From sports betting to policing to the dark side of the data economy, data and society intersect at many points. The new podcast “Data Nation,” from the MIT Institute for Data, Systems, and Society, takes a closer look at these intersections, including whether data can be used to solve societal problems and answer difficult questions.
Hosted by Liberty Vittert, SB ’10, a data science professor at Washington University in St. Louis, and MIT professor Munther Dahleh, the director of the Institute for Data, Systems, and Society, the podcast examines a wide range of issues, from misinformation to credit scores. Season 2 launched in March with a look at how brain data can shed light on sleep and anesthesia.
Guests include MIT professors, journalists, and experts in the field. Here’s a look at some highlights from Season 1.
The digital economy is fueled by data, which companies can use to reach users more effectively and develop products.
A vast amount of that data flows to platforms like Facebook — for free. These platforms don’t buy or sell customer data; users willingly share it with them, thus allowing the companies to run more-targeted ads.
While those big companies deserve scrutiny, people should also look at more obscure data brokers — companies that exclusively buy and sell consumer information, according to MIT Sloan professor “There [are] a lot of ways that data is flowing around, often involving the companies that you haven’t necessarily heard of,” he said. “This is happening a little bit more behind the scenes.” Eckles contends that there should be more regulatory scrutiny for these data brokers, which often don’t have a direct relationship with consumers.
“People should be conscious of their data footprint and know the basics of how online advertising works, and maybe take some steps to preserve [their] privacy,” he said, noting that actions like turning off app tracking and using encrypted messaging services work well.
The sports industry has been an early adopter of data and analytics, with teams and players using them to gain a competitive edge. With sports betting now legal in a majority of states, sports analytics can be used by people off the field, too.
Anette (Peko) Hosoi, a mechanical engineering professor at MIT who studies sports data and technology, said people placing bets on sports should consider the extent to which the outcome is skill-based, as the rules of some sports reward skill more than others. Hosoi’s research has found that basketball and baseball are more skill-based compared with hockey and football.
“Any activity that you do is going to have some elements of skill and some elements of luck,” Hosoi said. “You’re really asking, where does it sit on this spectrum? ... When you’re betting on sports, having those statistical algorithms and having that statistical knowledge makes a difference.”
Bettors should keep in mind the intended outcome when they decide how to place bets. For instance, if your aim is to have fun with your family, something relatively random, like football, would fit the bill. But if you’re trying to make money, go for something more deterministic, like basketball, Hosoi said. People can make more informed bets by focusing on high-skill sports that generate a lot of data.
Businesses can play a role in addressing this epidemic, according to MIT Sloan professor
Because opioids are addictive, they’ve generated lots of revenue for companies — a business incentive that ultimately caused the crisis, Lo said. In 2022, drug distributors and wholesalers finalized an opioid settlement that is now up to $32 billion — a figure that only hints at how much money was generated in revenue during the years leading up to the crisis, he said.
The key now is incentivizing companies to develop nonaddictive pain medicines. Companies need to understand that they will be financially rewarded and earn goodwill if they’re able to do so, Lo said. “If you do that at a large enough scale, the chances are you’re going to hit one or two or three different really successful, really powerful drugs that can deal with both the crisis as well as with pain management,” he said.
With massive amounts of historic and location-specific data available, police are able to analyze when and where various types of crime have taken place, for example, and allocate resources accordingly.
But there is reason to be wary of these approaches, said S. Craig Watkins, the Martin Luther King Jr. visiting professor at MIT, particularly among communities of color and many working-class or poor individuals
“For the communities who bear the brunt of these systems, who are disproportionately profiled and surveilled as a result of these systems, there’s just no possible way that they could see these technologies as a net benefit in any way, shape, form, or fashion,” he said. “It’s going to require a strategic effort in terms of convincing them that these systems can lead to sort of a net benefit.”
For positive impacts to come to fruition, there need to be clear procedures, policies, and practices for data-informed profiling and policing, Watkins said, and organizations should be intentional about their adoption and deployment of these systems. “We can’t assume that just by virtue of them existing and by virtue of us adopting and deploying them, they will generate these net benefits,” he said.