Claims

AI support can improve task performance while weakening users' metacognitive accuracy and leaving their own reasoning unimproved

Claim · All claims
Evidence · 1 study (2 entries) · causal r? · q1
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 2 of 2 entries) · not reviewed by a person

Subclaims

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q1 i? LLMs improved task performance but made users overconfident about their own accuracy, and most participants relied on single prompts without further follow-up. → Sander de Jong 2026 q1 i? Giving physicians access to an LLM did not improve their diagnostic reasoning even though the LLM outperformed them. → Sander de Jong 2026 (2)

Evidence

Sander de Jong 2026

Sander de Jong. (2026). Open Questions Towards Skill-Sustaining Reliance in Reflective AI Engagement. Workshop paper presented at CHIWORK'26 Workshop on Human Agency and Skill in AI-Supported Work. https://arxiv.org/abs/2609.27726 doi:10.48550/arxiv.2609.27726

q1 · i? · theoretical · r3

A workshop position paper that poses open questions; it runs no study and has no review method. In Section 4 it reports, second-hand and citing Fernandes et al., that LLMs improved task performance but made users overconfident about their own accuracy, and that most participants relied on single prompts without follow-up, which the author reads as the interaction not encouraging reflection. The finding is Fernandes et al.'s, not this paper's.

"Fernandes et al., who found that LLMs improved task performance but made users overconfident about their own accuracy [11]. Most participants relied on single prompts without further follow-up"

Sander de Jong 2026 (2)

Sander de Jong. (2026). Open Questions Towards Skill-Sustaining Reliance in Reflective AI Engagement. Workshop paper presented at CHIWORK'26 Workshop on Human Agency and Skill in AI-Supported Work. https://arxiv.org/abs/2609.27726

q1 · i? · causal · r?

Narrative review attribution in Section 5: the paper reports, citing Goh et al., that physician access to an LLM did not improve their diagnostic reasoning despite the LLM outperforming them, suggesting the interaction did not translate AI capability into better human reasoning.

"Goh et al. found that giving physicians access to an LLM did not improve their diagnostic reasoning, even though the LLM outperformed them"

Discussion

Page metadata
Field Value
type claim
id ai-performance-metacognition-dissociation
title AI support can improve task performance while weakening users' metacognitive accuracy and leaving their own reasoning unimproved
description AI support can improve task performance while weakening users' metacognitive accuracy and leaving their own reasoning unimproved
status review
evidence_strength weak
newest_evidence 2026
source_checked 2026-10-20
generated by process:wiki-ingest on 2026-10-11
trust unverified — no one has confirmed this page's content
sources 2 — sander-de-jong-2026, sander-de-jong-2026-2

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