↓ Skip to main content

Attributing Agency to Automated Systems: Reflections on Human–Robot Collaborations and Responsibility-Loci

Overview of attention for article published in Science and Engineering Ethics, July 2017
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#33 of 978)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
7 news outlets
twitter
16 X users

Citations

dimensions_citation
127 Dimensions

Readers on

mendeley
183 Mendeley
Title
Attributing Agency to Automated Systems: Reflections on Human–Robot Collaborations and Responsibility-Loci
Published in
Science and Engineering Ethics, July 2017
DOI 10.1007/s11948-017-9943-x
Pubmed ID
Authors

Sven Nyholm

Abstract

Many ethicists writing about automated systems (e.g. self-driving cars and autonomous weapons systems) attribute agency to these systems. Not only that; they seemingly attribute an autonomous or independent form of agency to these machines. This leads some ethicists to worry about responsibility-gaps and retribution-gaps in cases where automated systems harm or kill human beings. In this paper, I consider what sorts of agency it makes sense to attribute to most current forms of automated systems, in particular automated cars and military robots. I argue that whereas it indeed makes sense to attribute different forms of fairly sophisticated agency to these machines, we ought not to regard them as acting on their own, independently of any human beings. Rather, the right way to understand the agency exercised by these machines is in terms of human-robot collaborations, where the humans involved initiate, supervise, and manage the agency of their robotic collaborators. This means, I argue, that there is much less room for justified worries about responsibility-gaps and retribution-gaps than many ethicists think.

X Demographics

X Demographics

The data shown below were collected from the profiles of 16 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 183 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 183 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 31 17%
Student > Master 25 14%
Student > Bachelor 17 9%
Researcher 16 9%
Lecturer 8 4%
Other 34 19%
Unknown 52 28%
Readers by discipline Count As %
Social Sciences 24 13%
Philosophy 20 11%
Engineering 17 9%
Business, Management and Accounting 13 7%
Computer Science 11 6%
Other 39 21%
Unknown 59 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 67. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 February 2024.
All research outputs
#657,397
of 25,830,005 outputs
Outputs from Science and Engineering Ethics
#33
of 978 outputs
Outputs of similar age
#13,515
of 326,496 outputs
Outputs of similar age from Science and Engineering Ethics
#1
of 32 outputs
Altmetric has tracked 25,830,005 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 978 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.0. This one has done particularly well, scoring higher than 96% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 326,496 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.