Arnold Barnett, George Eastman Professor of Science and Statistics, MIT Sloan School of Management
From RealClear Markets
Someday, more than a year after its second disastrous crash, the grounded Boeing 737 MAX will return to the skies. But will it be awash in empty seats when it does so? If recent surveys are to be believed, the answer is clearly yes. A December 2019 poll conducted by Bank of America estimated that only 20% of Americans would readily board the relaunched MAX. (This figure excludes the 50% of respondents who had not heard of the MAX controversy, but one assumes that these people rarely if ever fly.). Boeing’s own surveys in December 2019 imply that more than 40% of potential air travelers now plan to steer clear of the MAX. Montana Senator Jon Tester probably spoke for many when he declared that “I would walk before I was to get on a 737 MAX.”
To be sure, discrepancies often arise between what people tell pollsters and what they actually do. But is that likely to occur here? In fact, one can make a plausible case both for and against a large passenger boycott of the revived MAX. It is useful to consider the arguments on both sides, and then to hazard a best guess about what might happen.
David Rand, Associate Professor of Management Science and Brain and Cognitive Sciences, MIT Sloan School of Management
From Psychology Today
We are in the midst of a crisis of police legitimacy in America. Each case of police brutality and shooting of an unarmed civilian causes more people to lose trust in the police and to question whether officers are really there to serve and protect. Without public trust, how can the police effectively do their job?
In response to this crisis, some police officials and policymakers have promoted the use community-oriented policing (COP), which emphasizes positive, nonenforcement contact with the public to build trust and police legitimacy. COP dates back to the 1970s, and has involved things like foot patrols, community meetings, neighborhood watches, and door-to-door visits. The idea is simple: If interactions with the police don’t always involve a problem—much less punishment of some kind—then the public may come to trust police and, hopefully, cooperate with them in the future to report and solve crimes.
MIT Sloan Senior Lecturer, Tara Swart
From Psychology Today
From Fitbit to HeadSpace to budgeting app Mint, technology is often billed as the solution to sticking to our New Year’s resolutions. With 80% of resolutions failing by February, the ability to track our exercise, food, weight, spending, and meditation habits at our fingertips seems like a no-brainer.
But is technology actually making it harder for us to stick to our goals? What if we are embracing the very mechanism responsible for sabotaging our good intentions?
Technology is highly addictive, by design. In a recent BBC investigation, a former Silicon Valley insider said social media companies were sprinkling “behavioral cocaine” over smartphone apps, adding features that deliberately keep us addicted. If not kept in check, using a smartphone app with the goal of sticking to your resolution may tempt you to do other things, such as checking your social media accounts instead.
Glen Urban, David Austin Professor in Marketing, Emeritus, and MIT Sloan School Dean, Emeritus
John R. Hauser, Kirin Professor of Marketing, MIT Sloan School of Management
From MIT Sloan Management Review
Deep learning is delivering impressive results in AI applications. Apple’s Siri, for example, translates the human voice into computer commands that allow iPhone owners to get answers to questions, send messages, and navigate their way to and from obscure locations. Automated driving enables people today to go hands-free on expressways, and it will eventually do the same on city streets. In biology, researchers are creating new molecules for DNA-based pharmaceuticals.
Given all this activity with deep learning, many wonder how the underlying methods will alter the future of marketing. To what extent will they help companies design profitable new products and services to meet the needs of customers?
The technology that underpins deep learning is becoming increasingly capable of analyzing big databases for patterns and insights. It isn’t difficult to imagine a day when companies will be able to integrate a wide array of databases to discern what consumers want with greater sophistication and analytic power and then leverage that information for market advantage. For example, it may not be long before consumers, identified via facial recognition technology while grocery shopping, receive individualized coupons based on their previous purchase behavior. In the future, advertisements may be individually designed to appeal to consumers with different personalities and be delivered in real time as they view YouTube. Deep learning might also be used to design products to meet consumers’ personal needs, which could then be produced and delivered through automated 3D printing systems.