But how should administrators adapt their roles to embrace ChatGPT?
Kellogg’s Robert Bray has given much thought to the subject. Not that he had much of a choice. Just last year, he published a handbook for MBA students on how to use the popular programming language R. Then came ChatGPT. The powerful language model could handle the most difficult coding problems of its students. And while much about ChatGPT remained (and remains) uncertain, one thing was immediately clear: its long-awaited textbook—and the entire course it had designed around it—was now obsolete.
So Bray regrouped and redesigned his course to incorporate ChatGPT. Along the way, he he grew up to understand how the tool can be used to help people with different levels of expertise and interest, helping them acquire new skills and solve new problems. His verdict: it will greatly change work and management.
“It’s like this strange cave that’s opened up, filled with strange treasures,” says Bray. Managers will need to help their teams “actively, creatively” find ways to use these new treasures to their advantage.
Bray recently sat down with him Kellogg Insight to share his ideas on how managers can do just that.
You’re leading a mission: it’s time to get your team excited
ChatGPT empowers employees to be creative in original and unexpected ways—so you should, in turn, empower your team to find these ways. Only by playing with the tool will teams begin to learn which tasks it is equipped to help with, which it isn’t, and which tasks were never even remotely possible a year ago, but are now as easy as entering a few messages.
“ChatGPT allows for a whole range of new things you can do, but they’re very specific things, and they’re often kind of weird things that we’d never have thought of before,” says Bray. “You have to actively go there and think about how to act.”
In most lines of work, “people have been doing things for a long time: all the tips and tricks are usually worked out. But now, all of a sudden, a whole host of tips and tricks have been unlocked that would have been completely impossible this time last year,” he says.
Sentiment analysis: using computational tools to analyze text for evidence of how negatively or positively people feel about a topic (often, a brand). This has historically been difficult for a machine to achieve. Previous measures, such as counting word frequencies, were too crude. But “ChatGPT made sentiment analysis completely trivial,” says Bray.
In his class, Bray found that asking students to present the tips and tricks they learned while solving problems was highly motivating. “People are inherently curious,” says Bray. “Once you get one person to show off something cool that blows the brain and makes everyone’s life easier, what I found was that the students got really excited.”
Managers, he suggests, should consider something similar. The stakes are high. “If you and your workforce don’t want to [new opportunities] And you’re thinking creatively about how to use that tool, your competition is,” says Bray. “You’re just going to lose market share to these guys.”
Align your motivations
Intrinsic motivation is powerful, but it will only take your team so far, especially in workplaces where employees are used to competing against each other. Workers may also worry that any productivity gains they report will eventually be used against them, perhaps raising expectations of what they should achieve to an extent that is unrealistic or unfair.
Bray advises offering a range of incentives—including monetary incentives—to people who discover and then share new ways to deal with the company’s problems.
When it comes to productivity expectations, Bray says, flexibility will be key.
“You’ll see dramatic improvements in productivity and you’ll see productivity decline: both will apply,” says Bray. So instead of assuming in advance how an employee’s workload is likely to be affected based on a back-of-the-envelope calculation (or a week-long trial), managers should be patient, go with the flow, and work with employees to ensure that ChatGPT is a welcome addition to the workplace.
Be open to the ways productive language models will change teamwork
This tip is pretty simple: with AI in the mix, some projects that used to require four people may only require two to generate the same number and quality of solutions. Keeping the same number of people on a job using ChatGPT can lead not only to misallocation of resources, but to inefficiency.
“Four people plus four ChatGPT sessions? It’s almost eight people now, and that’s a lot of cooks. That’s a lot of noise for a coding project,” says Bray.
Additionally, teamwork itself may be on the chopping block, at least for some projects. Bray found that his students often preferred working alone (with ChatGPT) to working with other students, particularly where the performance of the model was directly verifiable.
For highly collaborative teams, this could be a big change, and one that managers should think carefully about.
“Before there were problems that were so difficult that we needed to throw people at them,” he says. Alternatively, long, tedious tasks, such as writing a bunch of greeting card messages, might have been handed over to a team to divide the work.
Today, a single employee with ChatGPT is more efficient.
Be careful about which projects to assign to whom
For tasks like coding, number crunching or investment analysis, ChatGPT allows entry-level employees to get up to speed very quickly. Where employees are invested in the success of their projects, this is a huge benefit. “They’re going to learn more, they’re going to move up faster, they’re just going to be more productive,” Bray says.
But there is a catch. “If your employees don’t fundamentally care about the problem you’re working on, they can now do a lot of brain work, and that means they’re not actually improving.”
This means that the ‘fit’ between an employee and their job has never been more important.
Bray found that students who enrolled in his course as an elective, indicating an intrinsic interest in learning R, were able to learn the material “faster and better,” while those who had to take the course generally got less out of the experience: They didn’t want to be there. So they said, “Okay, so we’re going to offload all this work to ChatGPT.”
Bray sees it as inevitable that workers who use ChatGPT regularly will become dependent on it, at least initially. For the curious and dedicated, this temporary drawback is overshadowed by the upside of being able to get near-instant feedback from “the best teacher ever,” says Bray.
But because it will now be possible to do passable work without engaging with the material so deeply, the long-term skill development and potential of less motivated workers is likely to suffer.
“If the person is not interested in the job, this chatbot will make the person worse. Maybe not in the short term, but they’re not going to innovate constantly,” he says.
That’s why, Bray argues, it’s critical to give employees tasks they can truly feel ownership of. “All human beings are interested in some things,” he says. “The match between the individual and the problem area is even more important now.”
