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The increasing use of artificial intelligence (AI) in various sectors, including hiring, criminal justice, and healthcare, has sparked concerns about fairness and bias. While AI systems may seem less biased than humans, research shows that they can perpetuate and amplify existing societal biases. To address these complex challenges, experts from multiple fields must collaborate to develop technical improvements, operational practices, and ethical standards to minimize bias in both AI systems and human decision-making.The article highlights areas where algorithms can help reduce disparities caused by human biases, such as in hiring practices, and where more human oversight is necessary to critically analyze the biases that can become ingrained in AI systems. The article also provides an overview of ongoing research across disciplines to address bias in AI and offers emerging resources and practical approaches for those interested in delving deeper into the issue.The article concludes by outlining pragmatic steps forward and the work needed to ensure that AI lives up to its potential. By prioritizing collaboration, ethical standards, and continuous monitoring, we can mitigate bias in AI systems and promote fairness in decision-making processes.
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Criminal Justice
artificial intelligence
sparked concerns
including hiring
systems
bias
ethical standards
Human
biases
hiring practices
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