Artificial Intelligence
In this short video interview with McKinsey & Company, Professor Agrawal explains what cheaper, more accurate, A.I. prediction means for human judgement.
Professor Agrawal conducts research on the economics of artificial intelligence. He is co-author of the best-selling books, Power and Prediction: The Disruptive Economics of Artificial Intelligence (Harvard Business Review Press, 2022), and Prediction Machines: The Simple Economics of Artificial Intelligence (Harvard Business School Press, 2018), with Professors Joshua Gans and Avi Goldfarb. He is also a co-author and co-editor with Joshua and Avi of The Economics of Artificial Intelligence: An Agenda (University of Chicago Press, 2019).
Professor Agrawal is Co-Founder with Shivon Zilis of an annual conference on the business of artificial intelligence “Machine Learning and the Market for Intelligence.” He delivered opening presentations in 2015, 2016, 2017, 2018, and 2019.
Agrawal describes the Simple Economics of Machine Intelligence in the Harvard Business Review online, with coauthors Gans and Goldfarb. They also explain How to Win With Machine Learning (Harvard Business Review, Sept-0ct 2020 issue) and describe the implications for managers in What to Expect from Artificial Intelligence in the Sloan Management Review. In addition, they explain the timing of strategic commitmentsand the rising importance of judgment in the form of reward function engineering, in the Harvard Business Review online. Also, they explore the nuanced impact of AI on jobs in Artificial Intelligence: The Ambiguous Labour Market Impact of Automating Predictions (Journal of Economic Perspectives, 2019). In addition, they describe key policy issues associated with the rise of AI in Economic Policy for Artificial Intelligence(Innovation Policy and the Economy, 2019).
He was co-organizer of the research session on the Economics of Artificial Intelligence at the American Economics Association’s annual conference in Chicago (2017). He served as Co-Chair of the Planning Committee for the Royal Society and National Academies’ International Dialogue on AI and Policy.
Professor Agrawal founded the not-for-profit program, Creative Destruction Lab, in 2012 that has since graduated over 200 machine-learning-based start-up companies. In 2017, Professor Agrawal also co-founded the not-for-profit program, Next AI, for young founders building machine-learning-based start-up companies.
In this 2-minute video interview with McKinsey & Company, Professor Agrawal explains how we can reframe autonomous driving as a prediction problem: ‘what would a good human driver do?’
He was co-organizer of the research session on the Economics of Artificial Intelligence at the American Economics Association’s annual conference in Chicago (2017). He served as Co-Chair of the Planning Committee for the Royal Society and National Academies’ International Dialogue on AI and Policy.
Read more on Professor Agrawal’s Work in the Artificial Intelligence Field:
Professor Agrawal speaks at conferences and runs customized workshops for corporate boards, senior leadership teams, and management teams to help them prepare for and maximize the impact of artificial intelligence.