AI persuasion, AI manipulation
Or, have we always been reward hacking each other?
2015-10-05 — 2025-06-12
adversarial
AI safety
bounded compute
communicating
cooperation
culture
economics
faster pussycat
language
machine learning
mind
neural nets
NLP
security
technology
wonk
Suspiciously similar content
Placeholder, for future wondering about where our conversations with empathic machines will take us.
Humans are not amazing at rhetoric. Are machines better? Almost certainly. What will that mean for us?
1 Good metaphors for the persuasiveness of AI
Persuasive equal? Grooming a child? How potent is an AI at moving us, and what metaphor should that move us to consider its relationship to humanity?
2 Field experiments in persuasive AI
See This AI chatbot got conspiracy theorists to question their convictions (Costello, Pennycook, and Rand 2024).
This is pitched as AI-augmented de-radicalisation but you could change the goal and think of it as a test case for AI-augmented persuasion in general. Interestingly the AI doesn’t seem to need to resort to the traditional workarounds for human tribal reasoning such as deep canvassing, and the potential for scaling up individualised mass persuasion seems like it could become the dominant game in town, at least until the number of competing persuasive AI chatbots caused people to become inured to them.
See also Salvi et al. (2024).
3 Therapist in a box
TBD See also artifical intimacy.
4 Spamularity and the scam economy
See Spamularity for more on this.
5 The future wherein it is immoral to deny someone the exquisite companionship and attentive understanding of their own personal AI companion
See artificial intimacy for more on this.
6 Incoming
7 References
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Bay. 2018. “Weaponizing the Haters: The Last Jedi and the Strategic Politicization of Pop Culture Through Social Media Manipulation.” First Monday.
Benkler, Faris, and Roberts. 2018. Network propaganda: manipulation, disinformation, and radicalization in American politics.
Bradshaw, and Howard. 2017. “Troops, Trolls and Troublemakers: A Global Inventory of Organized Social Media Manipulation.”
Buçinca, Malaya, and Gajos. 2021. “To Trust or to Think: Cognitive Forcing Functions Can Reduce Overreliance on AI in AI-Assisted Decision-Making.” Proceedings of the ACM on Human-Computer Interaction.
Clark, and Clark. 2004. Natural-Born Cyborgs: Minds, Technologies, and the Future of Human Intelligence.
———. 2011. Supersizing the Mind: Embodiment, Action, and Cognitive Extension. Philosophy of Mind.
Costello, Pennycook, and Rand. 2024. “Durably Reducing Conspiracy Beliefs Through Dialogues with AI.” Science.
Dezfouli, Nock, and Dayan. 2020. “Adversarial Vulnerabilities of Human Decision-Making.” Proceedings of the National Academy of Sciences.
El-Sayed, Akbulut, McCroskery, et al. 2024. “A Mechanism-Based Approach to Mitigating Harms from Persuasive Generative AI.”
Fang, Liu, Danry, et al. 2025. “How AI and Human Behaviors Shape Psychosocial Effects of Chatbot Use: A Longitudinal Randomized Controlled Study.”
Jaidka, Chen, Chesterman, et al. 2024. “Misinformation, Disinformation, and Generative AI: Implications for Perception and Policy.” Digit. Gov.: Res. Pract.
Jecmen, Zhang, Liu, et al. 2020. “Mitigating Manipulation in Peer Review via Randomized Reviewer Assignments.” In Advances in Neural Information Processing Systems.
Kamenica. 2019. “Bayesian Persuasion and Information Design.” Annual Review of Economics.
Kanich, Kreibich, Levchenko, et al. 2008. “Spamalytics: An Empirical Analysis of Spam Marketing Conversion.” In Proceedings of the 15th ACM Conference on Computer and Communications Security. CCS ’08.
Khan, Hughes, Valentine, et al. 2024. “Debating with More Persuasive LLMs Leads to More Truthful Answers.”
Manzini, Keeling, Marchal, et al. 2024. “Should Users Trust Advanced AI Assistants? Justified Trust As a Function of Competence and Alignment.” In The 2024 ACM Conference on Fairness, Accountability, and Transparency.
Martin, and Yurukoglu. 2017. “Bias in Cable News: Persuasion and Polarization.” American Economic Review.
Marwick, and Lewis. 2017. “Media Manipulation and Disinformation Online.”
Mercier, and Sperber. 2011. “Why Do Humans Reason? Arguments for an Argumentative Theory.” Behavioral and Brain Sciences.
———. 2017. The Enigma of Reason.
Messeri, and Crockett. 2024. “Artificial Intelligence and Illusions of Understanding in Scientific Research.” Nature.
Meta Fundamental AI Research Diplomacy Team (FAIR), Bakhtin, Brown, et al. 2022. “Human-Level Play in the Game of Diplomacy by Combining Language Models with Strategic Reasoning.” Science.
Pataranutaporn, Leong, Danry, et al. 2022. “AI-Generated Virtual Instructors Based on Liked or Admired People Can Improve Motivation and Foster Positive Emotions for Learning.” In 2022 IEEE Frontiers in Education Conference (FIE).
Pataranutaporn, Liu, Finn, et al. 2023. “Influencing Human–AI Interaction by Priming Beliefs about AI Can Increase Perceived Trustworthiness, Empathy and Effectiveness.” Nature Machine Intelligence.
Pfeffer, and Gal. 2007. “On the Reasoning Patterns of Agents in Games.” In AAAI-07/IAAI-07 Proceedings. Proceedings of the National Conference on Artificial Intelligence.
Rao, and Reiley. 2012. “The Economics of Spam.” Journal of Economic Perspectives.
Salvi, Ribeiro, Gallotti, et al. 2024. “On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial.”
Shumailov, Shumaylov, Zhao, et al. 2023. “The Curse of Recursion: Training on Generated Data Makes Models Forget.”
Sperber, and Mercier. 2012. “Reasoning as a Social Competence.” In Collective Wisdom.
Swartz, Marwick, and Larson. 2025. ScamGPT: GenAI and the Automation of Fraud.
Taylor, and Hoffmann. n.d. “Industry Responses to Computational Propaganda and Social Media Manipulation.”
Teeny, Siev, Briñol, et al. 2021. “A Review and Conceptual Framework for Understanding Personalized Matching Effects in Persuasion.” Journal of Consumer Psychology.
Turkle. 2011. Alone Together: Why We Expect More from Technology and Less from Each Other.