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Adaptive and Adaptable Systems: Differentiating and Integrating AI and EUD

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End-User Development (IS-EUD 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13917))

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Abstract

The framework presented in the paper identifies the promises and pitfalls of Artificial Intelligence (AI) and End-User Development (EUD) approaches by focusing on two basic system components: (1) adaptive systems (grounded in AI) that change their behavior automatically driven by context-aware mechanisms including models of their users and specific task contexts, and (2) adaptable systems (grounded in EUD) that can be adjusted, modified, and extended by their users in order to capture unforeseen and important emergent user needs and aspects of problems. Grounded in an analysis of design trade-offs between the two approaches, arguments, and examples for creating a desirable symbiosis between adaptive and adaptable systems are described and design guidelines for future socio-technical environments are explored contributing to the development of theoretical concepts for the future of EUD.

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Acknowledgments

The author wishes to thank Daniela Fogli, Anders Mørch, Antonio Piccinno, and the three reviewers who provided insightful comments that greatly improved earlier versions of this article.

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Authors and Affiliations

  1. Center for Life Long Learning & Design (L3D), Department of Computer Science and Institute of Cognitive Science, University of Colorado, Boulder, USA

    Gerhard Fischer

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  1. Gerhard Fischer
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Correspondence to Gerhard Fischer .

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Editors and Affiliations

  1. University of Cagliari, Cagliari, Italy

    Lucio Davide Spano

  2. LMU Munich, Munich, Germany

    Albrecht Schmidt

  3. ISTI-CNR, Pisa, Italy

    Carmen Santoro

  4. University of Glasgow, Glasgow, UK

    Simone Stumpf

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Fischer, G. (2023). Adaptive and Adaptable Systems: Differentiating and Integrating AI and EUD. In: Spano, L.D., Schmidt, A., Santoro, C., Stumpf, S. (eds) End-User Development. IS-EUD 2023. Lecture Notes in Computer Science, vol 13917. Springer, Cham. https://doi.org/10.1007/978-3-031-34433-6_1

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  • DOI: https://doi.org/10.1007/978-3-031-34433-6_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-34432-9

  • Online ISBN: 978-3-031-34433-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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