Ethical Considerations in Artificial Intelligence: Addressing Bias and Fairness in Algorithmic Decision-Making

Abstract

The expanding use of artificial intelligence (AI) in decision-making across a range of industries has given rise to serious ethical questions about prejudice and justice. This study looks at the moral ramifications of using AI algorithms in decision-making and looks at methods to combat prejudice and advance justice. The study investigates the underlying causes of prejudice in AI systems, the effects of biased algorithms on people and society, and the moral obligations of stakeholders in reducing bias, drawing on prior research and real-world examples. The study also addresses new frameworks and strategies for advancing justice in algorithmic decision-making, emphasizing the value of openness, responsibility, and diversity in dataset gathering and algorithm development. The study concludes with suggestions for further investigation and legislative actions to guarantee that AI systems respect moral standards and advance justice and equity in the processes of making decisions. Keywords Ethical considerations, Artificial intelligence, Bias, Fairness, Algorithmic decision-making, Ethical implications, Ethical responsibilities, Stakeholders, Bias in AI systems, Impact of biased algorithms, Strategies for addressing bias, Promoting fairness, Algorithmic transparency.