The social dilemma of autonomous vehicles

Overview of attention for article published in Science, June 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#9 of 39,533)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Readers on

mendeley
61 Mendeley
Title
The social dilemma of autonomous vehicles
Published in
Science, June 2016
DOI 10.1126/science.aaf2654
Pubmed ID
Authors

Jean-François Bonnefon, Azim Shariff, Iyad Rahwan

Abstract

Autonomous vehicles (AVs) should reduce traffic accidents, but they will sometimes have to choose between two evils, such as running over pedestrians or sacrificing themselves and their passenger to save the pedestrians. Defining the algorithms that will help AVs make these moral decisions is a formidable challenge. We found that participants in six Amazon Mechanical Turk studies approved of utilitarian AVs (that is, AVs that sacrifice their passengers for the greater good) and would like others to buy them, but they would themselves prefer to ride in AVs that protect their passengers at all costs. The study participants disapprove of enforcing utilitarian regulations for AVs and would be less willing to buy such an AV. Accordingly, regulating for utilitarian algorithms may paradoxically increase casualties by postponing the adoption of a safer technology.

Twitter Demographics

The data shown below were collected from the profiles of 993 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 2%
Australia 1 2%
United Kingdom 1 2%
Japan 1 2%
United States 1 2%
Canada 1 2%
Unknown 55 90%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 18 30%
Researcher 12 20%
Student > Master 11 18%
Student > Ph. D. Student 9 15%
Professor 5 8%
Other 6 10%
Readers by discipline Count As %
Engineering 14 23%
Social Sciences 9 15%
Business, Management and Accounting 8 13%
Computer Science 8 13%
Psychology 6 10%
Other 16 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 2453. 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 21 April 2017.
All research outputs
#132
of 7,596,418 outputs
Outputs from Science
#9
of 39,533 outputs
Outputs of similar age
#4
of 239,504 outputs
Outputs of similar age from Science
#1
of 704 outputs
Altmetric has tracked 7,596,418 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 39,533 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 31.4. This one has done particularly well, scoring higher than 99% 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 239,504 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 99% of its contemporaries.
We're also able to compare this research output to 704 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 99% of its contemporaries.