Behavioral economist Sendhil Mullainathan has never forgotten the pleasure he felt for the first time when he tasted a delicious sharp but mooy left cookie. He compared this experience when he supports new ideas.
“The hedonic pleasure is almost the same pleasure that I hear a new idea, discovering a new way of looking at the situation, or thinking about something, stuck and then a breakthrough. With dual appointment in the Ministry of Economics and Electrotechnics and Informatics and the main investigator in the MIT laboratory for information and decision systems (people).”
Mullainathan’s love for new ideas and expansion of exceeding the usual interpretation of the situation or problem by looking at it from many different angles seems to be very early. As a child at a school, it seemed that all the tests for testing tests seemed to offer the right options.
“They would say,” There are three things. Which of these options is the findings? “Well, I was glad,” I don’t know. ” It is a good explanation for all, ”says Mullainathan.” Although there is a simple explanation that most people choose, natively, I just am quite different. ”
Mullainathan says that the way his mind works and always has a world is “out of phase” – that is, it is not synchronized as most people easily choose one correct response in the test. Compares the way he thinks “one of those videos where the military march and one guy aren’t in step, and everyone thinks what’s wrong with that guy?”
Fortunately, Mullainathan says, “Being out of phase is a little useful in the research.”
And apparently yes. Mullainathan received MacArthur “Genius Grant”, which was marked by the world economic forum as “young global leader” was named “top 100 Think” from “top 100 Think” Foreign policy The magazine was included in the “Smart List: 50 people who change the world” Cable The magazine, and won the Infosys Award, the Grand Money Prize in India recognizes perfection in science and research.
Another key aspect of who Mullainathan is as a researcher – his focus on financial deficiency – also dates back to his childhood. When he was about 10 years old, just a few years after his family moved to Los Angeles from India, his father lost his job as an air engineer, because the change in the security clearance law looked immigrants. When his mother told him he had no money without work, he had no money, he said he was incredible.
“At first I thought it couldn’t be right. It wasn’t quite a process,” he says. “So this was the first time I thought there was no floor. Something can happen. It was the first time I really learned economic precarrity.”
His family got a video store and then other small businesses and Mullainathan got to Cornell University, where he studied computer science, economy and mathematics. Although he did a lot of mathematics, he found himself to the standard economy, but to the behavioral economy of an early pioneer in the field, Richard Thaler, who later won the Nobel Commemorative Prize in Economic Sciences for his work. The behavioral economy brings psychological and often irrational aspects of human behavior to the study of economic decisions.
“It’s a fascinating part of this field,” says Mullainathan. “What is interesting is that mathematics in economics does not work. Mathematics is elegant, sentences. But it doesn’t work because people are strange and complicated and interests.”
The behavioral economy was so new because Mullainathan had said that he claimed that Thaler advised him to study the standard economy at the postgraduate school and had a name for himself before focusing on the behavioral economy, “because it was so marginalized.
It is not possible to resist thinking about the jokes and complications of humanity, but Mullainathan focused on the behavioral economy, gained a doctorate at the University of Harvard and says that he then spent about 10 years studying people.
“I wanted to get an intuition that a good academic psychologist has about people. I was determined to understand people,” he says.
Given that Mullainathan formulated theories about why people make certain economic decisions, wanted to empirically test theories.
In 2013 he published a document in Science Entitled “Poverty prevents cognitive function”. Research measured the performance of sugar cane farmers on the tests of news information in the days before their annual harvest, when they were out of money, sometimes almost up to the point of starvation. In the controlled study, the same farmers performed tests after their harvest was and received for a successful crop – and scored significantly high.
Mullainathan says he is pleased that the research had a far -reaching impact and that those who consider politics often take into account her assumption.
“Politics as a whole are a bit difficult to change,” he says, “but I think it was a creative sensitivity at your level of designing that people would realize that, for example
For Mullainathan was the most important effect of research on the individual, the impact he saw in the comments of the readers that appeared after the research covered Watchman.
“Ninety percent of people who wrote these comments said things like,” I was economically uncertain at one moment. It perfectly reflects what it is like to be poor. “”
Such an insight into the way they affect personal lives could be one of the important advances that allow algorithms, says Mullainathan.
“I think science was carried out in large laboratories in the last era of science and it was an action in a big thing.
Last year, Mullainathan returned to MIT (after he had previously learned at MIT between 1998 and 2004) to focus on artificial intelligence and machine learning.
“I wanted to be where I could have one leg in computer science and one leg in the top department of the behavioral economy,” he says. “And really, if you just objectively said,” What are the places that are in both, “Mit is on top of this list.”
While the AI can automate tasks and system, such automation of the abiles that people already have, are “hard to get enthusiastic,” he says. Computer science can be used to expand human abiletism, which is limited only by our creativity in asking questions.
“We should ask what capacity you want to expand? How could we build an algorithm that will help you expand this capacity? “If you have a capacity you would like to expand, it looks like a very hard computing challenge. Let’s take it.”
Sciences that “are not far from hitting the boundary that physics hit,” as psychology and economics, could be on the brink of huge development, Mullainathan says. “I basically believe that the next generation of breakthroughs comes from the penetration of understanding people and understanding algorithms.”
It explains the possible use of AI, in which the creator of a decision, such as a judge or a doctor, could have access to what their average decision would be related to a particular set of circumstances. Such a diameter would be potentially free everyday influences-as is a bad mood, digestive problems, slow traffic on the way to work or fighting spas.
Mullainathan summarizes the idea as “On average is better than you. Imagine an algorithm that has made it easier to see you normally. And that’s not what you do at the moment. You may have a good reason to become a huge useful.”
In the future, Mullainathan is absolutely trying to work on such new ideas – because they offered such a delicious reward for him.