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Evidence record 4009 · automatically gathered

Bridging the Disciplinary Gap in Explainable AI: From Abstract Desiderata to Concrete Tasks

Explainable AI (XAI) is often criticized for failing to satisfy broad desiderata (e.g., fairness, accountability) and for limited practical value to stakeholders. This challenge partly arises because researchers across disciplines prioritize different sets of desiderata that remain underspecified and context-dependent, yet expect XAI to satisfy them simultaneously, resulting in fragmented and sometimes incompatible operationalizations. We argue that many desiderata are not independent, but inste

Record details

Published: 19 May 2026
Source: arXiv
Category: Research
Topics: Bias & fairness · Transparency
Retrieved: 14 July 2026

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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: Transparency

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How to cite this record

ethics.ai (19 May 2026), “Bridging the Disciplinary Gap in Explainable AI: From Abstract Desiderata to Concrete Tasks,” evidence record 4009, https://ethics.ai/record/4009 (originally published by arXiv).

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