Rationalize: Shared Semantic Reasoning for Human-AI Alignment
We introduce Rationalize, a role-pair framework for shared semantic reasoning between humans and AI models in data-driven sensemaking. Building on ideas in human-machine teaming and critical thinking, we conceptualize human-AI interaction as a series of complementary role pairs (Explorer-Guide, Investigator-Informant, Teacher-Student, Judge-Advocate) operating in a shared reasoning space. In this space, human analysts and AI models (such as LLMs) make purposes, questions, assumptions, evidence,
Record details
Published: 28 May 2026
Source: arXiv
Category: Research
Topics: Safety & alignment · Children & education · Finance, VC & PE
Retrieved: 14 July 2026
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ethics.ai (28 May 2026), “Rationalize: Shared Semantic Reasoning for Human-AI Alignment,” evidence record 3473, https://ethics.ai/record/3473 (originally published by arXiv).
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