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Deceptive Dreams: Nudging for Better Sleep

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Deceptive AI (DeceptECAI 2020, DeceptAI 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1296))

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Abstract

Research on persuasive technologies for promoting health behaviours has been surging in recent years, but considerably few studies are about sleep. As an approach for persuasion, the nudge theory provides libertarian paternalistic means to influence sleep-related choices and behaviours. However, even though the freedom of choice is typically preserved in nudging, deceptive experiences arise in certain situations. The current study aims to understand the persuasive properties and deceptive characteristics of different methods of nudging used in technologies that encourage or facilitate better sleep hygiene. This paper introduces the preliminary results of an ongoing study and two types of deceptions within the framework of nudging: self-deception by cognitive biases and deception by non-transparency.

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Acknowledgments

Special thanks to Loïs Vanhée, Esteban Guerrero Rosero and Timotheus Kampik for providing guidance and support.

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Authors and Affiliations

  1. Umeå University, 901 87, Umeå, Sweden

    Hung-Chiao Chen

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  1. Hung-Chiao Chen
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Editor information

Editors and Affiliations

  1. Inria Sophia Antipolis-Méditerranée Research Centre, Valbonne, France

    Stefan Sarkadi

  2. United States Naval Research Laboratory, Washington D.C., WA, USA

    Benjamin Wright

  3. University of Melbourne, Melbourne, VIC, Australia

    Peta Masters

  4. King's College London, London, UK

    Peter McBurney

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Chen, HC. (2021). Deceptive Dreams: Nudging for Better Sleep. In: Sarkadi, S., Wright, B., Masters, P., McBurney, P. (eds) Deceptive AI. DeceptECAI DeceptAI 2020 2021. Communications in Computer and Information Science, vol 1296. Springer, Cham. https://doi.org/10.1007/978-3-030-91779-1_3

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  • DOI: https://doi.org/10.1007/978-3-030-91779-1_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-91778-4

  • Online ISBN: 978-3-030-91779-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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