AI Automatons: AI Systems Intended to Imitate Humans
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Abstract (arXiv)
There is a growing proliferation of AI systems designed to mimic people's behavior, work, abilities, likenesses, or humanness -- systems we dub AI automatons. Individuals, groups, or generic humans are being simulated to produce creative work in their styles, to respond to surveys in their places, to probe how they would use a new system before deployment, to provide users with assistance and companionship, and to anticipate their possible future behavior and interactions with others, just to name a few applications. The research, design, deployment, and availability of such AI systems have, however, also prompted growing concerns about a wide range of possible legal, ethical, and other social impacts. To both 1) facilitate productive discussions about whether, when, and how to design and deploy such systems, and 2) chart the current landscape of existing and prospective AI automatons, we need to tease apart determinant design axes and considerations that can aid our understanding of whether and how various design choices along these axes could mitigate -- or instead exacerbate -- potential adverse impacts that the development and use of AI automatons could give rise to. In this paper, through a synthesis of related literature and extensive examples of existing AI systems intended to mimic humans, we develop a conceptual framework to help foreground key axes of design variations and provide analytical scaffolding to foster greater recognition of the design choices available to developers, as well as the possible ethical implications these choices might have.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 4 Mar 2025.
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Citing papers per year: 2025: 4; 2026: 6.
10 papers.
- 2025SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviorscited by 52
- 2025Humanizing Machines: Rethinking LLM Anthropomorphism Through a Multi-Level Framework of Designcited by 11
- 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigorcited by 7
- 2025Perspectives on How Sociology Can Advance Theorizing about Human-Chatbot Interaction and Developing Chatbots for Social Goodcited by 0
- 2026Implicit Humanization in Everyday LLM Moral Judgmentscited by 0
- 2026Informing AI Policy Assessment using Large-Scale Simulation of Interventionscited by 0
- 2026When AI Says "I have been in similar situations": Synthetic Lived Experience in Peer-Like Caregiver Supportcited by 0
- 2026Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII)cited by 0
- 2026Psychological Influences of Conversational AI: Research and Design Directions for Reducing Harm and Promoting Well-Beingcited by 0
- 2026Investigating Assistant Bias in LLM User Simulators Using a Role Vectorcited by 0
- 2026Investigating Assistant Bias in LLM User Simulators Using a Role Vector1 Sep 2026
- 2026Psychological Influences of Conversational AI: Research and Design Directions for Reducing Harm and Promoting Well-Being27 Jul 2026
- 2026When AI Says "I have been in similar situations": Synthetic Lived Experience in Peer-Like Caregiver Support16 Jun 2026
- 2026Position: AI/ML Deepfake Research is Misaligned with AI-Generated Non-Consensual Intimate Imagery (AIG-NCII)16 May 2026
- 2026Informing AI Policy Assessment using Large-Scale Simulation of Interventions20 Apr 2026
- 2026Implicit Humanization in Everyday LLM Moral Judgments23 Mar 2026
- 2025SimBench: Benchmarking the Ability of Large Language Models to Simulate Human Behaviors20 Oct 2025
- 2025Humanizing Machines: Rethinking LLM Anthropomorphism Through a Multi-Level Framework of Design25 Aug 2025
- 2025Perspectives on How Sociology Can Advance Theorizing about Human-Chatbot Interaction and Developing Chatbots for Social Good7 Jul 2025
- 2025Rigor in AI: Doing Rigorous AI Work Requires a Broader, Responsible AI-Informed Conception of Rigor17 Jun 2025