GenAI Use Behavior and Post‐Failure Perceptions Among People With Functional Disabilities: A Multimethod Study

GenAI Use Behavior and Post‐Failure Perceptions Among People With Functional Disabilities: A Multimethod Study

Summary

This paper examines how people with functional disabilities (hearing, visual and mobility impairments) adopt and respond to generative AI (GenAI). Using two complementary studies — a survey (Study 1, n=284) employing a genetic algorithm and Bayesian regression, and an experiment (Study 2, n=231) contrasting GenAI vs human-caused service failures — the authors identify drivers of GenAI use and how failure attributions shape future expectations.

Key findings: habit, promotional benefits, trust and behavioural intention positively predict GenAI use; perceived value moderates (and can weaken) the intention→use link; failures attributed to GenAI produce lower inferential judgement than human failures; and both attitudes and prior GenAI use buffer negative post-failure reactions.

Key Points

• Study 1 (survey, n=284) found four main predictors of GenAI use among people with functional disabilities: habit, promotional benefits, perceived trust and behavioural intention.
• Perceived value moderates the intention→use relationship: higher perceived value can paradoxically weaken translation of intention into actual use (likely due to raised expectations and unmet accessibility needs).
• Study 2 (experiment, n=231) shows participants prefer human-run services after a failure; GenAI-caused failures lower inferential judgement more than human-caused errors.
• Attitudes towards GenAI moderate responses to failures: more favourable attitudes reduce negative spillover from GenAI errors.
• Frequent GenAI use also moderates post-failure judgement: habitual users are more resilient and less likely to generalise failures.
• Methodologically robust approach: combines genetic algorithms, Bayesian regression, IPWRA and experimental manipulation to triangulate results.
• Practical recommendations include inclusive design, stepwise onboarding/training, transparent governance and error-handling that reassures users with disabilities.
• Authors situate findings in the social model of disability: structural barriers and prior exclusion shape both adoption and post-failure perceptions.

Why should I read this?

If you work on AI, accessibility, product design or policy, this paper is a neat shortcut — it reads like a playbook. It tells you which levers actually move the dial for people with functional disabilities (habit, trust, tailored promotions) and why overhyping GenAI can backfire if accessibility isn’t nailed. Also, it spells out simple, evidence-backed fixes for onboarding and failure messaging that cut churn and build trust.

Source

Source: https://onlinelibrary.wiley.com/doi/10.1002/mar.70028?af=R