Navigating Social Trust in the AI Era
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As artificial intelligence (AI) is integrated in everyday life, from decision-making algorithms in healthcare and finance to generative tools in media and education, the question of social trust emerges. Trust in AI systems extends beyond technical performance, encompassing ethical design, transparency, accountability, and the perceived intentions of those utilizing the technology. In this evolving landscape, individuals and societies must grapple with concerns around data privacy, algorithmic bias, and the erosion of human agency. Navigating social trust in the AI era requires an approach tha...
As artificial intelligence (AI) is integrated in everyday life, from decision-making algorithms in healthcare and finance to generative tools in media and education, the question of social trust emerges. Trust in AI systems extends beyond technical performance, encompassing ethical design, transparency, accountability, and the perceived intentions of those utilizing the technology. In this evolving landscape, individuals and societies must grapple with concerns around data privacy, algorithmic bias, and the erosion of human agency. Navigating social trust in the AI era requires an approach that combines responsible innovation, inclusive governance, and public engagement to ensure AI serves public interest rather than worsening existing inequalities. Navigating Social Trust in the AI Era explores the ethical, legal, and social implications of AI, with an emphasis on privacy issues and regulatory developments. It examines the intersection of new AI technologies, personal data, social trust, and governance structures, while providing both theoretical perspectives and practical examples. This book covers topics such as data science, ethics and law, and accounting and finance, and is a useful resource for sociologists, computer engineers, policymakers, academicians, researchers, and data scientists.
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