissez faire attitude toward speech, how do we screen out disinformation or lies?[1] If, on the other hand, we attempt to screen out bad information via content moderation policies or other forms of censorship, how do we distinguish falsehoods from truth?[2] Was Lee Harvey Oswald, for example, part of a conspiracy to assassinate JFK?[3] Did COVID-19 originate from a lab in Wuhan, China?[4] Were the 2020 U.S. presidential elections stolen.[5]
In principle, three types of responses to this dilemma are possible: hardcore government censorship (the Communist China model), soft censorship or content moderation (the Mark Zuckerberg model), and absolute free speech (the Elon Musk model).[6] Under the Chinese model, the government strictly monitors Internet access and blocks website content,[7] while the Zuckerberg or soft censorship approach consists of some combination of content moderation, deplatforming, shadow-banning, and other forms of speech suppression.[8] Free speech absolutism, by contrast, is the most permissive or laissez faire approach to the problem of disinformation: everyone is free to post whatever information they want as long as no laws are being violated.[9]
Alas, none of these “solutions” is capable of distinguishing truth from lies in a reliable or consistent manner. The main problem with the Chinese model—and with any type of content moderation approach more generally—is that one cannot always determine ahead of time which conspiracy theories or disputed news stories are true and which are false.[10] By the same token, with free speech absolutism there is no real disincentive for posting false information on the Internet, since the marginal cost of Internet speech is virtually costless.[11] Also, to the extent many Internet users are engaged in “motivated reasoning,”[12] free speech absolutism might exacerbate the problem of false information.
So, what is to be done? What if we promoted a “truth market model” instead of censorship, content moderation, or costless speech? As explained in the remainder of this Article, a truth market would operate as a retrodiction market and would specialize in conspiracy theories, fake news, urban legends, and other forms of disputed information. On this market, people could buy or sell belief contracts, allowing them to bet on the truth values of their favorite conspiracy theories. With enough bettors representing a wide variety of views, the price of each belief contract should reflect the truth value of the conspiracy theory being bet on.
[1] The U.S. Department of Homeland Security (DHS) defines disinformation as “false information that is deliberately spread with the intent to deceive or mislead ….” See DHS Fact Sheet, DHS Internal Working Group Protects Free Speech and Other Fundamental Rights When Addressing Disinformation that Threatens the Security of the United States. Department of Homeland Security (May 2, 2022), https://perma.cc/HKQ2-RY6P (DHS Fact Sheet).
[2] Some recent works to address this difficult question include Yochai Benkler, Robert Faris, & Hal Roberts, Network Propaganda: Manipulation, Disinformation, and Radicalization in American Politics (2018); Richard L. Hasen, Cheap Speech: How Disinformation Poisons Our Politics–and How to Cure It (2022); and David L. Sloss, Tyrants on Twitter: Protecting Democracies from Information Warfare (2022). Alas, the scholarly literature regarding Internet disinformation is too voluminous to cite in full. For a small sample of this emerging and engaging literature (in alphabetical order), see, for example, Ibegbulem Obioma Hilary & Olannye-Okonofua Dumebi, Social Media as a Tool for Misinformation and Disinformation Management, 5 Linguistics and Culture Review 496 (2021); Filippo Menczer & Thomas Hills, Information Overload Helps Fake News Spread, and Social Media Knows It, 323 Scientific American 54 (2020); Michela Del Vicario, et al., The Spreading of Misinformation Online, 113 Proceedings of the National Academy of Sciences 554 (2016); and Christopher S. Yoo, Free Speech and the Myth of the Internet as Unintermediated Experience, 78 The George Washington Law Review 697 (2009).
[3] See, e.g., Jim Garrison, On the Trail of Assassins (2012).
[4] For a recent report giving credence to the lab-leak theory, see Katherine Eban & Jeff Kao, COVID-19 Origins: Investigating a “Complex and Grave Situation” Inside a Wuhan Lab, ProPublica (Oct. 28, 2022), https://www.propublica.org/article/senate-report-covid-19-origin-wuhan-lab.
[5] See, e.g., Ryan Teague Beckwith, Here Are the 253 Key Political Leaders Who Back Trump’s False Claims of Election Fraud, Bloomberg (Sep. 6, 2022), https://perma.cc/7PGG-STPY. For a comprehensive survey of various statistical claims that the 2020 elections were stolen, see Andrew C. Eggers, et al., No Evidence for Systematic Voter Fraud: A Guide to Statistical Claims about the 2020 Election, 118 Proceedings of the National Academy of Sciences e2103619118 (2022), https://perma.cc/5VL9-EQ3C.
[6] As an aside, these three approaches loosely correspond with the major methods of knowledge organization identified by F. A. Hayek in his classic work “The Use of Knowledge in Society”: central planning, monopoly, and markets. See Hayek, The Use of Knowledge in Society, American Economic Review, Vol. 35, No. 4. (Sep., 1945), at p. 521.
[7] Beina Xu & Eleanor Albert, Media Censorship in China, 24 Council on Foreign Relations 243 (Feb. 17, 2017), https://www.cfr.org/backgrounder/media-censorship-china.
[8] For myriad examples of the content moderation or Zuckerberg approach, see the Wikipedia entry for “Censorship by Facebook,” https://en.wikipedia.org/wiki/Censorship_by_Facebook. In addition to Meta Platforms’ internal efforts to monitor speech on its popular social media platforms Facebook and Instagram, The Intercept recently revealed that officials at the Department of Homeland Security (DHS) has for several years been colluding with Facebook, Twitter, and other Big Tech firms to censor what the DHS deems to be false information. See Ken Klippenstein & Lee Fang, Truth Cops: Leaked Documents Outline DHS’s Plans to Police Disinformation, The Intercept (Oct. 31, 2022), https://theintercept.com/2022/10/31/social-media-disinformation-dhs/.
[9] See, e.g., Dan Milmo, How “Free Speech Absolutist” Elon Musk Would Transform Twitter, The Guardian (Apr. 14, 2022), https://perma.cc/HC67-4ULE. In reality, however, Elon Musk has used his newfound control of Twitter to censor his critics. See, e.g., Amanda Marcotte, Elon Musk’s Censorship Spree Exposes the Fundamental Flaw in the Right’s Definition of “Free Speech”, Salon (Dec. 19, 2022), https://perma.cc/RPL2-7BCK.
[10] For an in-depth survey of a far-fetched but real conspiracy, see Ryan Holiday, Conspiracy: A True Story of Power, Sex, and a Billionaire’s Secret Plot to Destroy a Media Empire 2018 (describing an “unbelievable conspiracy” led by billionaire tech investor Peter Thiel against the popular Internet media outlet Gawker).
[11] See, e.g., Hasen, op. cit.
[12] See, e.g., Ming M. Boyer, Aroused Argumentation: How the News Exacerbates Motivated Reasoning, 28 The International Journal of Press/Politics 92 (2023).
prior probability 