Demo Data from SIGIR 2026 / reviewers in the wild / expert
Steve Loughnan
dblp:136/8145
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0002-4737-5120ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 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
2 papers |
Collaborative and social computing · 49% Usability and user experience research · 43% Interaction techniques and input · 9% |
Topics — the 3 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › social cognition
mind perception |
0.9 | 1 | 2025 | Robots, Chatbots, Self-Driving Cars: Perceptions of Mind and Morality Across Artificial Intelligences · CHI 2025 |
Usability and user experience research
user perception |
0.9 | 1 | 2025 | Robots, Chatbots, Self-Driving Cars: Perceptions of Mind and Morality Across Artificial Intelligences · CHI 2025 |
Collaborative and social computing
audience experience |
0.2 | 1 | 2014 | Audience experience in social videogaming: effects of turn expectation and game physicality · CHI 2014 |
Methods — techniques the papers use, named apart from their topics
online study · 0.9controlled study · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Robots, Chatbots, Self-Driving Cars: Perceptions of Mind and Morality Across Artificial IntelligencesabstractAI systems have rapidly advanced, diversified, and proliferated, but our knowledge of people's perceptions of mind and morality in them is limited, despite its importance for outcomes such as whether people trust AIs and how they assign responsibility for AI-caused harms. In a preregistered online study, 975 participants rated 26 AI and non-AI entities. Overall, AIs were perceived to have low-to-moderate agency (e.g., planning, acting), between inanimate objects and ants, and low experience (e.g., sensing, feeling). For example, ChatGPT was rated only as capable of feeling pleasure and pain as a rock. The analogous moral faculties, moral agency (doing right or wrong) and moral patiency (being treated rightly or wrongly) were higher and more varied, particularly moral agency: The highest-rated AI, a Tesla Full Self-Driving car, was rated as morally responsible for harm as a chimpanzee. We discuss how design choices can help manage perceptions, particularly in high-stakes moral contexts. Ali Ladak, Matti Wilks, Steve Loughnan, Jacy Reese Anthis |
CHI | 3 |
| 2014 | Audience experience in social videogaming: effects of turn expectation and game physicalityabstractVideogames are often played socially with both co-players and audiences. Audience members' experiences are not well understood, nor are the factors of videogaming sessions that influence their experience. We conducted a study to examine the effects of game physicality and turn anticipation on audience members' experiences in social videogaming sessions. Pairs of participants played games under three conditions of physicality (controller-based, Wii, and Kinect) and their expectation of turn-taking was manipulated. Their enjoyment, game engagement, social engagement and sense of participation were measured. We found that the introduction of turn-taking into the session had positive effects for audience members -- both anticipated and residual play effects -- and that Kinect gameplay resulted in a more enjoyable experience for audience members. We argue that audience members' experience changes as they become more active within a session, and suggest there are design opportunities between purely active 'players' and passive 'audience members'. John Downs, Frank Vetere, Steve Howard, Steve Loughnan, Wally Smith |
CHI | 4 |