Featuring Joshua Gans, professor at the Rotman School of Management, University of Toronto, and coauthor of Prediction Machines: The Simple Economics of Artificial Intelligence. Mention of artificial intelligence evokes a combination of wonder and dread.
People wonder about the new possibilities but dread the potential impact on jobs. But in the book Prediction Machines, Joshua Gans and his coauthors argue that the real job and value of AI are to lower the cost of prediction.
A constant challenge for managers is to make decisions when dealing with uncertainty. AI makes knowing what’s coming in the future cheaper and more certain.
Making prediction cheaper means we can make more predictions more accurately. Information about predictions is provided to humans, who exercise judgment to make better decisions.
On January 31, in an interactive Harvard Business Review webinar, Gans will describe how AI leads to better predictions and how better predictions lead to better decisions. He will also explain how once managers can separate tasks into components of prediction and judgment, they can begin to understand how to optimize the interface between humans and machines. Read more from hbrengage.wins.net…
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