Tal-Chen Rabinowitch

dblp:80/736 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2010
0000-0003-0112-5350ORCID · verified

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2Human-computer interaction and ubiquitous computing · 2

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 · 67% Interaction techniques and input · 33%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Interaction techniques and input › gesture input
cooperative gestures
0.112010
Cooperative gestures: effective signaling for humanoid robots · HRI 2010
Human-robot interaction
anthropomorphism
0.112009
How anthropomorphism affects empathy toward robots · HRI 2009
Human-robot interaction › affective interaction
empathy toward robots
0.112009
How anthropomorphism affects empathy toward robots · HRI 2009

Methods — techniques the papers use, named apart from their topics

video-based experiment · 0.1experiment · 0.1
YearPublicationVenuePosition
2010 Cooperative gestures: effective signaling for humanoid robots
abstract
Cooperative gestures are a key aspect of human-human pro-social interaction. Thus, it is reasonable to expect that endowing humanoid robots with the ability to use such gestures when interacting with humans would be useful. However, while people are used to responding to such gestures expressed by other humans, it is unclear how they might react to a robot making them. To explore this topic, we conducted a within-subjects, video based laboratory experiment, measuring time to cooperate with a humanoid robot making interactional gestures. We manipulated the gesture type (beckon, give, shake hands), the gesture style (smooth, abrupt), and the gesture orientation (front, side). We also employed two measures of individual differences: negative attitudes toward robots (NARS) and human gesture decoding ability (DANVA2-POS). Our results show that people cooperate with abrupt gestures more quickly than smooth ones and front-oriented gestures more quickly than those made to the side, people's speed at decoding robot gestures is correlated with their ability to decode human gestures, and negative attitudes toward robots is strongly correlated with a decreased ability in decoding human gestures.
Laurel D. Riek, Tal-Chen Rabinowitch, Paul Bremner, Anthony G. Pipe, Mike Fraser 0001, Peter Robinson 0001
HRI2
2009 How anthropomorphism affects empathy toward robots
abstract
A long-standing question within the robotics community is about the degree of human-likeness robots ought to have when interacting with humans. We explore an unexamined aspect of this problem: how people empathize with robots along the anthropomorphic spectrum. We conducted an experiment that measured how people empathized with robots shown to be experiencing mistreatment by humans. Our results indicate that people empathize more strongly with more human-looking robots and less with mechanicallooking robots.
Laurel D. Riek, Tal-Chen Rabinowitch, Bhismadev Chakrabarti, Peter Robinson 0001
HRI2