# Learning to detect AI texts and learning the limits

**Authors:** Jiří Milička, Anna Marklová, Ondřej Drobil, Eva Pospíšilová

PMC · DOI: 10.1371/journal.pone.0333007 · PLOS One · 2025-10-15

## TL;DR

This study shows that people can learn to distinguish AI-generated texts from human-written ones with feedback, improving their accuracy and confidence.

## Contribution

The study demonstrates that explicit feedback significantly improves human ability to detect AI texts and recalibrate self-assessment.

## Key findings

- Participants with feedback improved in accuracy and confidence calibration.
- Without feedback, participants were most wrong when most confident.
- Training with feedback corrects misconceptions about AI text features.

## Abstract

This study investigates whether individuals can learn to accurately discriminate between human-written and AI-produced texts when provided with immediate feedback, and if they can use this feedback to recalibrate their self-perceived competence. We also explore the specific criteria individuals rely upon when making these decisions, focusing on textual style and perceived readability.

We used GPT-4o to generate several hundred texts across various genres and text types comparable to Koditex, a multi-register corpus of human-written texts. We then presented randomized text pairs to 254 Czech native speakers who identified which text was human-written and which was AI-generated. Participants were randomly assigned to two conditions: one receiving immediate feedback after each trial, the other receiving no feedback until experiment completion. We recorded accuracy in identification, confidence levels, response times, and judgments about text readability along with demographic data and participants’ engagement with AI technologies prior to the experiment. Participants receiving immediate feedback showed significant improvement in accuracy and confidence calibration.

Participants initially held incorrect assumptions about AI-generated text features, including expectations about stylistic rigidity and readability. Notably, without feedback, participants made the most errors precisely when feeling most confident—an issue largely resolved among the feedback group.

The ability to differentiate between human and AI-generated texts can be effectively learned through targeted training with explicit feedback, which helps correct misconceptions about AI stylistic features and readability, as well as potential other variables that were not explored, while facilitating more accurate self-assessment. This finding might be particularly important in educational contexts, since the ability to identify AI-generated content is highly desirable and, more importantly, false confidence in this domain can be harmful.

## Full-text entities

- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

10 figures with captions in the complete paper: https://tomesphere.com/paper/PMC12527182/full.md

## References

13 references — full list in the complete paper: https://tomesphere.com/paper/PMC12527182/full.md

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Source: https://tomesphere.com/paper/PMC12527182