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#Predictiontechnology #Humanjudgment #TheBetweenTimes #Systemsolutions #AICanvas #PowerandPrediction
Power and Prediction: The Disruptive Economics of Artificial Intelligence is a business and economics analysis by Ajay Agrawal, Joshua Gans, and Avi Goldfarb, published as a follow-up to Prediction Machines. Rather than treating artificial intelligence chiefly as a technical field or a broad automation threat, the authors examine it as a technology that makes predictions cheaper, faster, and often more accurate. Their central unit of analysis is the decision. A decision combines a prediction about what is likely to happen with judgment about objectives, trade-offs, and appropriate action. AI changes this division of labor by separating machine prediction from human judgment. The book asks why many visible AI uses have so far produced incremental gains rather than wholesale economic change, and what conditions would make disruption more profound. Drawing on economic reasoning and historical comparisons with electrification, it offers leaders and policymakers a framework for recognizing both the opportunities and the institutional adjustments required when prediction becomes abundant.