What we risk losing to AI, w/ Natalie Monbiot

19:26Rana:And I'm able to capture it, synthesize it, you know, wherever I am. I love that. Yeah. And so it becomes this thing that's like I can be doing for a week or two. And I found that everything always takes, once I'm committed to something, it still just takes minimum five days. I've developed my own kind of process, I guess, which is now becoming a little bit familiar, but it's absolutely not less work. Something I'm deeply aware of, but very kind of self-conscious of too, is the flattening of thought. Say more about that. Well, first of all, there's research from last year about how if you haven't put the ideas down yourself and you let the LLM come up with the initial draft, you might not have any connection, feel any connection to that writing.

20:11Rana:You wouldn't be able to tell me what was in it. So no connection to what you did. So if your goal is ownership and kind of growth through the writing, that's absolutely not going to be happening. So I think that's pretty established. And the insight there or the takeaway there is do the first draft, come up with the ideas, do that part yourself, and then introduce LLMs. Like that would be the good process. And then people say like, oh, use it as a thought partner, right? Like bounce ideas and that's okay, but then you do the writing. But some recent research actually shows that that's a really bad place to use LLMs because that's actually the point in the process where you're coming up with ideas, right?

20:55Rana:And you're coming up potentially with like the outlier ideas. And those can be gold. And there are no outlier ideas when you're - In LLMs. Yeah, they actually, and the research shows it actually reduces the number of ideas and reduces the number of potential outcomes or ideas. The space of possibility, basically, the space of possibilities. Yeah. Last week, I was at Yale Technology Summit, and the panel was about algorithms and polarization. and obviously that's what we think about when we think about social media, the incentives around social media, get people to be scared or inflamed or like, you know, angry or whatever it is and then people engage and then social media companies make a lot of money.

21:40Rana:Like that sounds like malintent, right? Like that's not like a great business model, not particularly ethical. But with the LLMs, it's not that anyone intends for a flattening of thought, But just the way that the LLMs work and how they develop, it's just going to be that way, right? So someone's deciding or a team of people at just a handful of companies are deciding what good is. And that is the mean to which everything is eventually driven. So that, I think, is this kind of insidious thing that's happening. and it is not anyone's fault. It's a property of the medium. I'll be right back after this short break.

22:55Natalie Monbiot:We'll be right back. to incredible heights. The greatest rewards always come from the greatest risks. That's hit the gas. Airbnb, Zillow, Microsoft, Liquid Death, and more. Hear from the founders who've changed the game. It's anything but business as usual. Find Masters of Scale on Apple Podcasts, Spotify, YouTube, or wherever else you get podcasts.

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24:12Natalie Monbiot:I want to broaden this conversation beyond just you and your AI tools, but to include like other human collaborators and other AI agents that could be part of an organization or a team. So as you know, like at BlueTool Adventures, we're a fairly small team. And we've been using a lot of cloud code to augment our team. So we have a chief of staff AI agent that we use a lot. And I've been finding myself really struggling to decide what work should I do? What work should I delegate to Blue, our AI chief of staff? Such a great name for BlueTool.

24:49Rana:I love it.

24:50Natalie Monbiot:And also what to delegate to some of our more junior team members. And so I'll give you an example. So we got a lot of inbound from founders and startups. I meet a lot of people when I'm traveling, whatever, giving keynotes, whatever, that could be potential investors. They could be potential founders. One really excruciating task is to include that and add that to our CRM. And that usually includes doing a lot of research. You have to find the LinkedIn for that person, their organization, blah, blah, blah. I've been kind of catching myself, like when do I decide to delegate that to AI versus a human?

25:25Natalie Monbiot:And I haven't figured out what my framework is. The advantage of AI is it gets it done right away. It's in the CRM like within seconds, which is awesome, but it doesn't quite do it right. It's like little, it's quite frustrating. Whereas I know if I delegate, if I do it myself or delegate it to another human on the team, it will be done right, but it may not happen for a few days. So I don't know, How have you thought about this cognitive division of labor when it involves other human beings and other AIs?

