Demo Data from SIGIR 2026 / reviewers in the wild / expert
Lindsay J. Wilson
dblp:260/1307
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2020
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1Human-computer interaction and ubiquitous computing · 1
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 · 77% Collaborative and social computing · 23% |
Topics — the 1 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing
public engagement |
0.1 | 1 | 2020 | Robots in the Danger Zone: Exploring Public Perception through Engagement · HRI 2020 |
Methods — techniques the papers use, named apart from their topics
quiz-format survey · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2020 | Robots in the Danger Zone: Exploring Public Perception through EngagementabstractPublic perceptions of Robotics and Artificial Intelligence (RAI) are important in the acceptance, uptake, government regulation and research funding of this technology. Recent research has shown that the public's understanding of RAI can be negative or inaccurate. We believe effective public engagement can help ensure that public opinion is better informed. In this paper, we describe our first iteration of a high throughput in-person public engagement activity. We describe the use of a light touch quiz-format survey instrument to integrate in-the-wild research participation into the engagement, allowing us to probe both the effectiveness of our engagement strategy, and public perceptions of the future roles of robots and humans working in dangerous settings, such as in the off-shore energy sector. We critique our methods and share interesting results into generational differences within the public's view of the future of Robotics and AI in hazardous environments. These findings include that older peoples' views about the future of robots in hazardous environments were not swayed by exposure to our exhibit, while the views of younger people were affected by our exhibit, leading us to consider carefully in future how to more effectively engage with and inform older people. David A. Robb 0001, Muneeb Imtiaz Ahmad, Carlo Tiseo, Simona Aracri, Alistair McConnell, Vincent Pagé, Christian Dondrup, Francisco Javier Chiyah Garcia, Hai-Nguyen Nguyen, Èric Pairet, Paola Ardón Ramirez, Tushar Semwal, Hazel M. Taylor, Lindsay J. Wilson, David Lane, Helen Hastie, Katrin S. Lohan |
HRI | 14 |