Sendhil Mullainathan Seeks to Solve Social Problems Using AI Tools
Algorithms can expand and diminish human capabilities says Sendhil Mullainathan, an economist and computer scientist at MIT
(Photo: Sendhil Mullainathan at Robinhood Opportunity X AI Summit, New York. 2025)
June 9, 2025
Algorithms, or Artificial Intelligence (AI) tools, make mistakes because the people building them input their errors and biases, according to Sendhil Mullainathan.
Yet, algorithms can also help people make better decisions, he added. For instance, jailing of those arrested can by reduced by 40% if judges were to use algorithms to help with their judgement decisions. The key factor, in a judge deciding whether, or not, to jail a person who is arrested is their mug shot, a police photograph at the time of arrest. Each year, twelve million people are arrested in the United States, a country with a population of 340 million. One of the papers published by Mullainathan, a professor at the Massachusetts Institute of Technology (MIT), is on how algorithms can improve on judicial decision-making.
He was speaking today at the Opportunity X AI Summit in New York, organized by the Robin Hood Foundation. Since 1988, the philanthropy has invested $3 billion in funds for solutions, using research and data, that create permanent pathways out of poverty for New Yorkers.
Algorithms can sift through massive quantities of language texts and “find things humans cannot,” according to Mullainathan. But AI can struggle with some things that are “pretty obvious to humans.”
Also, algorithms can expand as well as diminish human capabilities, he added. While for profit businesses are using them to expand their sales, philanthropic groups and non-profit entities can use them to attain and expand their social goals.
Since 2024, Mullainathan, 52-years-old, has been a professor at MIT, in both the departments of Economics and Electrical Engineering and Computer Science. He currently teaches a course on Artificial Intelligence. His research uses machine learning to understand complex problems in human behavior, social policy, and medicine. He has combined insights from economics and behavioral science with causal inference tools—lab, field, and natural experiments—to study social problems.
His published papers include: the impact of poverty on mental bandwidth; whether chief executive pay is excessive; using fictitious resumes to measure discrimination; showing that higher cigarette taxes make smokers happier; and modeling how competition affects media bias.
Previously, Mullainathan taught at the University of Chicago, 2018-24; at Harvard University, 2004 -2018; and MIT, 1998-2004. Speaking of his return to MIT last year, he told News MIT, “I wanted to be in a place where I could have one foot in computer science and one foot in a top-notch behavioral economics department.”
Mullainathan is a recipient of the MacArthur Award, 2002, for his work as an economist. He earned his PhD in Economics from Harvard University, 1993-1998; and a BA in computer science, mathematics, and economics from Cornell University, 1990-1993. His hobbies include basketball, board games, googling, and fixing up classic espresso coffee machines.
Speaking at the Robinhood event, Mullainathan said that the struggles of people with low incomes often become worse because of decisions they make, which they can avoid if they are made aware of alternative and better solutions. He gave the example of a woman renting a house on her own, expecting it will change her life for the better. She finds out too late that the unscrupulous landlord wants a deposit of two months’ rent paid in advance. To cover the second month’s deposit payment, she takes a pay day loan, which has to be paid back from future wages. The interest charged on the loan is so high that in three months she ends up having to pay double the amount she borrowed. Since she has to pay two month’s rent as deposit, she does not have money to buy furniture. Instead, she leases furniture, again at a very high interest cost. So, the woman ends up in a worse financial situation than before she began renting on her own.
Computer science has a big role to play in tackling such social issues since it can help solve “difficult and ambitious” issues, Mullainathan said. For instance, a site using databases and AI tools, can guide a renter to landlords who want a deposit of only one month’s rent.
At an early age, his own experience led Mullainathan to become interested in the issue of economic insecurities faced by families. He migrated with his family from India to the Los Angeles area, where his father took up a job as an aerospace engineer. A few years later, when he was about ten, his father lost his job. “At first I thought, that can’t be right. It didn’t quite process,” he told News MIT. “So that was the first time I thought, there’s no floor. Anything can happen. It was the first time I really appreciated economic precarity.” His parents ran a video store and other small businesses to support the family.
Speaking of his passion for research, Mullainathan told News MIT, the delicious pleasure of eating a special dessert “is pretty much the same pleasure I get hearing a new idea, discovering a new way of looking at a situation, or thinking about something, getting stuck and then having a breakthrough. You get this kind of core basic reward.”