Combatting Online Harms Through Innovation
for The Markup used a machine learning tool to examine whether “Amazon routinely ranked its own brands and exclusives ahead of better-known brands with higher star ratings.” 41 One caveat for consumer protection or competition enforcers, however, is that it makes little sense to use limited resources to obtain any AI tools without having already decided what exactly to do with them. It would be more sensible to determine first what an agency wants to find or learn and then see what available tools, AI or not, are best suited and most appropriate for that task. Of course, the agency would also need staff capable of deploying such tools and evaluating their responsible use.
B. Manipulated content intended to mislead individuals, including deepfake videos and fake individual reviews Deepfakes While most of the Congressionally specified harms predate and exist outside the online environment, deepfakes — and similar forms of synthetic media or media manipulation — are creatures of it. Deepfakes are video, photo, text, or audio recordings that seem real but have been manipulated with AI. 42 It would stand to reason, then, that AI or other sophisticated technology could help with — if not be integral to — detection of deepfakes. Indeed, public and private research on AI solutions to the deepfake problem have been underway for some time. As detection technology continues to improve, however, so will the ability to evade it, meaning that this AI battle will not end soon and that technological mitigation is insufficient. 43 A team overseen by DHS issued a report in 2021 that came to this conclusion and recommended pairing improved and constantly updated detection tools — to be used proactively and open-sourced as appropriate — with new laws, public-private cooperation, scientific responsibility, authentication tools, and education, with due consideration for civil liberties. 44
41 See Julia Angwin, The Mathematics of Amazon’s Advantage, Hello World #79 (Oct. 16, 2021), https://www.getrevue.co/profile/themarkup/issues/the-mathematics-of-amazon-s-advantage-803575. 42 In 2020, the Commission explored issues related to voice cloning, a subcategory of deepfakes, in a public workshop. See https://www.ftc.gov/news-events/events-calendar/you-dont-say-ftc-workshop-voice-cloningtechnologies. 43 See DHS, Increasing Threat of Deepfake Identities at 29 (Sep. 2021), https://www.dhs.gov/publication/2021-aepdeliverables; Government Accountability Office, Science & Tech Spotlight: Deepfakes (Feb. 2020), https://www.gao.gov/assets/gao-20-379sp.pdf; European Parliamentary Research Service (“EPRS”), Tackling deepfakes in European policy at 16-19, 60 (Jul. 2021), https://www.europarl.europa.eu/stoa/en/document/EPRS STU(2021)690039; Siwei Lyu, Deepfakes and the New AI-Generated Fake Media Creation-Detection Arms Race, Scientific American (Jul. 20, 2020), https://www.scientificamerican.com/article/detecting-deepfakes1/; James Vincent, Facebook develops new method to reverse-engineer deepfakes and track their source, The Verge (Jun. 16, 2021), https://www.theverge.com/2021/6/16/22534690/facebook-deepfake-detection-reverse-engineer-ai-modelhyperparameters. 44 DHS, Increasing Threat of Deepfake Identities, supra note 43 at 3, 29-34.
FEDERAL TRADE COMMISSION • FTC.GOV
12
