[Submitted on 22 Jul 2026]

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Abstract:Human judgment is fundamentally prone to error. A promise of AI is that it will rid decisions of bias and ensure a fairer and safer world for all. Yet research unequivocally demonstrates that LLMs exhibit consequential sociocognitive biases. We alert readers that bias in AI (a) is covert and ironically a feature of alignment goals, (b) is not merely a mirror, but an amplifier of human bias, (c) intensifies across model generations, and (d) even transmits bias to humans. Given the potentially seismic and ubiquitous influence of AI on decision making, we propose countermeasures that are diagnostic, regulatory and operational.

Submission history

From: Arnau Marin-Llobet [view email]
[v1] Wed, 22 Jul 2026 19:53:51 UTC (15 KB)