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“Hit the Robot on the Head With This Mallet” – Making a Case for Including More Open Questions in HRI Research

Overview of attention for article published in Frontiers in Robotics and AI, February 2021
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

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16 X users

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5 Dimensions

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36 Mendeley
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Title
“Hit the Robot on the Head With This Mallet” – Making a Case for Including More Open Questions in HRI Research
Published in
Frontiers in Robotics and AI, February 2021
DOI 10.3389/frobt.2021.603510
Pubmed ID
Authors

Katie A. Riddoch, Emily. S. Cross

Abstract

Researchers continue to devise creative ways to explore the extent to which people perceive robots as social agents, as opposed to objects. One such approach involves asking participants to inflict 'harm' on a robot. Researchers are interested in the length of time between the experimenter issuing the instruction and the participant complying, and propose that relatively long periods of hesitation might reflect empathy for the robot, and perhaps even attribution of human-like qualities, such as agency and sentience. In a recent experiment, we adapted the so-called 'hesitance to hit' paradigm, in which participants were instructed to hit a humanoid robot on the head with a mallet. After standing up to do so (signaling intent to hit the robot), participants were stopped, and then took part in a semi-structured interview to probe their thoughts and feelings during the period of hesitation. Thematic analysis of the responses indicate that hesitation not only reflects perceived socialness, but also other factors including (but not limited to) concerns about cost, mallet disbelief, processing of the task instruction, and the influence of authority. The open-ended, free responses participants provided also offer rich insights into individual differences with regards to anthropomorphism, perceived power imbalances, and feelings of connection toward the robot. In addition to aiding understanding of this measurement technique and related topics regarding socialness attribution to robots, we argue that greater use of open questions can lead to exciting new research questions and interdisciplinary collaborations in the domain of social robotics.

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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.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 11 31%
Student > Ph. D. Student 7 19%
Student > Bachelor 2 6%
Researcher 2 6%
Professor 1 3%
Other 3 8%
Unknown 10 28%
Readers by discipline Count As %
Unspecified 11 31%
Psychology 3 8%
Business, Management and Accounting 2 6%
Agricultural and Biological Sciences 1 3%
Sports and Recreations 1 3%
Other 5 14%
Unknown 13 36%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 16 July 2021.
All research outputs
#3,170,507
of 25,295,968 outputs
Outputs from Frontiers in Robotics and AI
#199
of 1,753 outputs
Outputs of similar age
#77,566
of 427,498 outputs
Outputs of similar age from Frontiers in Robotics and AI
#6
of 72 outputs
Altmetric has tracked 25,295,968 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,753 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.7. This one has done well, scoring higher than 88% 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 427,498 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 72 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 93% of its contemporaries.