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Prediction Machines delves into the transformative effects of artificial intelligence (AI) on both business and society. The authors present a compelling argument that AI should be perceived primarily as a means to lower the costs associated with making predictions. This perspective challenges traditional views on AI, shifting the focus towards its economic implications and practical applications.
Through a rigorous analysis, the authors outline how organisations can leverage the capabilities of AI to enhance decision-making processes and develop robust strategies. They explore various dimensions of AI, including:
Central to the book is the theme of adaptation in a world increasingly dominated by AI. The authors provide valuable guidance for stakeholders across various sectors, including CEOs, managers, policymakers, investors, and entrepreneurs. By framing AI in economic terms, they elucidate the importance of prediction in driving innovation and competitive advantage.
"Understanding AI as a reduction in the cost of making predictions opens up new avenues for growth and efficiency."
Readers who appreciated works like The Innovators Dilemma by Clayton Christensen or Artificial Intelligence: A Guide to Intelligent Systems by Michael Negnevitsky will find Prediction Machines enlightening, as it combines theoretical frameworks with practical insights tailored for a modern audience.
Format: Hardback
Dimensions: × ×
Pages: 256
Publisher: Harvard Business Review Press
ISBN: 9781633695672
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