End-User Development for Artificial Intelligence: A Systematic Literature Review

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Abstract

In recent years, Artificial Intelligence has become more and more relevant in our society. Creating AI systems is almost always the prerogative of IT and AI experts. However, users may need to create intelligent solutions tailored to their specific needs. In this way, AI systems can be enhanced if new approaches are devised to allow non-technical users to be directly involved in the definition and personalization of AI technologies. End-User Development (EUD) can provide a solution to these problems, allowing people to create, customize, or adapt AI-based systems to their own needs. This paper presents a systematic literature review that aims to shed the light on the current landscape of EUD for AI systems, i.e., how users, even without skills in AI and/or programming, can customize the AI behavior to their needs. This study also discusses the current challenges of EUD for AI, the potential benefits, and the future implications of integrating EUD into the overall AI development process.

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Esposito, A., Calvano, M., Curci, A., Desolda, G., Lanzilotti, R., Lorusso, C., & Piccinno, A. (2023). End-User Development for Artificial Intelligence: A Systematic Literature Review. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 13917 LNCS, pp. 19–34). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-34433-6_2

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