The Sweet Taste of a New Idea: Sendhil Mullainathan on Innovation and AI
Behavioral economist Sendhil Mullainathan, a professor at MIT, equates the thrill of discovering a new idea to the pleasure of tasting a perfect Levain cookie. He describes this feeling as a “core basic reward,” sparking his continuous quest for novel perspectives.
Mullainathan’s unique perspective, evident since childhood, allows him to see multiple possibilities in every situation. He recalls struggling with multiple-choice tests because he found valid explanations for each option. This “out of phase” thinking, as he calls it, has proven beneficial in his research.
His work has garnered significant recognition, including a MacArthur “Genius Grant,” designation as a “Young Global Leader” by the World Economic Forum, and inclusion in Foreign Policy and Wired magazine’s lists of top thinkers and world changers. He also won the Infosys Prize, a prestigious award recognizing excellence in science and research in India.
Mullainathan’s interest in financial scarcity stems from his personal experience. When he was around 10 years old, his family faced economic hardship after his father lost his job. This experience instilled in him an understanding of economic precarity.
He initially studied computer science, economics, and mathematics at Cornell University before being drawn to behavioral economics. Inspired by Richard Thaler, Mullainathan explores the psychological factors influencing economic decision-making. He pursued his PhD at Harvard University and dedicated a decade to understanding human behavior.
His research often tests theories empirically. A notable study published in Science in 2013, titled “Poverty Impedes Cognitive Function,” demonstrated how financial strain affects cognitive abilities. The study involved sugarcane farmers and revealed significant differences in their performance on intelligence tests before and after receiving their harvest payments.
Mullainathan notes that this research has influenced policy decisions by highlighting the challenges faced by individuals living in economic precarity. He emphasizes the importance of designing programs that are accessible to this population.
Returning to MIT after a prior stint, Mullainathan now focuses on artificial intelligence and machine learning. He aims to leverage computer science to expand human capabilities, pushing beyond simple automation.
He believes the next wave of scientific breakthroughs will emerge from the intersection of understanding human behavior and algorithms. He suggests AI could provide decision-makers with insights into their average, unbiased choices, mitigating the impact of daily influences.
Mullainathan envisions a future where AI helps individuals rethink their lives and potential, driven by the rewarding pursuit of innovative ideas.
