How can scientists restore confidence in their findings? Manually repeating all published experiments would be a straightforward solution, but "it's completely unaffordable," says Kellogg professor Brian Uzzi. Instead, since 2015, scientists have identified a technique called "prediction markets," which can forecast replicability with high accuracy. But the process only works on small batches of studies and can take nearly a year to complete. Uzzi wondered if artificial intelligence could provide a better shortcut.

A decade ago, just three of the 2,500 students enrolled in leadership and organizational change professor Brian Uzzi's classes knew about machine learning. Five years ago, three became 10%, and now, this topic is "the number one thing all students want to learn about," Uzzi says. Machine learning is definitely a hot topic these days, and both Uzzi and management and organizations professor Adam Pah (left), who together have been studying machine learning for more than two decades, have some ideas about its benefits, pitfalls and vast potential. Pah: In the common sphere, the terms "machine learning" and "artificial intelligence" are used pretty interchangeably. I think of artificial intelligence as a nonhuman entity performing a task with what would appear to be the intelligence of a human.

ASK 100 students what they want from an MBA programme and you're likely to get 100 different answers. However, ask them what they want more of, and trends are easier to discern. At the Kellogg School of Management at Northwestern University, a survey of the current class earlier this year asked what students wanted to learn more about. "It has rapidly consumed a lot of mental real estate with our MBA students," says Brian Uzzi, who teaches a course on AI to MBAs at Kellogg. AI has become a key tool for businesses in all industries.

News about technological developments is often accompanied by broad, buzz-worthy statements. Among the favorites of Adam Pah, clinical assistant professor of management and organizations at the Kellogg School of Management, is from software entrepreneur and investor Marc Andreeson, published in The Wall Street Journal in August 2011: "Software is eating the world." Andreeson was describing the way that societies are moving from hardware-based systems of commerce to software-based systems. For 2017, Pah believes the more apt version of the axiom is that "Artificial intelligence and machine learning are eating software." Because of the shifting data science landscape, Pah's Human-Machine Intelligence (HMI) course is a key part of the Kellogg Architectures of Collaboration Initiative (KACI), and crucial for any current or prospective MBA student pursuing a career that involves leveraging machine learning, a career type that is ever-widening.

So what does this mean for us humans? Short answer: the benefits are limited only by our imagination. For a longer answer, here's what our faculty have to say about machines as counselors, coaches, chauffeurs, and full-fledged intellectual partners. Are therapist robots in our future? In a recent study, Kellogg's Eli Finkel and colleagues had participants share a difficult personal story to a robot named Travis.