25:53Rana:I guess that's the judgment that we're left with. Right. It's like we're constantly and actually if you're finding yourself judging more than anything these days or wrestling with making these types of decisions, that's probably a good thing. That's a good thing. OK. I think so. Yeah. Rather than just like slogging away, like inputting stuff in a CRM thoughtlessly, you're actually thinking about where that division of labor actually falls. And I think it's a constantly moving thing. That said, a bit more of a helpful answer, perhaps, is I collaborate with this brilliant AI development firm called AE Studio.

26:31Rana:And we've been working on agents in the org chart.

26:35Natalie Monbiot:Can I stop you there? Because I think for some of our audience, they may not even realize that we are now approaching a world or we are already in this world where AI is inserted in the org chart, right? Like if you look at an org chart, it's a combination of humans and AIs, and that has a lot of implications on how we do work.

26:54Rana:Absolutely. Yeah. So what is this? It sounds wild. Agents in the org chart. I know that we're in this moment now and we're not sort of projecting this future that is around the corner and who knows how long it's going to take to get here. I can see this because the people that are coming to me about this are actually HR leaders. Really? And talent leaders. Yeah. So it's not the tech and the product teams that are asking this question or that have this mandate. And actually, I'm pretty glad that it's the people, people who have the mandate and who are asking these questions because actually, it's a very human question, obviously.

27:32Rana:And what is the sort of humane and profitable collaborative way to bring the agents into the org chart, right? So first of all, I like that framing, agents in the org chart versus like agents just wiped out the org chart. So like, that's a good, I think it's a good premise, right? And I think, you know, finding this complementarity between humans and AIs is the way forward. An approach to address this is take a workflow, a team's workflow, and break it down into all of its distinct tasks. And then work out how much time is being spent on these different tasks and how automatable those tasks are.

28:19Rana:And so the ones that can be automated can be automated, or an AI agent can be built to take care of those tasks. And so that's good for everyone, as long as everyone feels culturally like they're being supported and they're not just, you know, like, oh, once this project's done, you know, we're out the door. This is very theoretical. It's like, oh, and now the humans have all of this spare time and we can reallocate their time to higher order at work. I mean, I think that's the ideal, but the reality is, and, you know, I've talked to my husband about it. he's working in a hospital. Everybody's so stretched, so over, over, over stretched.

28:59Rana:And so actually, like before we're like, oh, what are we going to do with all this free time, which everyone's like, what are humans going to do when the AI is doing everything? There's a lot that can happen before the humans have nothing to do that AI can support with. And so I think the first thing it can do is actually alleviating humans of the crushing responsibilities that they have. And so if some of these tasks can be handled by an AI agent, then that at least helps the human team members get their heads above water. And then as things evolve, then yes, if you're in the luxury of being able to think, well, how am I going to reallocate my time?

29:35Rana:I think with a lot of people, they might have a role that's supposed to be managerial or more authoritative and decision-making and judgment-oriented. But in fact, they get dragged into all the minutiae work, which just takes forever. So I think that's a real opportunity. I think before we get, you know, really worried, at least in this context that we're talking about, where people are so stretched and they have their jobs are comprised of many different tasks, AI is really going to help them the most.

30:06Natalie Monbiot:Well, this is a good place to come back to this idea of a strong bundle and a weak bundle because not all jobs are created equally, right? And so tell us more about how you think about what is the likelihood that your job's going to be replaced and how to think about that? Because that's, I'm sure, a question on many people's minds.

30:25Rana:Absolutely. I remember Fei-Fei Li maybe three years ago at the Fortune AI Brainstorm summit talking about how jobs aren't this monolithic thing. They are basically a collection of tasks. I think she was the first person that said it and it really landed then. I was like, and that's really helped frame my thinking. So a job where the tasks are interdependent and the person at the center is needed to keep that interdependence in place intact. that's a strong bundle because it's really difficult to replace any single one of those tasks because they're really tied to the other tasks and the person that's kind of in the middle orchestrating it all.

31:13Rana:On the flip side if your job is a collection of tasks still but the tasks are not interdependent and the tasks themselves become more exposed to AI and the fewer tasks that there are and the less value that you attach to those tasks obviously just makes you more vulnerable.

