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A NEW COMMON LAW of WEB SCRAPING of WEB SCRAPING LAW a NEW COMMON Affiliate, Berkman Klein Center for Internet & Society, Harvard University

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A NEW COMMON LAW of WEB SCRAPING of WEB SCRAPING LAW a NEW COMMON Affiliate, Berkman Klein Center for Internet & Society, Harvard University 43059-lcb_25-1 Sheet No. 82 Side A 03/17/2021 10:17:28 LCB_25_1_Art_4_Sobel (Do Not Delete) 3/3/2021 7:28 PM A NEW COMMON LAW OF WEB SCRAPING by Benjamin L.W. Sobel * The Clearview AI facial recognition scandal is a monumental breach of pri- vacy that arrived at a particularly inopportune time. A shadowy company re- portedly scraped billions of publicly-available images from social media plat- forms and compiled them into a facial recognition database that it made available to law enforcement and private industry. To make matters worse, the scandal came to light just months after the Ninth Circuit’s decision in hiQ v. LinkedIn, which held that scraping the public web probably does not violate the Computer Fraud and Abuse Act (CFAA). Before hiQ, the CFAA would have seemed like the surest route to redress against Clearview. This Article analyzes the implications of the hiQ decision, situates the Clearview outrage in historical context, explains why existing legal remedies give aggrieved plain- tiffs little to no recourse, and proposes a narrow tort to empower ordinary In- ternet users to take action against gross breaches of privacy by actors like Clear- view: the tort of bad faith breach of terms of service. Section II argues that the Ninth Circuit’s hiQ decision marks, at least for the time being, the reascension of common law causes of action in a field that had been dominated by the CFAA. Section III shows that the tangle of possible common law theories that courts must now adapt to cyberspace resembles the strained property and contract concepts that jurists and privacy plaintiffs reck- oned with at the turn of the twentieth century. It suggests that modern courts, 43059-lcb_25-1 Sheet No. 82 Side A 03/17/2021 10:17:28 following the example some of their predecessors set over a century ago, may properly recognize some common law remedies for present-day misconduct. Section IV catalogs familiar common law claims to argue that no established property, tort, or contract claim fully captures the relational harm that conduct like Clearview’s wreaks on individual Internet users. Section V proposes a new tort, bad faith breach of terms of service, that can provide aggrieved plaintiffs * Affiliate, Berkman Klein Center for Internet & Society, Harvard University. I am grateful to Saptarishi Bandopadhyay, Alvaro Bedoya, Dinis Cheian, Gabe Doble, Terry Fisher, John Gold- berg, Joe Gratz, James Grimmelmann, Ben Hopper, Spencer Livingstone, Henry Smith, Rebecca Tushnet, and Salomé Viljoen for comments that have clarified and improved my arguments, and to the Harvard Law School Project on the Foundations of Private Law for financial support of this project. 147 C M Y K 43059-lcb_25-1 Sheet No. 82 Side B 03/17/2021 10:17:28 LCB_25_1_Art_4_Sobel (Do Not Delete) 3/3/2021 7:27 PM 148 LEWIS & CLARK LAW REVIEW [Vol. 25.1 with a proper remedy without sacrificing doctrinal fidelity or theoretical co- herence. I. Introduction ......................................................................................... 149 II. Cyberlaw’s Common Law Turn ............................................................ 153 A. Cyberlaw’s Common Law Origins ................................................... 154 B. The Burgeoning CFAA ................................................................... 156 C. The Waning CFAA (and the Waxing Common Law?) ...................... 157 III. Warren and Brandeis All Over Again: Why Common Law Can and Should Help Us .................................................................................... 159 A. Privacy From Property .................................................................... 160 B. Privacy From Contract ................................................................... 161 C. What Common Law Courts Can Do ............................................... 163 D. A Qualified Defense of Formalism ................................................... 166 IV. Web Scraping Looks More Like a Contracts Problem than a Property Problem ................................................................................................ 167 A. Users’ Property Interests ................................................................... 168 1. Users’ Personal Property Interests ............................................... 168 2. Users’ Copyright Interests .......................................................... 169 3. Users’ Publicity Rights ............................................................... 172 B. Platforms’ Property Interests ............................................................ 