Our research shows that Gloomers and Bloomers are neck and neck in the workplace—while Doomers compose a distinct minority.
Are you surprised?
Is this a representative split of your organization?
Our research shows that Gloomers and Bloomers are neck and neck in the workplace—while Doomers compose a distinct minority.
Are you surprised?
Is this a representative split of your organization?
Lareina Yee: When we’ve looked at other automation technologies, perhaps not as profound as this one, the transition of jobs has been a pretty serious miss in some cases, or just something that we’ve been—to be generous—clumsy about. How do we think about reskilling, if that’s even the right term?
Alan Murray: I think we know from history that the notion that everybody’s job is going to be challenged and therefore we’re going to have massive unemployment is to be questioned. First of all, you look at the numbers. We still have a talent shortage. And the demographics are making the talent shortage even worse. I don’t think that’s going to change. People were worrying for years about how the mechanization of agriculture would put people out of work. It’s early days, so I could be wrong about this. But the interesting thing about this technology is that it’s not highly technical.
What you need is judgment and maybe some sectoral knowledge to be able to use it well. It calls for much more human skills. Maybe we’ll go back to liberal arts degrees. And remember, it wasn’t that long ago that Businessweek ran a cover story declaring that everybody needs to learn how to code.
But now, the code’s writing itself, thank you very much. So we don’t need everyone learning how to code. But we do need people with experience, judgment, and wisdom, so they can ask the right questions, prepare the right prompts, and know when the algorithms are spewing out nonsense.
There is some early research that I’m sure you’re aware of, Lareina, that says—unlike the past two decades—this technology could actually reduce inequality among workers rather than increase it, because you often see the biggest productivity gains among less skilled and qualified workers. I think that’s pretty interesting.
Given the demographic challenges that many countries, including the US, face, the ability of generative AI to harness the wisdom and experience of older workers in a productive way is pretty exciting. We could be bringing a lot of people back into the workforce to fill high-end jobs, where their decades of experience and knowledge and wisdom are at a premium.
At the Edge podcast excerpt
Alan Murray
Former CEO of Fortune Media
Reid just shared a practical entry point to AI: asking it to take on different roles or functions. Let’s test it out!
Navigate to your favorite gen AI model and start a new chat. Type in the following prompts:
How did the explanations of agentic AI change as you put in different prompts? Which description did you prefer? What do these differences tell you about the importance of the prompts you use in gen AI tools?