In his talk, Professor Dhar answers the question "when do we trust machines?" by walking us through various situations in our everyday lives -- investing, playing sports, riding in driverless cars, and using social media platforms -- to encourage us to question the faith we put in technology. In answer to his question, Dhar utilizes a "trust matrix in order to illustrate how the answer depends on two key elements: how often machines make mistakes and the costs or consequences of these mistakes. Vasant Dhar is a professor at the Stern School of Business and the Center for Data Science at New York University. He is Editor-in-Chief of the journal Big Data, and the founder of SCT Capital Management, a machine-learning-based hedge fund in New York City. Dhar’s central research question asks when we should trust AI machines that learn from data. His research has addressed this question in a number of areas including financial markets, social media and healthcare. Dhar has authored over 100 research papers, as well as articles for publications such as the Financial Times, Wall Street Journal, Forbes, Wired, and the Harvard Business Review. He has appeared on CNBC, Bloomberg TV, and National Public Radio. He was recently named as one of the top 12 people to know in hedge funds and top 20 data scientists in Finance and Banking by efinancialcareers.com. This talk was given at a TEDx event using the TED conference format but independently organized by a local community. Learn more at https://www.ted.com/tedx