Who Does What? Archetypes of Roles Assigned to LLMs During Human-AI Decision-Making

• URL: http://arxiv.org/abs/2602.11924v1
• Date: Thu, 12 Feb 2026 13:23:04 GMT
• Title: Who Does What? Archetypes of Roles Assigned to LLMs During Human-AI Decision-Making
• Authors: Shreya Chappidi, Jatinder Singh, Andra V. Krauze,
• Abstract summary: This paper introduces the concept of human-LLM archetypes, defined as re-curring socio-technical interaction patterns.<n>We describe 17 human-LLM archetypes derived from a scoping literature review and thematic analysis of 113 LLM-supported decision-making papers.<n>We present relevant tradeoffs and design choices across human-LLM archetypes, including decision control, social hierarchies, cognitive forcing strategies, and information requirements.
• Score: 7.680699347065006
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: LLMs are increasingly supporting decision-making across high-stakes domains, requiring critical reflection on the socio-technical factors that shape how humans and LLMs are assigned roles and interact during human-in-the-loop decision-making. This paper introduces the concept of human-LLM archetypes -- defined as re-curring socio-technical interaction patterns that structure the roles of humans and LLMs in collaborative decision-making. We describe 17 human-LLM archetypes derived from a scoping literature review and thematic analysis of 113 LLM-supported decision-making papers. Then, we evaluate these diverse archetypes across real-world clinical diagnostic cases to examine the potential effects of adopting distinct human-LLM archetypes on LLM outputs and decision outcomes. Finally, we present relevant tradeoffs and design choices across human-LLM archetypes, including decision control, social hierarchies, cognitive forcing strategies, and information requirements. Through our analysis, we show that selection of human-LLM interaction archetype can influence LLM outputs and decisions, bringing important risks and considerations for the designers of human-AI decision-making systems

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