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Rebecca Davidson

dblp:237/8440 · DBLP profile ↗
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1ranked-venue papers
1as first author
0since 2021 · last 2019
—ORCID · none

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

Artificial intelligence and machine learning · 1 · 1 first-authorHuman-computer interaction and ubiquitous computing · 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
1 paper
Human-robot interaction · 100%

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

TopicWeightPapersLastEvidence papers
Human-robot interaction
child-robot interaction
0.412019
Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and Learning · HRI 2019
Human-robot interaction
moral judgment
0.412019
Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and Learning · HRI 2019
Human-robot interaction › robot ethics
robot abuse
0.112019
Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and Learning · HRI 2019

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

user study · 0.4
YearPublicationVenuePosition
2019 Children's Judgments of Anti-Social Behaviour Towards a Robot: Liking and Learning
abstract
Children have been documented extending prosocial ideals and moral worth towards robots. However, there is also emerging evidence that children will behave violently towards robots. Given expectations that robots will soon become common fixtures in classrooms, and that children can behave violently towards robots, it is important that we identify how others might appraise the victims (robots) and perpetrators (children) of these scenarios. It is critical that we understand whether children will think it is okay to behave immorally towards a robot, or if they will be deterred by these acts of abuse. Additionally, we must determine how this will influence children's learning decisions. The proposed study aims to address these questions by creating a novel paradigm where children are asked to rate robots and humans who have been involved in a transgression, where the human behaves anti-socially towards the robot. This study will also aim to understand how these appraisals will influence childrens learning decisions in a forced choice, selective learning task.
Rebecca Davidson, Kristyn Sommer, Mark Nielsen
HRI1