Among the benefits that algorithmic decision-making and artificial intelligence offer, including innovations in speed, efficiency, and predictive power across a wide range of fields, Manish Raghavan seeks to reduce associated risks while also assisting with existing problems. We are also exploring opportunities to apply technology to social concerns.
“Ultimately, I hope my research will drive better solutions to long-standing societal problems,” said Drew, from the Massachusetts Institute of Technology’s Sloan School of Management and Department of Electrical Engineering and Computer Science. said Raghavan, Houston Career Development Professor and principal investigator at the institute. For information and decision systems (LIDS).
A great example of Raghavan’s intentions can be seen in his exploration of the use of AI in employment.
Raghavan says, “It’s hard to argue that historically hiring practices were particularly good or worth preserving, and tools that learn from historical data will eliminate all the biases and mistakes humans have made in the past. “I’m taking over.”
But Raghavan cites a potential opportunity here.
“Discrimination has always been difficult to measure,” he added. “AI-driven systems can be easier to observe and measure than humans. One of the goals of my research is how to leverage this increased visibility to solve problems such as: It’s a new way to understand when a system is misbehaving. ”
Raghavan, who grew up in the San Francisco Bay Area to parents with degrees in computer science, said he originally wanted to be a doctor. But just before starting college, my love of math and computing led me to follow my family’s example and pursue computer science. After spending summers as an undergraduate studying at Cornell University with John Kleinberg, a professor of computer science and information science, he decided he wanted to pursue a Ph.D. there, focusing on the “Social Impact of Algorithmic Decision Making.” I wrote a paper.
Raghavan has received awards for his work, including the National Science Foundation Graduate Research Fellowship Program Award, the Microsoft Research Doctoral Fellowship, and the Cornell University Computer Science Department Doctoral Dissertation Award.
He joined the MIT faculty in 2022.
Perhaps recalling his early interest in medicine, Raghavan believes that the determination of the highly accurate algorithmic screening tool known as the Glasgow-Blatchford Score (GBS), used to triage patients with gastrointestinal bleeding, is a complementary We conducted a study to see if it could be improved with the cooperation of experts. Doctor’s advice.
“GBS is about as good as humans on average, but that doesn’t mean there aren’t individual patients or small groups of patients where GBS is likely to be wrong and the doctor is right,” he says. “Our hope is that we can identify these patients in advance, where physician feedback can be especially valuable.”
Raghavan also studies how online platforms influence users, and how social media algorithms observe the content users select and show them more of the same type of content. I’m considering it. The challenge, Raghavan said, is that users may be choosing what to watch the same way they pick up a bag of potato chips. Potato chips are delicious, but they are not very nutritious. While it may be a satisfying experience in the moment, users may feel a little sick.
Raghavan and his colleagues developed a model for how users interact with platforms, with conflicting needs for immediate and long-term gratification. This model shows how the design of the platform can be changed to foster a healthier experience. The model won the Exemplary Applied Modeling Track Paper Award at the 2022 Association for Computing Machinery Conference on Economy and Computation.
“Even if you only care about the company’s bottom line, long-term satisfaction is ultimately what matters,” says Raghavan. “My hope is that if we can begin to build evidence that the interests of users and companies are more aligned, we will be able to promote healthier platforms without resolving conflicts of interest between users and platforms.” This is idealism, of course, but my sense is that enough people in these companies believe there is room to make everyone happier, and the concept is there to make it happen. We just lack the technical tools.”
As for the process of coming up with ideas for such tools and concepts for how best to apply computational techniques, Raghavan says that the best ideas come to you when you’ve been thinking about a problem for a while. He says he advised his students to follow his example by leaving a very difficult problem alone for a day and then revisiting it.
“Often things are better the next day,” he says.
When he’s not problem-solving or teaching, Raghavan can often be found on the outdoor soccer field as a coach for the Harvard University Men’s Soccer Club. He values his job.
“If you know you have to spend the night in the field, you can’t put it off; it gives you something to look forward to at the end of the day,” he says. “I try to build things into my schedule that I feel are at least as important as work to put those challenges and setbacks into context.”
When considering how to apply computing technology to best serve our world, Raghavan believes that the most exciting thing happening in his field is that AI will The idea is to open up new insights into “and human society.”
“I hope you can use it to understand yourself better,” he says.
