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Main Authors: Rudaz, Damien, Carreras, Barbara Nino, Merlino, Sara, Due, Brian L., Brown, Barry
Format: Preprint
Published: 2026
Subjects:
Online Access:https://arxiv.org/abs/2602.05671
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author Rudaz, Damien
Carreras, Barbara Nino
Merlino, Sara
Due, Brian L.
Brown, Barry
author_facet Rudaz, Damien
Carreras, Barbara Nino
Merlino, Sara
Due, Brian L.
Brown, Barry
contents Does human-AI assistance unfold in the same way as human-human assistance? This research explores what can be learned from the expertise of blind individuals and sighted volunteers to inform the design of multimodal voice agents and address the enduring challenge of proactivity. Drawing on granular analysis of two representative fragments from a larger corpus, we contrast the practices co-produced by an experienced human remote sighted assistant and a blind participant-as they collaborate to find a stain on a blanket over the phone-with those achieved when the same participant worked with a multimodal voice agent on the same task, a few moments earlier. This comparison enables us to specify precisely which fundamental proactive practices the agent did not enact in situ. We conclude that, so long as multimodal voice agents cannot produce environmentally occasioned vision-based actions, they will lack a key resource relied upon by human remote sighted assistants.
format Preprint
id arxiv_https___arxiv_org_abs_2602_05671
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle (Computer) Vision in Action: Comparing Remote Sighted Assistance and a Multimodal Voice Agent in Inspection Sequences
Rudaz, Damien
Carreras, Barbara Nino
Merlino, Sara
Due, Brian L.
Brown, Barry
Human-Computer Interaction
Does human-AI assistance unfold in the same way as human-human assistance? This research explores what can be learned from the expertise of blind individuals and sighted volunteers to inform the design of multimodal voice agents and address the enduring challenge of proactivity. Drawing on granular analysis of two representative fragments from a larger corpus, we contrast the practices co-produced by an experienced human remote sighted assistant and a blind participant-as they collaborate to find a stain on a blanket over the phone-with those achieved when the same participant worked with a multimodal voice agent on the same task, a few moments earlier. This comparison enables us to specify precisely which fundamental proactive practices the agent did not enact in situ. We conclude that, so long as multimodal voice agents cannot produce environmentally occasioned vision-based actions, they will lack a key resource relied upon by human remote sighted assistants.
title (Computer) Vision in Action: Comparing Remote Sighted Assistance and a Multimodal Voice Agent in Inspection Sequences
topic Human-Computer Interaction
url https://arxiv.org/abs/2602.05671