Trust me, I’m wrong: The perils of AI hallucinations, a silent killer

Artificial intelligence is a disruptive technology, revolutionizing industries and fostering human capability. Irrespective of its efficiency, it is paired with a critical vulnerability, notably AI hallucinations. This case study dissects this phenomenon, where AI produces seemingly reasonable yet fabricated outputs. Hallucinations manifest in forms ranging from logical inconsistencies to persona deviations, with its detrimental consequences. They inflict severe reputational, financial, and ethical damage on both organizations and consumers. To address these risks, the case proposes a comprehensive two-pronged strategy. On the supply side, a technical framework of guardrails validates outputs and integrates trusted data sources, preventing hallucinations at its origin. Simultaneously, the demand side requires platform accountability and user education. Strategies include proactive prebunking, retroactive debunking, and initiatives that build user resilience through media literacy and cognitive nudges. The case helps students solve these problems by providing a practical framework for risk assessment and mitigation by empowering them to develop holistic, real-world solutions that combine both technical and behavioral strategies for the safe and responsible deployment of AI.

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Publication Details

Journal
Journal of Information Technology Teaching Cases
Published
2026-02-09
DOI
https://doi.org/10.1177/20438869261423221
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
0.00
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article

Trust me, I’m wrong: The perils of AI hallucinations, a silent killer

Anirban Chakraborty, Sourav Kumar Samanta
Journal of Information Technology Teaching Cases
Ethics and Social Impacts of AI
article

Trust me, I’m wrong: The perils of AI hallucinations, a silent killer

Anirban Chakraborty, Sourav Kumar Samanta
article en

Abstract

Artificial intelligence is a disruptive technology, revolutionizing industries and fostering human capability. Irrespective of its efficiency, it is paired with a critical vulnerability, notably AI hallucinations. This case study dissects this phenomenon, where AI produces seemingly reasonable yet fabricated outputs. Hallucinations manifest in forms ranging from logical inconsistencies to persona deviations, with its detrimental consequences. They inflict severe reputational, financial, and ethical damage on both organizations and consumers. To address these risks, the case proposes a comprehensive two-pronged strategy. On the supply side, a technical framework of guardrails validates outputs and integrates trusted data sources, preventing hallucinations at its origin. Simultaneously, the demand side requires platform accountability and user education. Strategies include proactive prebunking, retroactive debunking, and initiatives that build user resilience through media literacy and cognitive nudges. The case helps students solve these problems by providing a practical framework for risk assessment and mitigation by empowering them to develop holistic, real-world solutions that combine both technical and behavioral strategies for the safe and responsible deployment of AI.

Journal of Information Technology Teaching Cases
Indian Institute of Management Lucknow (IN)
Quality Education
Openalex Percentile: Top 64%
Ethics and Social Impacts of AI
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Trust me, I’m wrong: The perils of AI hallucinations, a silent killer — Anirban Chakraborty, Sourav Kumar Samanta · Journal of Information Technology Teaching Cases (2026) | TGRS Research Map | TGRS