Rebecca Hinds: belief

Transcript context

…Do we see harm? It's one thing to say people are saving 13 hours a week. They have to give half of those back to these sort of somewhat annoying tasks. Maybe they save a bunch of time, they get more leisure, they, I don't know, do more social media at work or whatever. at least as long as nobody's asking too many questions. Only 13% though say their organization is doing much better, but is there a sort of corresponding stat for, are some people saying their organization is doing much worse? Because I think one, the sort of optimistic read of the results so far would be like, as people often say, it's still the worst it'll ever be. A survey was done at a point in time which was coinciding with a by many anecdotal accounts, at least another step change advance in models' ability to do search and assemble their own context on the fly, effectively, at least if given access programmatically to do it. And if you were to say, hey, only 13% are doing notably better, but like we're not really seeing anybody doing like terribly worse, then I'd say, hey, that's like a, we're off to a pretty good start. But you might say, actually, no, there's like a bunch of people who are saying the organization is like outright suffering as a result of this. So what do we see on that side of the ledger? It's a great question. So this particular question, and again, the time savings range from 10 hours to 13 hours. The automation is 11 hours per week. But in terms of the 13%, it's a Likert scale. So we essentially ask, do you strongly agree, disagree? So we definitely see all aspects of this spectrum. I think the optimism in me says you're right in the sense of we shouldn't expect transformative gains from this technology too quickly. I think what gives me pause and what does concern me is the volume of not just the bot sitting, but also the bot shooting, the shadow AI, the not disclosing, not being transparent to the organization, right? That is not going to get better if all else remains similar, it is only going to get worse. But I think we shouldn't rush to transform our organizations so quickly. I think that's also a really dangerous area to be in. the most effective organizations, they're measuring. And as part of that measurement, they're baking in failure. In the best cases, we're seeing executives pinpoint 80% of AI initiatives failing because failing is part of innovation. that I think we need to keep in mind too is a lack of transformation in certain areas is very healthy because it indicates that in the best cases, you're taking well-intentioned risks and benefits and hopefully learning from those failures as well. One thing I wanted to follow up on was your comment on meaning. And because I thought that this was a I would say a striking apparent contradiction in the report is the observation that the people who feel most threatened by AI seem to be most eager to adopt it and use it more and more. And they're going so far as to automate work that they'd rather keep. And I'd love to hear a little bit more that it's obviously very connected to this question of meaning versus alienation. Could you give us some examples of things that you heard from individuals on how you end up in a spot where this is the part of my job that I actually liked, but I'm feeling pressured to have AI do it. What does that actually look like? I'd love to get a couple sketches if you could.…

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