173 1. Platforms’ Personal Property Interests ......................................... 174 2. Platforms’ Intellectual Property Interests ..................................... 175 C. Users’ Relational Interests ................................................................ 176 1. Users’ Rights Under State Statutes.............................................. 176 2. Users’ “Privacy Tort” Claims ..................................................... 177 43059-lcb_25-1 Sheet No. 82 Side B 03/17/2021 10:17:28 3. Unjust Enrichment ................................................................... 179 D. Platforms’ Relational Interests .......................................................... 182 V. The Tort of Bad Faith Breach of Terms of Service ................................ 183 A. The Trust-Your-Overlords Problem ................................................. 183 1. The Information Fiduciary Response .......................................... 185 B. Bilateral Terms of Service Can Create Duties to Third Parties ........... 187 1. Anti-Scraping Covenants Arguably Exist for Users’ Benefit .......... 189 2. Privacy Harm Is a Foreseeable, Certain, and Proximate Consequence of Nonconsensual, Commercial Facial Recognition .. 190 3. Clearview’s Alleged Conduct Is Morally Blameworthy ................. 192 4. California’s Public Policy Is to Prevent Biometric Privacy Harms ..................................................................................... 194 C. Bad Faith Breaches of Contractual Duties Can Be Tortious ............... 195 D. Synthesizing Duties to Third Parties and Tortious Breaches: The Tort of Bad Faith Breach of Terms of Service ................................... 198 1. Willfulness of Breach ................................................................. 199 C M Y K 43059-lcb_25-1 Sheet No. 83 Side A 03/17/2021 10:17:28 LCB_25_1_Art_4_Sobel (Do Not Delete) 3/3/2021 7:28 PM 2021] WEB SCRAPING 149 2. Recklessness to or Knowledge of Consequences .............................. 199 3. Materiality of Breached Covenant.............................................. 200 E. Answering Some Threshold Objections ............................................. 201 1. The Tort Is Unlimited .............................................................. 201 2. The Tort Is Too Limited ........................................................... 203 3. What About the First Amendment? ............................................ 204 VI. Conclusion ........................................................................................... 206 I. INTRODUCTION On January 18, 2020, the investigative journalist Kashmir Hill broke a sensa- tional story: a “secretive” startup, Clearview AI, offers facial recognition software that identifies persons of interest against a database of nearly three billion photo- graphs. The company’s CEO initially claimed that the software was “strictly for law enforcement,” but later reporting revealed that Clearview’s app was also used by private companies to surveil their premises—and even by private individuals to vet dinner dates. Clearview did not invent facial recognition technology or pioneer a particularly powerful algorithm. Nor did Clearview develop a business model that allowed it to license a singularly comprehensive photo database. Instead, Clearview reportedly just “scraped” publicly-accessible photographs from sites like Facebook, YouTube, Twitter, and Instagram. That is, Clearview harvested images in bulk, using auto- mated software—in violation of the sites’ Terms of Service, which prohibited that very activity. The Clearview exposé outraged civil society. Days after Hill’s story broke, a 43059-lcb_25-1 Sheet No. 83 Side A 03/17/2021 10:17:28 1 Kashmir Hill, The Secretive Company That Might End Privacy as We Know It, N.Y. TIMES (Jan. 18, 2020), https://www.nytimes.com/2020/01/18/technology/clearview-privacy-facial- recognition.html. Hill’s report focused on law enforcement applications, but a subsequent leak of Clearview’s client list revealed that it also offered its services to private entities. Ryan Mac et al., Clearview’s Facial Recognition App Has Been Used by the Justice Department, ICE, Macy’s, Walmart, and the NBA, BUZZFEED NEWS (Feb. 27, 2020), https://www.buzzfeednews.com/article/ ryanmac/clearview-ai-fbi-ice-global-law-enforcement. 2 Kashmir Hill, Before Clearview Became a Police Tool, It Was a Secret Plaything of the Rich, N.Y. TIMES (Mar. 5, 2020), https://www.nytimes.com/2020/03/05/technology/clearview- investors.html; Mac et al., supra note 1. 3 Hill, supra note 1. 4 See generally, e.g., Jennifer Lynch, Clearview AI—Yet Another Example of Why We Need a Ban on Law Enforcement Use of Face Recognition Now, ELECTRONIC FRONTIER FOUND. (Jan. 31, 2020), https://www.eff.org/deeplinks/2020/01/clearview-ai-yet-another-example-why-we-need- ban-law-enforcement-use-face; Ryan Mac et al., Clearview AI Once Told Cops To “Run Wild” With Its Facial Recognition Tool. It’s
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