Bias and Fairness in AI Technology

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Author(s): Muhsina (PES University, India)and Zidan Kachhi (PES University, India)
Copyright: 2024
Pages: 15
Source title: Exploring the Ethical Implications of Generative AI
Source Author(s)/Editor(s): Aftab Ara (University of Hail, Saudi Arabia)and Affreen Ara (Department of Computer Science, Christ College, Bangalore, India)
DOI: 10.4018/979-8-3693-1565-1.ch003

Keywords: Artificial Intelligence / Business & Management / Cyber Ethics / Information Science Reference

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Abstract

This chapter's objective is to provide an overview of how artificial intelligence (AI) has become an essential part of human life. It explains the sources of bias and its types in AI technology. With the help of previous studies, the chapter elucidates the strategies that can be used to avoid decision-making as a source of bias in AI technology. It also talks about the importance of understanding how human bias can also cause AI systems to exhibit bias towards certain groups. Unfairness in AI is also one of the most common sources of biassed data, and it's explained with strategies for detecting and addressing unfairness. The chapter also covers the need for transparency in AI technology along with ethical considerations, as transparency in AI is essential to ensuring that AI systems operate in adherence to ethical standards.

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