This podcast is intended as an introduction to issues that arise when an AI bot creates defamatory content. For detailed commentary on this specialist area of law, see: Gatley on Libel and Slander (12th Ed, 2017) and Duncan and Neill on Defamation (4th Ed, 2015 – with new addition forthcoming). For an overview, see our chapter on ‘Liability for Economic Harm’ in The Law of Artificial Intelligence (2020, forthcoming).

Cases relevant to auto-generated content include:

• Bunt v Tilly [2006] EWHC 407 (QB)
• Metropolitan International Schools Ltd (trading as Skillstrain and/or Train2Game) v Designtechnica Corpn (trading as Digital Trends) and others [2009] EWHC 1765 (QB)
• Tamiz v Google Inc. [2013] EWCA Civ 68 CA

For other jurisdictions, see e.g. Defteros v Google LLC [2020] VSC 219 at [40], in which Richards J summarised the Australian position as follows: “The Google search engine … is not a passive tool. It is designed by humans who work for Google to operate in the way that it does, and in such a way that identified objectionable content can be removed, by human intervention, from the search results that Google displays to a user.” For Hong Kong, see e.g. Yeung v Google Inc. [2014] HKCFI 1404; Oriental Press Group Ltd v Fevaworks Solutions Ltd [2013] HKFCA 47 (especially [76] for a test endorsed by the authors of Gatley).

On the contradictory positions taken by search engines worldwide, see, e.g., Sookman, “Is Google a publisher according to Google? The Google v Equustek and Duffy cases”, C.T.L.R. 2018, 24(1).