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John Voiklis

dblp:29/7029 · DBLP profile ↗
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6ranked-venue papers
4as first author
0since 2021 · last 2016
0000-0002-1590-9028ORCID · corroborated

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

Artificial intelligence and machine learning · 6 · 4 first-authorApplied, interdisciplinary, general and emerging computing · 4 · 4 first-authorHuman-computer interaction and ubiquitous computing · 3 · 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 · 100%

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

TopicWeightPapersLastEvidence papers
Human-robot interaction
moral judgment
0.212016
Which Robot Am I Thinking About?: The Impact of Action and Appearance on People's Evaluations of a Moral Robot · HRI 2016
Human-robot interaction
trust in robots
0.112016
Which Robot Am I Thinking About?: The Impact of Action and Appearance on People's Evaluations of a Moral Robot · HRI 2016
Human-robot interaction › social robot
social robot design
0.112015
Sacrifice One For the Good of Many?: People Apply Different Moral Norms to Human and Robot Agents · HRI 2015

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

user study · 0.2online experiment · 0.2
YearPublicationVenuePosition
2016 Which Robot Am I Thinking About?: The Impact of Action and Appearance on People's Evaluations of a Moral Robot
abstract
In three studies we found further evidence for a previously discovered Human-Robot (HR) asymmetry in moral judgments: that people blame robots more for inaction than action in a moral dilemma but blame humans more for action than inaction in the identical dilemma (where inaction allows four persons to die and action sacrifices one to save the four). Importantly, we found that people's representation of the “robot” making these moral decisions appears to be one of a mechanical robot. For when we manipulated the pictorial display of a verbally described robot, people showed the HR asymmetry only when making judgments about a mechanical-looking robot, not a humanoid robot. This is the first demonstration that robot appearance affects people's moral judgments about robots.
Bertram F. Malle, Matthias Scheutz, Jodi Forlizzi, John Voiklis
HRI4
2016 Moral judgments of human vs. robot agents
abstract
Robots will eventually perform norm-regulated roles in society (e.g. caregiving), but how will people apply moral norms and judgments to robots? By answering such questions, researchers can inform engineering decisions while also probing the scope of moral cognition. In previous work, we compared people's moral judgments about human and robot agents' behavior in moral dilemmas. We found that robots, compared with humans, were more commonly expected to sacrifice one person for the good of many, and they were blamed more than humans when they refrained from that decision. Thus, people seem to have somewhat different normative expectations of robots than of humans. In the current project we analyzed in detail the justifications people provide for three types of moral judgments (permissibility, wrongness, and blame) of robot and human agents. We found that people's moral judgments of both agents relied on the same conceptual and justificatory foundation: consequences and prohibitions undergirded wrongness judgments; attributions of mental agency undergirded blame judgments. For researchers, this means that people extend moral cognition to nonhuman agents. For designers, this means that robots with credible cognitive capacities will be considered moral agents but perhaps regulated by different moral norms.
John Voiklis, Corey J. Cusimano, Bertram F. Malle
RO-MAN1
2015 Sacrifice One For the Good of Many?: People Apply Different Moral Norms to Human and Robot Agents
abstract
Moral norms play an essential role in regulating human interaction. With the growing sophistication and proliferation of robots, it is important to understand how ordinary people apply moral norms to robot agents and make moral judgments about their behavior. We report the first comparison of people's moral judgments (of permissibility, wrongness, and blame) about human and robot agents. Two online experiments (total N = 316) found that robots, compared with human agents, were more strongly expected to take an action that sacrifices one person for the good of many (a "utilitarian" choice), and they were blamed more than their human counterparts when they did not make that choice. Though the utilitarian sacrifice was generally seen as permissible for human agents, they were blamed more for choosing this option than for doing nothing. These results provide a first step toward a new field of Moral HRI, which is well placed to help guide the design of social robots.
Bertram F. Malle, Matthias Scheutz, Thomas Arnold 0001, John Voiklis, Corey J. Cusimano
HRI4
2014 A Social-Conceptual Map of Moral Criticism
John Voiklis, Corey J. Cusimano, Bertram F. Malle
CogSci1
2011 The Social-Pragmatics of Category Learning
John Voiklis, James E. Corter
CogSci1
2011 Tort Reform: Negligence Explains Attributions of Intentionality for Negative Side Effects
John Voiklis, Jeffrey V. Nickerson
CogSci1