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Evidence record 515 · automatically gathered

Generative AI Literacy Training Improves Intelligence Analysts' Discrimination of Real and AI-Generated Images

Across social and online platforms, people are increasingly exposed to AI-generated images. As a consequence, the task of distinguishing AI-generated from authentic images is becoming a central challenge for information ecosystems. While humans perform better than chance, accuracy falls short of many operational needs. Initial evidence shows that visually oriented training can improve deepfake detection but does not improve participants' ability to identify real images as real. Here, we investig

Record details

Published: 26 June 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Misinformation · Finance, VC & PE
Retrieved: 14 July 2026

source-onlyevidence status

These records share source-supplied organisations, an exact publisher byline, automatic topics or regions. The reason is shown on every link; related does not mean supporting, agreeing with or verifying this record.

Shared topic: Bias & fairness · Shared topic: Misinformation

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Shared topic: Bias & fairness · Shared topic: Misinformation

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Shared topic: Bias & fairness · Shared topic: Misinformation

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Shared topic: Bias & fairness · Shared topic: Finance, VC & PE

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Shared topic: Bias & fairness · Shared topic: Finance, VC & PE

PeerCheck: Enhancing LLM-Generated Academic Reviews Towards Human-Level Quality

arXiv · 18 June 2026

Shared topic: Bias & fairness · Shared topic: Finance, VC & PE

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How to cite this record

ethics.ai (26 June 2026), “Generative AI Literacy Training Improves Intelligence Analysts' Discrimination of Real and AI-Generated Images,” evidence record 515, https://ethics.ai/record/515 (originally published by arXiv).

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