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Bridging Social Sciences and AI for Understanding Child Behaviour

Author(s)
Kaya, Heysem; Hessels, Roy; Najafian, Maryam; Hanekamp, Sandra; Safavi, Saeid
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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.

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Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
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Abstract
Child behaviour is a topic of wide scientific interest among many different disciplines, including social and behavioural sciences and artificial intelligence (AI). In this workshop, we aimed to connect researchers from these fields to address topics such as the usage of AI to better understand and model child behavioural and developmental processes, challenges and opportunities for AI in large-scale child behaviour analysis and implementing explainable ML/AI on sensitive child data. The workshop served as a successful first step towards this goal and attracted contributions from different research disciplines on the analysis of child behaviour. This paper provides a summary of the activities of the workshop and the accepted papers and abstracts.
Description
ICMI ’20, October 25–29, 2020, Virtual Event, Netherlands
Date issued
2020-10-21
URI
https://hdl.handle.net/1721.1/158235
Department
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
Publisher
ACM|Proceedings of the 2020 International Conference on Multimodal Interaction
Citation
Kaya, Heysem, Hessels, Roy, Najafian, Maryam, Hanekamp, Sandra and Safavi, Saeid. 2020. "Bridging Social Sciences and AI for Understanding Child Behaviour."
Version: Final published version
ISBN
978-1-4503-7581-8

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