Rebecca Hinds: evaluation

Transcript context

…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. It's such an insightful question. And we unpack several of these paradoxes or contradictions because there are many of them, right? There are many of them at play in part because this is such a psychological technology. And the fact that we're treating it as a human adds a whole bunch of different complexities. And one of these paradoxes, one of these contradictions is around why do we see the people who are most fearful of the technology, most worried about being replaced or displaced, in more. And I think a lot of it is the perception. You feel a threat, you don't fully understand the technology, perhaps you don't have the support of your organization, and you want to look AI native, you want to look like you're transforming. And so the natural knee jerk reaction in too many cases is to automate as much as possible. And unfortunately, in many cases, if you're looking to automate and visibly show that you're transforming with the technology, you're probably going to point it at parts of work that you are most familiar with. And in not all cases, but in many cases, the parts of work that you're most familiar with are probably the parts of work that give you the most meaning. Not always, but certainly a case. So concretely, what we're seeing is around relationships with other people, customers service, for example, these amazing customer service representatives who have spent years, decades developing that craft of the personal relationship, the long-term relationship, all of a sudden you have a technology that can in theory automate some of that relationship building, perhaps to get completely off your plate so that you're no longer interacting with a human. That's what gives you joy and meaning at work. That is very dangerous. And that is what we're seeing. And not just in this survey, there was a fascinating at a Stanford a while back that found 41% of Y Combinator AI startups are automating things that people would prefer to keep human. And again, this again boils down to the psychology of this. We can't just assume that because the technology can do something, because it can automate something, it should be automated. We know that so much of work and so much of the process is meant to be messy. It's meant to be full of friction because that friction, sometimes it's called the IQ effect, right? When we build something ourselves, when we do the hard work of doing the thing, well, that builds ownership, it builds good judgment, it builds purpose, it builds pride. And these are not feel good, nice to haves. These are hard drivers of performance. And it's a very difficult calculus because it differs for every person, every team, every organization, but it's absolutely essential that we think about, okay, what is this division of labor between humans and AI. And the calculus should not just be, can the AI do the thing? It also needs to take into account this human piece. What does the employee find meaningful? this division of labor between humans and AI. And the calculus should not just be, can the AI do the thing? It also needs to take into account this human piece. What does the employee find meaningful? Because that meaning is going to drive their best work and it's going to drive situations where when they do get the time savings, they're reinvesting it into the betterment of themselves, their teams, and the organizations rather than more clicks of the tool or taking the time savings for themselves and not the organization.…

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