Demo Data from EDBT 2026 / reviewers in the wild / expert
Serhiy Kandul
dblp:319/3513
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2023
0000-0001-8175-2252ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Human-computer interaction and ubiquitous computing · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 first-author · 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 · 100% |
Topics — the 4 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction
reliance on AI |
0.6 | 1 | 2022 | Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making · CHI 2022 |
Human-AI interaction › responsible AI
responsibility attribution |
0.6 | 1 | 2022 | Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making · CHI 2022 |
Human-AI interaction
trust in AI |
0.6 | 1 | 2022 | Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making · CHI 2022 |
Human-AI interaction › human decision-making
moral decision-making |
0.2 | 1 | 2022 | Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision Making · CHI 2022 |
Methods — techniques the papers use, named apart from their topics
vignette study · 0.6survey · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2023 | Human control redressed: Comparing AI and human predictability in a real-effort task
Serhiy Kandul, Vincent Micheli, Juliane Beck, Thomas Burri, François Fleuret, Markus Kneer, Markus Christen |
CogSci | 1 |
| 2022 | Capable but Amoral? Comparing AI and Human Expert Collaboration in Ethical Decision MakingabstractWhile artificial intelligence (AI) is increasingly applied for decision-making processes, ethical decisions pose challenges for AI applications. Given that humans cannot always agree on the right thing to do, how would ethical decision-making by AI systems be perceived and how would responsibility be ascribed in human-AI collaboration? In this study, we investigate how the expert type (human vs. AI) and level of expert autonomy (adviser vs. decider) influence trust, perceived responsibility, and reliance. We find that participants consider humans to be more morally trustworthy but less capable than their AI equivalent. This shows in participants’ reliance on AI: AI recommendations and decisions are accepted more often than the human expert’s. However, AI team experts are perceived to be less responsible than humans, while programmers and sellers of AI systems are deemed partially responsible instead. Suzanne Tolmeijer, Markus Christen, Serhiy Kandul, Markus Kneer, Abraham Bernstein |
CHI | 3 |