Claims

Explainability's effect on trust in AI-enabled systems is mixed: it can increase trust and reliance but also raises cognitive load, slows performance, and sometimes does not improve trust

Claim · All claims
Evidence · 1 study (2 entries) · quant-synthesis r2 · q2
Currency · newest study 2026 · not yet checked against its sources · 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.

q2 i? Several reviewed studies found explainability positively increased user trust and reliance, particularly in complex visual tasks with heatmap-based explanations. → Abramson SL 2026 q2 i? Other reviewed studies found explanations, particularly multiple types simultaneously, increased cognitive load, slowed user performance, or did not improve trust even when present. → Abramson SL 2026 (2)

Evidence

Abramson SL 2026

Abramson SL, Sora-Cardenas J, Nandakumar P, Bruce JE, Gopinath N, Zangari LG and Feijóo-García PG (2026). Trust and interaction design in AI-enabled systems: a systematic literature review. Front. Psychol. 17:1932655. https://doi.org/10.3389/fpsyg.2026.1932655

q2 · i? · quant-synthesis · r2

The review reports, citing Maehigashi et al. (2024a, b), that heatmap-based explanations aided comprehension and increased trust in complex visual tasks; the review narrates these studies without printing effect sizes.

"Several studies found that explainability positively increased user trust and reliance, particularly in complex visual tasks where heatmap-based explanations aided user comprehension of AI reasoning"

Abramson SL 2026 (2)

Abramson SL, Sora-Cardenas J, Nandakumar P, Bruce JE, Gopinath N, Zangari LG and Feijóo-García PG (2026). Trust and interaction design in AI-enabled systems: a systematic literature review. Front. Psychol. 17:1932655. https://doi.org/10.3389/fpsyg.2026.1932655

q2 · i? · review · r3

The review attributes countervailing findings to the same cited studies: explanations "increased cognitive load", slowed performance, and in some cases did not improve trust. No effect sizes are printed for these outcomes.

"other studies reported that providing explanations, particularly multiple types of explanations simultaneously, increased cognitive load ( Maehigashietal., 2024a ), slowed user performance (Maehigashietal.,2024b ),andinsomecasesdidnotimprovetrust evenwhenexplanationswerepresent"

Discussion

Learner Variables

Page metadata
Field Value
type claim
id explainability-mixed-effect-on-trust
title Explainability's effect on trust in AI-enabled systems is mixed: it can increase trust and reliance but also raises cognitive load, slows performance, and sometimes does not improve trust
description Explainability's effect on trust in AI-enabled systems is mixed: it can increase trust and reliance but also raises cognitive load, slows performance, and sometimes does not improve trust
status review
evidence_strength mixed
newest_evidence 2026
generated by process:wiki-ingest on 2026-10-10
trust unverified — no one has confirmed this page's content
sources 2 — abramson-sl-2026, abramson-sl-2026-2

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