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Retrieved on: 2024-03-25 19:21:18
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Summary
The article outlines the integration of artificial intelligence (AI) and machine learning (ML) in banking for tasks such as fraud detection, regulatory compliance, customer service, and market research. It highlights the efficiency gains and potential risks like data bias and transparency in AI-driven decision-making processes, emphasizing the need for responsible AI implementation to mitigate existential and ethical risks. The tags encapsulate the article's discussion on AI applications and concerns in banking and healthcare, touching upon cybernetics, AI philosophy, and regulatory aspects.
Article found on: rsmus.com
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