What question did this study set out to answer?

The aim is to evaluate AI behavior in organizational settings using the Human-Context Reasoning framework.

May 25, 2026Open Access

Human-Context Reasoning in Artificial Intelligence: A Qualitative Evaluation of AI Behavior in Organizational Decision Environments

Key Points

The aim is to evaluate AI behavior in organizational settings using the Human-Context Reasoning framework.
Introduced a qualitative framework for assessing AI behavior in organizational decision contexts.
Evaluated AI responses to various scenarios such as layoffs and ethical conflicts.
Context-sensitive reasoning patterns were identified when AI systems engaged with real human contexts, rather than abstract scenarios.
AI demonstrated improved decision-making capabilities when grounded in specific human situations.

Abstract

This paper introduces Human-Context Reasoning (HCR), a qualitative framework for evaluating AI behavior in organizational decision environments characterized by ambiguity, emotional complexity, and structural constraints. The study evaluates AI responses across scenarios including layoffs, burnout, ethical conflict, and power asymmetry. Findings suggest that context-sensitive reasoning patterns emerge when AI systems are constrained to operate within lived human situations rather than abstract problem-solving structures. The work proposes Human-Context Reasoning as an early conceptual framework for situationally grounded AI systems.

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