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article | Large language models (LLMs) are increasingly deployed as decision-support tools in organizational contexts, yet their susceptibility to contextual framing remains poorly understood. This preregistered experimental study systematically examines how six framing dimensions—procedural justice, outcome severity, stakeholder power, resource scarcity, temporal urgency, and transparency requirements—influence ethical recommendations from three frontier models: Claude 3.5 Sonnet, GPT-4o, and Gemini 1.5 Pro. We developed 5,000 unique organizational vignettes using a fractional factorial exper
When Algorithms Meet Ethics: Systematic Evidence of Framing Effects in LLM Organizational Decision-Making
article | Large language models (LLMs) are increasingly deployed as decision-support tools in organizational contexts, yet their susceptibility to contextual framing remains poorly understood. This preregistered experimental study systematically examines how six framing dimensions—procedural justice, outcome severity, stakeholder power, resource scarcity, temporal urgency, and transparency requirements—influence ethical recommendations from three frontier models: Claude 3.5 Sonnet, GPT-4o, and Gemini 1.5 Pro. We developed 5,000 unique organizational vignettes using a fractional factorial exper