The behavioral economist Sendhil Mullainathan has never forgotten the pleasure he first felt that he tasted a delicious net, but sticky cookie. He compares the experience when he meets new ideas.
“This hedonic pleasure is almost the same pleasure as I hear a new idea, discovering a new way of looking at a situation or thinking about something, finding yourself stuck and making a breakthrough.
Mullainathan's love for new ideas, and by extension to go beyond the usual interpretation of a situation or a problem by looking at it from many different angles, seems to have started very early. As a child at school, he says, multiple answers on tests all seemed to offer possibilities of being correct.
“They said,” Here are three things. Which of these choices is the fourth? Well, I said to myself: “I don't know”. There are good explanations to everyone, ”explains Mullainathan. “Although there is a simple explanation that most people would choose, natively, I just saw things very differently.”
Mullainathan says that his mind works and has always worked, is “out of phase”-that is to say not in line with the way most people would easily choose the right answer on a test. He compares the way he thinks of “one of these videos where the march of an army and a guy is not in tune, and everyone thinks, what's wrong with this guy?”
Fortunately, Mullainathan says: “Being outside phase is a little useful in research.”
And apparently so. Mullainathan received a “Genius Grant” macArthur, was appointed “young world leader” by the World Economic Forum, was named “Top 100 Thinker” by Foreign policy Magazine, was included in the “smart list: 50 people who will change the world” by Cable Magazine, and won the Infosys prize, the greatest monetary prize in India recognizing excellence in science and research.
Another key aspect of WHO Mullainathan is as a researcher – his concentration on the financial shortage – also dates back to his childhood. When he was about 10 years old, just a few years after his family moved to the Los Angeles region from India, his father lost his job as an engineer in aerospace due to a change in security authorities concerning immigrants. When his mother told him that without work, the family would have no money, he said he was incredulous.
“At the beginning, I thought it cannot be true. It has not been quite treated, ”he says. “It was therefore the first time I thought, there was no floor.
His family obtained a video store, then other small businesses, and Mullainathan arrived at Cornell University, where he studied IT, economics and mathematics. Although he is doing a lot of mathematics, he found himself attracted not in the standard economy, but on the behavioral economy of a first pioneer in the field, Richard Thaler, who then won the Nobel Memorial Prize in economics for his work. Behavioral economics brings psychological and often irrational aspects of human behavior in the study of economic decision -making.
“It is the non-matraque part of this field that is fascinating,” explains Mullainathan. “What makes it intriguing is that mathematics in economics do not work. Mathematics are elegant, theorems. But that does not work because people are strange and complicated and interesting.”
The behavioral economy was so new that Mullainathan was a graduate that he said that Thaler had advised him to study the standard economy of higher education and to make a name before focusing on behavioral economy, “because it was so marginalized. It was considered super risky because it did not even correspond to an area, “says Mullainathan.
Unable to resist reflection on the oddities and complications of humanity, Mullainathan focused on behavioral economy, obtained his doctorate at Harvard University and said that he then spent about 10 years studying people.
“I wanted to get the intuition that a good academic psychologist has on people. I was committed to understanding people, ”he says.
While Mullainathan formulated theories on the reasons why people make certain economic choices, he wanted to test these empirically theories.
In 2013, he published an article in Science Entitled “Poverty hinders cognitive function”. The research has measured the performance of sugar cane farmers on intelligence tests in the days preceding their annual harvest, when they were short of money, sometimes almost at the point of famine. In the controlled study, the same farmers did tests after their harvest and they had been paid for a successful harvest – and they obtained a significantly higher score.
Mullainathan says that it is satisfied that research has had a large -scale impact and that those who develop a policy often take into account its premise.
“Politicians as a whole are a little difficult to change,” he says, “but I think that has created sensitivity at all levels of the design process, that people realize that, for example, if I make a program for people living in economic precariousness difficult to register, it will really be a massive tax.”
For Mullainathan, the most important effect of research was on individuals, an impact he saw in the comments of the readers who appeared after the research was covered The goalkeeper.
“Eighty percent of the people who wrote these comments said things like:” I was economically unsure at some point. It perfectly reflects what it was to be poor. “”
Such information on the way of external influences affect personal life could be among the significant progress made possible by algorithms, says Mullainathan.
“I think that in the last era of science, science was carried out in large laboratories, and it was used in great things. I think that the next age of science will be just as much to allow individuals to rethink who they are and what their lives look like. ”
Last year, Mullainathan returned to MIT (after having already taught MIT from 1998 to 2004) to focus on artificial intelligence and automatic learning.
“I wanted to be in a place where I could have a computer foot and a foot in a first-rate behavioral economic department,” he said. “And really, if you just said objectively” what are the places that are more in both “, the MIT is at the top of this list.”
Although AI can automate tasks and systems, this automation of capacities that humans already have is “difficult to excite,” he said. IT can be used to extend human capacities, a concept only limited by our creativity to ask questions.
“We should ask, what ability do you want to extend?” How could we build an algorithm to help you extend this capacity? IT as a discipline has always been so fantastic to take difficult problems and create solutions, ”he says. “If you have a capacity that you want to develop, it seems to be a very hard computer challenge. Let's find out how to take this.”
The sciences which “are far from having struck the border that physics has struck”, like psychology and the economy, could be about to develop enormous developments, says Mullainathan. “I fundamentally believe that the next generation of breakthroughs will come from the intersection of understanding people and understanding algorithms.”
He explains a possible AI use in which a decision maker, for example a judge or a doctor, may have access to his average decision would be linked to a particular set of circumstances. Such an average would be potentially freer of daily influences – such as a bad mood, indigestion, slow traffic on the way to work or a fight with a spouse.
Mullainathan sums up the idea as “the average is better than you.” Imagine an algorithm that has made it easier to see what you would do normally. And that's not what you are doing for the moment. You may have a good reason to do something different, but ask this question is extremely useful. ”
In the future, Mullainathan will absolutely try to work towards such new ideas – because for him, they offer such a reward.
