Designing AI for Real Users -- Accessibility Gaps in Retail AI Front-End

Fuente: arXiv
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Auteurs principaux: Puri, Neha, Dixon, Tim
Format: Preprint
Publié: 2026
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author Puri, Neha
Dixon, Tim
author_facet Puri, Neha
Dixon, Tim
contents As AI becomes embedded in customer-facing systems, ethical scrutiny has largely focused on models, data, and governance. Far less attention has been paid to how AI is experienced through user-facing design. This commentary argues that many AI front-ends implicitly assume an 'ideal user body and mind', and that this becomes visible and ethically consequential when examined through the experiences of differently abled users. We explore this through retail AI front-ends for customer engagement - i.e., virtual assistants, virtual try-on systems, and hyper-personalised recommendations. Despite intuitive and inclusive framing, these systems embed interaction assumptions that marginalise users with vision, hearing, motor, cognitive, speech and sensory differences, as well as age-related variation in digital literacy and interaction norms. Drawing on practice-led insights, we argue that these failures persist not primarily due to technical limits, but due to the commercial, organisational, and procurement contexts in which AI front-ends are designed and deployed, where accessibility is rarely contractual. We propose front-end assurance as a practical complement to AI governance, aligning claims of intelligence and multimodality with the diversity of real users.
format Preprint
id arxiv_https___arxiv_org_abs_2603_28196
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Designing AI for Real Users -- Accessibility Gaps in Retail AI Front-End
Puri, Neha
Dixon, Tim
Human-Computer Interaction
Artificial Intelligence
As AI becomes embedded in customer-facing systems, ethical scrutiny has largely focused on models, data, and governance. Far less attention has been paid to how AI is experienced through user-facing design. This commentary argues that many AI front-ends implicitly assume an 'ideal user body and mind', and that this becomes visible and ethically consequential when examined through the experiences of differently abled users. We explore this through retail AI front-ends for customer engagement - i.e., virtual assistants, virtual try-on systems, and hyper-personalised recommendations. Despite intuitive and inclusive framing, these systems embed interaction assumptions that marginalise users with vision, hearing, motor, cognitive, speech and sensory differences, as well as age-related variation in digital literacy and interaction norms. Drawing on practice-led insights, we argue that these failures persist not primarily due to technical limits, but due to the commercial, organisational, and procurement contexts in which AI front-ends are designed and deployed, where accessibility is rarely contractual. We propose front-end assurance as a practical complement to AI governance, aligning claims of intelligence and multimodality with the diversity of real users.
title Designing AI for Real Users -- Accessibility Gaps in Retail AI Front-End
topic Human-Computer Interaction
Artificial Intelligence
url https://arxiv.org/abs/2603.28196