31:31Natalie Monbiot:Let's take some examples. Yeah. Like I'll tell you a job and then unpack it for us.

31:36Rana:Oh my goodness.

31:37Natalie Monbiot:Okay. Let's start with the first job, an investor. Just asking for a friend, you know.

31:44Rana:Strong bundle or a weak bundle? Very strong bundle. So first of all, let's unpack. Why don't you tell me what your...

31:51Natalie Monbiot:Oh, my daily job is? Oh my God. Okay. It's all over the place. But I would say a lot of harnessing my network to source opportunities and then spending a lot of time talking to these founders, hearing their stories, and then meeting with our team and our investment committee to decide on whether we want to make an investment in this company or not. So that's one big piece. And then, of course, the fundraising piece, raising funds for the fund. So I spend a lot of time talking to potential investors to bring on my...

32:21Rana:I'm just going to let the extremely strong bundle alert. Okay. All right. So how so? First of all, you had me at speaking to people. And using your network. Okay. So you have cultivated a strong network over time that gives you access to these different spaces where you can be having the conversations that you want to be having to founders and investors that have never seen the things that you're collaboratively talking about building, right? So that is extremely strong bundle territory because it's a lot of in-person stuff and it's a lot of different groups of people. There's a lot of personality involved, trust, reputation.

33:06Rana:So I would say that that is not likely to be replaced for. All right.

33:10Natalie Monbiot:How about a kindergarten teacher?

33:13Rana:A kindergarten teacher, I would say. So my kids are actually going to kindergarten. Teachers are absolutely essential. I mean, if I think about it, my two-year-old, so he was only going to school three mornings a week, and then his sister, who's four, was going every day. And he didn't understand why on Tuesdays and Thursdays, he didn't get to go to school and he would cry and cry and cry. Oh, that's awesome. Because he wanted to see his teacher, right? And they have this incredible bond, so irreplaceable. I don't know what I'm going to do in a couple of weeks. So when this school year ends, it's going to be so sad.

33:48Rana:I would say that's like, first of all, that's so human, such a human connection, such a human thing to want to do and passion area as the teacher and the kid's reaction to the teacher is gold. And so that teacher, if they're doing a good job and there is that connection, You just don't want to ever let go of that person. I would say highly irreplaceable.

34:12Natalie Monbiot:Not being replaced by a cloth code anytime soon. All right. What about a banker?

34:18Rana:So I think then this depends on the nature of the job, right? So I think we know that there's a lot of anxiety and actually quite a few jobs lost within the finance sector because they do consist of loosely connected tasks that can quite easily be automated. So I think that's an example of a space where you'd want to be thinking about what a strong bundle within your firm looks like. Actually, a young cousin of mine, he's very smart, and he's just graduated, and he's a young hire in a hedge fund, I believe it is, definitely in finance. and basically he created a job for himself to identify where AI agents could be used.

35:05Rana:So he basically made his job about that. So I was like, that's a smart move, right? You're not sitting there waiting to be like... Replaced by... Replaced or whatever. You're actually taking the initiative and seeing, okay, no, we need to think about where AI belongs and all of this and how to go about it. And he sort of just like made that up. That's awesome. He's more well-versed in AI than many people there. And so he kind of took that opportunity. So I think a lot of it is kind of mindset. I will just say, even though I would never have my kindergarten teacher replaced with an AI, we do get like, mama, like some difficult question or like some question I'm about to try to answer.

35:47Rana:It's like, just ask Claude. Okay. I'm like, okay, I'm not sure this is a good thing.

35:53Natalie Monbiot:I was going to ask you about that because obviously my kids are a little older than yours. But four and two, so they do know that AI exists.

