The authors introduce a taxonomy with target, functional role, and mode of justification axes plus a framework that decomposes abstract XAI desiderata into concrete benchmarkable tasks via identified dependency structures.
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2026 3verdicts
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Oversight strategy in computer-use agents shapes exposure to problematic actions more reliably than correction success, with plan-based approaches reducing occurrences but not uniformly improving interventions.
A literature review concludes that pursuing consensus in data annotation creates biased AI by dismissing subjective disagreements and enforcing geographic hegemony, and proposes mapping diversity instead.
citing papers explorer
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Bridging the Disciplinary Gap in Explainable AI: From Abstract Desiderata to Concrete Tasks
The authors introduce a taxonomy with target, functional role, and mode of justification axes plus a framework that decomposes abstract XAI desiderata into concrete benchmarkable tasks via identified dependency structures.
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Comparing Human Oversight Strategies for Computer-Use Agents
Oversight strategy in computer-use agents shapes exposure to problematic actions more reliably than correction success, with plan-based approaches reducing occurrences but not uniformly improving interventions.
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The Consensus Trap: Dissecting Subjectivity and the "Ground Truth" Illusion in Data Annotation
A literature review concludes that pursuing consensus in data annotation creates biased AI by dismissing subjective disagreements and enforcing geographic hegemony, and proposes mapping diversity instead.