International University of Travnik , Travnik , Bosnia and Herzegovina
One of the major issues that can have far-reaching consequences on society is bias in the development of AI algorithms. Algorithms that cannot guarantee fairness result in discrimination and inequality, and this is very evident in sectors such as healthcare, the legal system, and finance. This paper discusses the different biases arising in AI systems, their causes, impacts, and possible mitigation strategies. In the interest of fair application of AI technology, we focus on ethical dilemmas and strategies that include more transparency and diversity in data and algorithms.
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