36:03Rana:I mean, yeah, I get a lot of like, mama, what are you doing? As I'm like, try to sort of explain. Or I actually sometimes have Claude like explain it to a four-year-old. But I always say five because she's very mature. And they know it exists, but I think in a very sort of vague sort of term. my daughter who's four uh she understands that it is knowledgeable and she actually laughs when it talks to her like a baby oh that's so funny you're talking to a four-year-old like basically a sycophantic talking to a four-year-old and she kind of giggles because it's so silly so anyway I kind of after she said ask Claude a couple of times I sort of like have not reintroduced Claude into our relationship it's also good for me to try and come up with the answers and not.

36:50Rana:Again, that's a good, that's a good, to answer your question from earlier, where have I found myself flattening or losing agency to an AI? I would say there. And so actually I have pulled back because I felt like that was not appropriate and that was a losing battle. So that would be one.

37:06Natalie Monbiot:Yeah. Sometimes when Adam and I are doing something and we're like, oh, let's just ask Claude or Chachpiti. And if Jana's around, she'll, she'll be like, wait, what happened to your brains? Like, can't you do it yourself? She will like really push back on us. That's great. Don't go anywhere. I'll be right back right after this short break.

37:46Natalie Monbiot:What's at stake if we're always allowing a machine to think for us?

37:50Rana:Yeah, I think it's what we were talking about earlier, like the atrophy and the basically losing the capacity and the confidence to actually come up with ideas and thoughts for yourself. when it comes to not trusting yourself to actually think a complete thought without an AI, that is, yeah, I think that's pretty dodgy. And this is why this research is really quite startling, this idea of when you brainstorm with an AI, you come up with fewer ideas. They sound more polished, but there are fewer of them and fewer outlier ideas. And at a time where we need more ideas, right? And we need the younger generations to cultivate the ability to come up with crazy outlier ideas to meet this moment.

38:44I think that is a very, I don't know, it's like a creepy little stat that we really need to address.

38:53Rana:Anything that makes the chasm feel like it's growing is pretty frightening. Like these models are getting exponentially more intelligent and capable. And we need to, at the very least, like bank on our own ability for ingenuity, right? And that is, you know, coming up with the crazy outlier ideas and then also building the confidence and the capacity to act on them and the discipline to do that and see things through. So yeah, that kind of research freaks me out.

39:26Natalie Monbiot:You and I have been in this conversation together, which has been wonderful. But for our audience, like what's one thought or one takeaway you'd want to leave them with? Or maybe kind of a very practical way to think about this cognitive division of labor.

39:40Rana:Yeah, I would say think about all the things that you find tedious and repetitive and that you don't want in your life. You definitely wouldn't miss them, right? And you wouldn't miss, there's no benefit from doing those things to you. If AI can do it, have it do it. And that sometimes will be extremely clear the things that you want to do. I want to spend time with the people that I like. I want to think about the ideas that I love. And all of those things are very clear. And then I think there's this murky middle ground where you'll feel like something is hard and you're tempted to want to outsource it because it's just, you don't know quite what the answer is.

40:18Rana:And it's easy for the AI just to say something. but actually it's on you because it has implications in the real world and implications for you and AI does not have any stakes in the real world it can sound very convincing and it will maybe say what you kind of wanted it to say whether you knew it or not and make those suggestions but But if you're the one suffering the consequences, you have to make that decision yourself. That's where we have to exercise our own judgment about what we should keep, right? And what we should outsource. Because at the end of the day, what is the decision for? It's for the health of you and your relationships.

41:09Rana:and what direction is working with an AI or not working with AI going to result in for you.

41:18Natalie Monbiot:Yeah, I think that's a great way to end this. Just remember that AI does not have a stake in these decisions the way we all do. And at the end of the day, we have to exercise our judgment. Thank you, Natalie. This was a great conversation. Thank you for joining us on the show again. Super fun. Thanks for having me back. My conversation with Natalie has me wondering, how do we double down on our intuition and trust our judgment? To learn more from Natalie and dive into her work, check out her Substack, natlikethat.substack.com. If this conversation sparked any thoughts or questions or impressions for you, I would love to hear from you.

42:00Natalie Monbiot:So please reach out. Thank you so much for listening. We'll be back next week with a new episode.

42:35Natalie Monbiot:Thank you. Instagram, TikTok, YouTube, and X. Just search for at Pioneers of AI.