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New protocol elicits XAI needs from stroke survivors for rehabilitation systems

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a novel video-based scaffolding protocol to elicit explainable AI (XAI) requirements from stroke survivors, addressing the challenges posed by acquired communication disorders. This protocol utilizes four scaffolding approaches—analogical bridging, projective personas, binary forcing, and extended response time—to help patients and caregivers articulate their needs for algorithmic transparency. The study identified heterogeneous XAI requirements and also revealed three systematic facilitation biases that practitioners should be aware of, contributing a reusable methodology for designing trustworthy human-machine systems in rehabilitation. AI

IMPACT This research offers a new methodology for designing more trustworthy AI systems in healthcare, specifically for stroke rehabilitation.

RANK_REASON The cluster contains an academic paper detailing a new methodology for eliciting XAI requirements. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New protocol elicits XAI needs from stroke survivors for rehabilitation systems

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The cluster contains an academic paper detailing a new methodology for eliciting XAI requirements. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Param Rajpura, Yogesh Kumar Meena ·

    From Dyad to Triad: Eliciting XAI Requirements in Stroke Rehabilitation

    arXiv:2607.25423v1 Announce Type: cross Abstract: Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trustworthy brain-computer interfaces for rehabilitation. How can patients and caregi…

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