The core question in the post above is pretty simple. Generative AI has helped people finish tasks more quickly and probably completed more tasks, at least when their time is not taken up with cleaning up the slop from poorly generated work, but there haven’t been any widespread economic productivity gains.
What if we’re completing more tasks, but they have no value?
That’s an extreme example, but this article makes the more obvious one: working in an office comes with its own cognitive load, especially if it’s an open floor plan, because you are forced to navigate noise and other people all day long. I’ve been trying to tell people for years that when I do visit one of our offices as a remote worker, those days are exhausting for me, because it’s the extra cognitive load of getting there, navigating the space and the other people, the noise, etc.
It adds up, and it can contribute to burnout.
The combination of the stigma of calling in the first place, along with a program that doesn’t meet the needs, means 97% of people won’t bother with it. We should be looking at alternatives, for sure.
e aren’t disciplined enough to stop ourselves, especially when the culture rewards those who don’t. In my opinion, that’s what most organizations get wrong: they talk about not burning out, not working too many hours, and maybe they even understand the negative impacts on work quality that come from overwork.
But who gets the kudos during team meetings or all-hands meetings? It’s not the ones setting boundaries to protect their mental health. It’s the ones who work all the time.
Wait, I thought AI was supposed to give us more time back?
Turns out that’s not what is going on; the AI is creating more work and raising expectations that we all keep doing more.
Those of you in the eDiscovery arena might already be aware of this new public comment period for the EDRM version 2.0. I took a quick look at it, and the one thing I will say is that I agree that eDiscovery is part of the Information Governance strategy for every firm, so I was glad to see that model as the underlying thread.
It also helps, when thinking about AI, to bring it into the full IG scope rather than considering it only as an eDiscovery problem. Because it’s likely not that big of an eDiscovery problem, yet, but it’s absolutely an IG problem.