88 Samuel Woolley, Manufacturing Consensus: Understanding Propaganda in the Era of Automation and Anonymity (New Haven, CT: Yale University Press, 2023), 33.
89 Nathaniel Gleicher, “Removing Coordinated Inauthentic Behavior and Spam from India and Pakistan,” Meta, April 1, 2019, https://about.fb.com/news/2019/04/cib-and-spam-from-india-pakistan.
90 Woolley, Manufacturing Consensus, 35.
91 Zoya Mateen, “Jack Dorsey: India Threatened to Shut Twitter and Raid Employees,” BBC, June 13, 2023, https://www.bbc.com/news/world-asia-india-65886825.
92 Julia C. Wong and Hannah Ellis-Petersen, “Facebook Planned to Remove Fake Accounts in India—Until It Realized a BJP Politician Was Involved,” The Guardian, April 15, 2021, https://www.theguardian.com/technology/2021/apr/15/facebook-india-bjp-fake-accounts; Newley Purnell and Jeff Horwitz, “Facebook’s Hate-Speech Rules Collide with Indian Politics,” Wall Street Journal, August 14, 2020, https://www.wsj.com/articles/facebook-hate-speech-india-politics-muslim-hindu-modi-zuckerberg-11597423346.
93 Think of the GAN process as a pair of AI artists working against each other. One AI, called the “generator,” tries to create something that looks real, like a lifelike photo of a person. The other AI, called the “discriminator,” tries to tell if what the generator made is real or fake. They keep playing this game, with the generator getting better at making things and the discriminator getting better at spotting fakes. This competition makes the generator improve until it can create things that are so realistic, it’s hard to tell they’re not real. Jason Brownlee, “A Gentle Introduction to Generative Adversarial Networks (GANs),” Machine Learning Mastery, June 17, 2019, https://machinelearningmastery.com/what-are-generative-adversarial-networks-gans.
94 Shannon Bond, “AI-Generated Fake Faces Have Become a Hallmark of Online Influence Operations,” NPR, December 15, 2022, https://www.npr.org/2022/12/15/1143114122/ai-generated-fake-faces-have-become-a-hallmark-of-online-influence-operations; Sophie J. Nightingale and Hany Farid, “AI-Synthesized Faces Are Indistinguishable from Real Faces and More Trustworthy,” PNAS 119, no. 8 (2022): 1–3, https://doi.org/10.1073/pnas.2120481119.
95 Josh A. Goldstein and Renée DiResta, “Research Note: This Salesperson Does Not Exist: How Tactics from Political Influence Operations on Social Media Are Deployed for Commercial Lead Generation,” HKS Misinformation Review, September 15, 2022, https://misinforeview.hks.harvard.edu/article/research-note-this-salesperson-does-not-exist-how-tactics-from-political-influence-operations-on-social-media-are-deployed-for-commercial-lead-generation.
96 Shivansh Mundra et al., “New Approaches for Detecting AI-Generated Profile Photos,” LinkedIn Engineering, June 20, 2023, https://engineering.linkedin.com/blog/2023/new-approaches-for-detecting-ai-generated-profile-photos.
97 Cade Metz, “Meet GPT-3. It Has Learned to Code (and Blog and Argue),” New York Times, November 24, 2020, https://www.nytimes.com/2020/11/24/science/artificial-intelligence-ai-gpt3.html.
98 DiResta, Grossman, and Siegel, “In-House vs. Outsourced Trolls.”
99 Jeffrey St. Clair and Joshua Frank, “Go Ask Alice: The Curious Case of ‘Alice Donovan.’” CounterPunch, December 25, 2017, https://www.counterpunch.org/2017/12/25/go-ask-alice-the-curious-case-of-alice-donovan-2.
100 Kris McGuffie and Alex Newhouse, “The Radicalization Risks of GPT-3 and Advanced Neural Language Models,” Middlebury Institute of International Studies, September 9, 2020, https://www.middlebury.edu/institute/sites/www.middlebury.edu.institute/files/2020-09/gpt3-article.pdf.
101 Josh A. Goldstein et al., “Generative Language Models and Automated Influence Operations: Emerging Threats and Potential Mitigations,” arXiv, January 10, 2023, https://arxiv.org/abs/2301.04246.
102 Emilio Ferrara, “Social Bot Detection in the Age of ChatGPT: Challenges and Opportunities,” First Monday 28, no. 6 (June 5, 2023), https://doi.org/10.5210/fm.v28i6.13185; Kai-Cheng Yang and Filippo Menczer, “Anatomy of an AI-Powered Malicious Social Botnet,” arXiv (July 2023): 1–27, https://doi.org/10.48550/arXiv.2307.16336.
103 Philip Marcelo, “FACT FOCUS: Fake Image of Pentagon Explosion Briefly Sends Jitters Through Stock Market,” AP News, May 23, 2023, https://apnews.com/article/pentagon-explosion-misinformation-stock-market-ai-96f534c790872fde67012ee81b5ed6a4.
104 Blue checkmarks had once been awarded by Twitter to notable accounts, including news organizations and prominent people who had verified their identity. Following Elon Musk’s acquisition of Twitter, most legacy accounts lost their checks, and the verification symbol became available to any account willing to pay for an $8/month subscription to Twitter (without any actual verification). There were multiple instances of accounts paying to impersonate others within the first few days of the program.
