Identifiable Victim Effect

Narrative over Numbers: The Identifiable Victim Effect and its Amplification Under Alignment and Reasoning in Large Language Models

This research systematically investigates the Identifiable Victim Effect (IVE) in Large Language Models, a cognitive bias where specific, narratively described victims receive more resources than statistically characterized groups. The large-scale empirical study across 16 frontier LLMs determines if these systems inherit human affective irrationalities in critical applications like humanitarian triage and content moderation.