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Cooperating with machines

Overview of attention for article published in Nature Communications, January 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
19 news outlets
blogs
10 blogs
twitter
415 tweeters
facebook
4 Facebook pages
wikipedia
3 Wikipedia pages
googleplus
3 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
98 Dimensions

Readers on

mendeley
403 Mendeley
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Title
Cooperating with machines
Published in
Nature Communications, January 2018
DOI 10.1038/s41467-017-02597-8
Pubmed ID
Authors

Jacob W. Crandall, Mayada Oudah, Tennom, Fatimah Ishowo-Oloko, Sherief Abdallah, Jean-François Bonnefon, Manuel Cebrian, Azim Shariff, Michael A. Goodrich, Iyad Rahwan

Abstract

Since Alan Turing envisioned artificial intelligence, technical progress has often been measured by the ability to defeat humans in zero-sum encounters (e.g., Chess, Poker, or Go). Less attention has been given to scenarios in which human-machine cooperation is beneficial but non-trivial, such as scenarios in which human and machine preferences are neither fully aligned nor fully in conflict. Cooperation does not require sheer computational power, but instead is facilitated by intuition, cultural norms, emotions, signals, and pre-evolved dispositions. Here, we develop an algorithm that combines a state-of-the-art reinforcement-learning algorithm with mechanisms for signaling. We show that this algorithm can cooperate with people and other algorithms at levels that rival human cooperation in a variety of two-player repeated stochastic games. These results indicate that general human-machine cooperation is achievable using a non-trivial, but ultimately simple, set of algorithmic mechanisms.

Twitter Demographics

The data shown below were collected from the profiles of 415 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 403 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Luxembourg 1 <1%
Unknown 399 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 104 26%
Student > Master 58 14%
Researcher 55 14%
Student > Bachelor 37 9%
Student > Doctoral Student 21 5%
Other 64 16%
Unknown 64 16%
Readers by discipline Count As %
Computer Science 113 28%
Engineering 39 10%
Psychology 36 9%
Business, Management and Accounting 21 5%
Social Sciences 19 5%
Other 87 22%
Unknown 88 22%

Attention Score in Context

This research output has an Altmetric Attention Score of 476. 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 08 December 2022.
All research outputs
#46,074
of 22,985,065 outputs
Outputs from Nature Communications
#705
of 47,309 outputs
Outputs of similar age
#1,268
of 441,906 outputs
Outputs of similar age from Nature Communications
#26
of 1,232 outputs
Altmetric has tracked 22,985,065 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 47,309 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.9. This one has done particularly well, scoring higher than 98% 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 441,906 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 1,232 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 97% of its contemporaries.