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Keys K. Rigual

dblp:429/0516 · DBLP profile ↗
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1ranked-venue papers
0as first author
1since 2021 · last 2026
0009-0005-3806-6827ORCID · reported

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Human-computer interaction and pervasive computing
1 paper
Human-robot interaction · 50% Accessibility and assistive technology · 38% Collaborative and social computing · 12%

Topics — the 4 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Human-robot interaction › social robot
companion robots
1.012026
Not the Intended User: Queer Perspectives on Identity, Risk, and Trust in Robot Companions · HRI 2026
Accessibility and assistive technology
inclusive design
1.012026
Not the Intended User: Queer Perspectives on Identity, Risk, and Trust in Robot Companions · HRI 2026
Collaborative and social computing › vulnerable populations
marginalized communities
0.312026
Not the Intended User: Queer Perspectives on Identity, Risk, and Trust in Robot Companions · HRI 2026
Human-robot interaction
trust in robots
0.312026
Not the Intended User: Queer Perspectives on Identity, Risk, and Trust in Robot Companions · HRI 2026

Methods — techniques the papers use, named apart from their topics

survey · 1.0participatory design · 1.0mixed-methods study · 1.0
YearPublicationVenuePosition
2026 Not the Intended User: Queer Perspectives on Identity, Risk, and Trust in Robot Companions
abstract
Robot companions often default to cisnormative and heteronormative assumptions, undermining trust and inclusion for LGBTQIA+ (queer) communities. Although inclusivity is widely discussed in HRI, empirical, community-led insights into queer needs and risks remain limited. We address this gap through a mixed-methods study of how queer individuals envision affirming and trustworthy robot companions, combining an online survey of community priorities with participatory design workshops exploring lived experiences and design tensions. Although many participants felt they were not the "intended user" of current technologies, they outlined clear priorities for future robot companions, including accurate handling of names and pronouns, robust privacy and data safeguards, clear and bounded utilitarian roles, and user-controlled adaptability, while identifying risks such as misgendering, surveillance, stereotype reinforcement, and unhealthy dependence. We translate these findings into justice-oriented design requirements for robot companions serving queer and other marginalized communities.
Kaylee Nam, Jackie Yee, Raitah A. Jinnat, Keys K. Rigual, Alexandria Thylane, Raj Korpan
HRI4