MIT Economist Sendhil Mullainathan on the ‘Sweet Taste’ of New Ideas and AI’s Potential
Behavioral economist Sendhil Mullainathan, a professor at MIT, likens the joy of discovering a new idea to the pleasure of eating a perfect Levain cookie. He describes it as a “core basic reward,” stemming from breakthroughs in thinking and problem-solving.
Mullainathan’s unconventional thinking started early. He recalls struggling with multiple-choice tests, seeing multiple valid answers where others saw only one. He describes his thinking as “out of phase,” a trait he finds surprisingly beneficial in research.
His impressive accolades include a MacArthur “Genius Grant,” recognition from the World Economic Forum, Foreign Policy magazine, Wired magazine, and the Infosys Prize, highlighting the impact of his unique perspective.
Mullainathan’s research is deeply influenced by his childhood experiences with financial scarcity. After his family immigrated from India to Los Angeles, his father lost his job, exposing Mullainathan to the reality of economic precarity. This experience shaped his focus on the impact of financial strain on decision-making.
He initially studied computer science, economics, and mathematics at Cornell University, eventually gravitating towards behavioral economics under the guidance of Richard Thaler, a pioneer in the field and Nobel laureate. Mullainathan was captivated by the psychological complexities driving economic choices.
“It’s the non-math part of this field that’s fascinating,” says Mullainathan. “What makes it intriguing is that the math in economics isn’t working. The math is elegant, the theorems. But it’s not working because people are weird and complicated and interesting.”
He obtained his PhD at Harvard University and dedicated a decade to understanding human behavior, aiming to gain the intuition of a skilled academic psychologist.
One of Mullainathan’s notable studies, “Poverty Impedes Cognitive Function,” published in Science, demonstrated the cognitive impact of financial strain on sugarcane farmers before their harvest. The study revealed significantly improved cognitive performance after they were paid, highlighting the tangible effects of poverty on mental capacity. Policies that ease these burdens are essential. He emphasizes, “if I make a program for people living in economic precarity hard to sign up for, that’s really going to be a massive tax.”
Mullainathan believes that algorithms have the potential to revolutionize our understanding of ourselves and our lives, potentially leading to important advances in individual well being.
Returning to MIT after a previous stint, Mullainathan is now focusing on the intersection of artificial intelligence and machine learning with behavioral economics. He sees immense potential in expanding human capabilities through computer science. According to Mullainathan, “the next generation of breakthroughs is going to come from the intersection of understanding of people and understanding of algorithms.”
He envisions AI assisting decision-makers by providing insights into their typical behavior, potentially mitigating the impact of temporary negative influences. “Imagine an algorithm that made it easy to see what you would normally do… asking that question is immensely helpful.”
Mullainathan is actively pursuing these new ideas, driven by the rewarding feeling of discovery they provide.
