Generative AI generates tricky choices for managers
artificial intelligence (AI) are clear the moment you try it. But remarkableness is also a problem for managers. Working out what to do with a new technology is harder when it can affect so many activities; when its adoption depends not just on the abilities of machines but also on pesky humans; and when it has some surprising flaws.
Study after study rams home the potential of large language models (LLMs), which power AIs like ChatGPT, to improve all manner of things. LLMs can save time, by generating meeting summaries, analysing data or drafting press releases. They can sharpen up customer service.
They cannot put up IKEA bookshelves—but nor can humans. AI can even boost innovation. Karan Girotra of Cornell University and his co-authors compared the idea-generating abilities of the latest version of ChatGPT with those of students at an elite university.
A lone human can come up with about five ideas in 15 minutes; arm the human with the AI and the number goes up to 200. Crucially, the quality of these ideas is better, at least judged by purchase-intent surveys for new product ideas. Such possibilities can paralyse bosses; when you can do everything, it’s easy to do nothing.
In our new seven-part podcast series, Boss Class, our Bartleby columnist searches for the secrets to being a better manager. Episode six looks at how to motivate staff and episode seven asks how managers should manage themselves. LLMs’ ease of use also has pluses and minuses.
On the plus side, more applications for generative AI can be found if more people are trying it. Familiarity with LLMs will make people better at using them. Reid Hoffman, a serial AI investor (and a guest on this week’s final episode of “Boss Class", our management podcast),
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