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Human–Robot Interactions and Affective Computing: The Ethical Implications

Authors: Devillers, Laurence;

Human–Robot Interactions and Affective Computing: The Ethical Implications

Abstract

AbstractThe field of social robotics is fast developing and will have wide implications especially within health care, where much progress has been made towards the development of “companion robots.” Such robots provide therapeutic or monitoring assistance to patients with a range of disabilities over a long timeframe. Preliminary results show that such robots may be particularly beneficial for use with individuals who suffer from neurodegenerative pathologies. Treatment can be accorded around the clock and with a level of patience rarely found among human healthcare workers. Several elements are requisite for the effective deployment of companion robots. They must be able to detect human emotions and in turn mimic human emotional reactions as well as having an outward appearance that corresponds to human expectations about their caregiving role. This chapter presents laboratory findings on AI-systems that enable robots to recognize specific emotions and to adapt their behavior accordingly. Emotional perception by humans (how language and gestures are interpreted by us to grasp the emotional states of others) is being studied as a guide to programming robots so they can simulate emotions in their interactions with humans.

Country
France
Keywords

[INFO.INFO-HC] Computer Science [cs]/Human-Computer Interaction [cs.HC]

  • BIP!
    Impact byBIP!
    selected citations
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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    25
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Top 10%
Top 10%
Top 10%
hybrid