Demo Data from EDBT 2026 / reviewers in the wild / expert
Gabe Clapper
dblp:319/3460
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-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-AI interaction · 56% Usability and user experience research · 44% |
Topics — the 1 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction
responsible AI |
0.2 | 1 | 2022 | "Because AI is 100% right and safe": User Attitudes and Sources of AI Authority in India · CHI 2022 |
Methods — techniques the papers use, named apart from their topics
survey · 0.6interviews · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | "Because AI is 100% right and safe": User Attitudes and Sources of AI Authority in IndiaabstractMost prior work on human-AI interaction is set in communities that indicate skepticism towards AI, but we know less about contexts where AI is viewed as aspirational. We investigated the perceptions around AI systems by drawing upon 32 interviews and 459 survey respondents in India. Not only do Indian users accept AI decisions (79.2% respondents indicate acceptance), we find a case of AI authority—AI has a legitimized power to influence human actions, without requiring adequate evidence about the capabilities of the system. AI authority manifested into four user attitudes of vulnerability: faith, forgiveness, self-blame, and gratitude, pointing to higher tolerance for system misfires, and introducing potential for irreversible individual and societal harm. We urgently call for calibrating AI authority, reconsidering success metrics and responsible AI approaches and present methodological suggestions for research and deployments in India. Shivani Kapania, Oliver Siy, Gabe Clapper, Nithya Sambasivan |
CHI | 3 |