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2024 | OriginalPaper | Buchkapitel

Fairness and Explainability for Enabling Trust in AI Systems

verfasst von : Dimitris Sacharidis

Erschienen in: A Human-Centered Perspective of Intelligent Personalized Environments and Systems

Verlag: Springer Nature Switzerland

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Abstract

This chapter discusses the ethical complications and challenges arising from the use of AI systems in our everyday lives. It outlines recent and upcoming regulations and policies regarding the use of AI systems, and dives into the topics of explainability and fairness. We argue that trustworthiness has at its heart explainability, and thus we present ideas and techniques aimed at making AI systems more understandable and ultimately more trustworthy for humans. Moreover, we discuss the topic of algorithmic fairness and the requirement that AI systems are free from biases and do not discriminate against individuals on the basis of some protected attributes. In all cases, we present a brief summary of the most important concepts and results in the literature. As a conclusion, we present some ideas for future research and sketch open challenges in the field.

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Vorheriges Kapitel The Role of Human-Centered AI in User Modeling, Adaptation, and Personalization—Models, Frameworks, and Paradigms

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Titel: Fairness and Explainability for Enabling Trust in AI Systems
verfasst von: Dimitris Sacharidis
Verlag: Springer Nature Switzerland
Buch: A Human-Centered Perspective of Intelligent Personalized Environments and Systems
Print ISBN: 978-3-031-55108-6

Electronic ISBN: 978-3-031-55109-3

Copyright-Jahr: 2024
DOI: https://doi.org/10.1007/978-3-031-55109-3_3

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