EDBT 2026 Demo / reviewers in the wild / expert
Jürgen Brandstetter
dblp:153/7474
· DBLP profile ↗
3ranked-venue papers
2as first author
0since 2021 · last 2017
0000-0001-7489-1844ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Artificial intelligence and machine learning · 3 · 2 first-authorHuman-computer interaction and ubiquitous computing · 2 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-author
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 |
Human-robot interaction · 79% Human-AI interaction · 21% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction › human decision-making
moral decision-making |
0.1 | 1 | 2016 | Can a Robot Bribe a Human?: The Measurement of the Negative Side of Reciprocity in Human Robot Interaction · HRI 2016 |
Human-robot interaction › robot design
robot behavior design |
0.1 | 1 | 2016 | Can a Robot Bribe a Human?: The Measurement of the Negative Side of Reciprocity in Human Robot Interaction · HRI 2016 |
Methods — techniques the papers use, named apart from their topics
user study · 0.3rock-paper-scissors game · 0.2direct and indirect speech · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2017 | Persistent Lexical Entrainment in HRIabstractIn this study, we set out to ask three questions. First, does lexical entrainment with a robot interlocutor persist after an interaction? Second, how does the influence of social robots on humans compare with the influence of humans on each other? Finally, what role is played by personality traits in lexical entrainment to robots, and how does this compare with the role of personality in entrainment to other humans? Our experiment shows that first, robots can indeed prompt lexical entrainment that persists after an interaction is over. This finding is interesting since it demonstrates that speakers can be linguistically influenced by a robot, in a way that is not merely motivated by a desire to be understood. Second, we find similarities between lexical entrainment to the robot peer and lexical entrainment to a human peer, although the effects are stronger when the peer is human. Third, we find that whether the peer is a robot or a human, similar personality traits contribute to lexical entrainment. In both peer conditions, participants who score higher on ``Openness to experience" are more likely to adopt less conventional terminology. Jürgen Brandstetter, Clay Beckner, Eduardo Benítez Sandoval, Christoph Bartneck |
HRI | 1 |
| 2016 | Can a Robot Bribe a Human?: The Measurement of the Negative Side of Reciprocity in Human Robot InteractionabstractReciprocity is a cornerstone of human relationships and apparently it also appears in human-robot interaction independently of the context. It is expected that reciprocity will play a principal role in HRI in the future. The negative side of reciprocal phenomena has not been entirely explored in human-robot interaction. For instance, a reciprocal act such as bribery between Humans and robots is a very novel area. In this paper, we try to evaluate the questions: Can a robot bribe a human? To what extent is a robot bribing a human affect his/her reciprocal response? We performed an experiment using the Rock, Paper, Scissors game (RPSG). The robot bribes the participant by losing intentionally in certain rounds to obtain his/her favour later, and through using direct and indirect speech in certain rounds. The participants could obtain between 20%- 25% more money when the robot bribed them than in the control condition. The robot also used either direct or indirect speech requesting a favour in a second task. Our results show that the bribing robot received significantly less reciprocation than in the control condition regardless of whether the request was couched in direct or indirect speech. However there is a significant interaction effect between the bribe and speech conditions. Moreover, just three of sixty participants reported the robot-bribe in an interview as a malfunction, though they did not mention any moral judgement about its behaviour. Further, just 10% of the participants reported the bribe in the online questionnaire. We consider that our experiment makes an early contribution to continue the exploration of morally ambiguous and controversial reciprocal situations in HRI. Robot designers should consider the reciprocal human response towards robots in different contexts including bribery scenarios. Additionally our study could be used in guidelines for robot behavioural design to model future HRI interactions in terms of moral decisions. Eduardo Benítez Sandoval, Jürgen Brandstetter, Christoph Bartneck |
HRI | 2 |
| 2014 | A peer pressure experiment: Recreation of the Asch conformity experiment with robotsabstractThe question put forward in this paper is whether robots can create conformity by means of group pressure. We recreate and expand on a classic social psychology experiment by Solomon Asch, so as to explore three main dimensions. First, we wanted to know whether robots can prompt conformity in human subjects, and whether there is a significant difference between the degree to which individuals conform to a group of robots as opposed to a group of humans. Secondly we ask whether group pressure (from human or robot peers) can exert influence in verbal judgments, analogously to the influence on visual judgments that is known from previous research [3], [2]. Thirdly, we investigate whether the level of conformity differs between an ambiguous situation and a non-ambiguous situation. Our results show that in both visual and verbal tasks, participants exhibit conformity with human peers, but not with robot peers. The social influence of robot peers is not a significant predictor of verbal or visual judgments in our tasks. Furthermore, the level of conformity is significantly higher in an ambiguous (unclear) situation. Jürgen Brandstetter, Péter Rácz, Clay Beckner, Eduardo Benítez Sandoval, Jennifer Hay, Christoph Bartneck |
IROS | 1 |