Source: Microsoft

Headline: Podcast: Neuroscientist Anne-Laure Le Cunff on using AI to set and achieve goals

MOLLY WOOD: Today I’m talking to neuroscientist, educator, and writer Anne-Laure Le Cunff, who created the immensely popular Ness Labs newsletter, which she describes as an exploration of how we can learn how to experiment with ideas, explore creative projects, make better decisions, and reflect on your progress. She is also the author of the new book, Tiny Experiments: How to Live Freely in a Goal-Obsessed World. I cannot wait to hear more about this. She joined us to share insights on why goal setting is broken, how we can use experimentation to improve productivity, how our brains process uncertainty, and how AI can help optimize our approach to all of these areas. And now my conversation with Anne-Laure. Welcome.  

ANNE-LAURE LE CUNFF: Thanks so much for having me.  

MOLLY WOOD: So, I want to start with your newsletter and your book. You’ve written a lot about applying lessons from neuroscience and just the basic methodologies of scientific research to productivity and processes and decision making. What would you say are some of the key takeaways? 

ANNE-LAURE LE CUNFF: It took me a long time to formulate it as I am going to give it to you right now. But the main insight that is covered is that we should always default to curiosity, whatever challenge we’re facing, whatever roadblock, whatever area of doubt. If you decide to approach it with curiosity, you’re not only going to find a solution faster, but it’s also probably going to be a lot more fun. 

MOLLY WOOD: There’s also this phrase that kicks around in your work, mindful productivity. What can you say about that and why it’s so important for business leaders? As opposed to mindless productivity, which I think we can all understand. [Laughter] 

ANNE-LAURE LE CUNFF: A lot of people are a bit confused about this term, mindful productivity. You feel like mindfulness, productivity, like, that doesn’t really go together. The way I explain it is to go back to the definition of mindfulness. Being mindful really just means paying attention without judgment. And that’s what mindful productivity is about. It’s about paying more attention to how you feel, to your output, but also to the experience of producing this output. Paying attention to the way you communicate with others, to the way you manage your time, your energy levels. And then without judgment, a little bit like a scientist, just asking yourself, what can I do better? What can I experiment with? What can I tweak? What can I approach differently? And how can I collaborate with others to be more productive without sacrificing my mental health?  

MOLLY WOOD: I kind of flippantly said, we can all understand what mindless productivity is, but now I kind of want you to define that too. I think we’re going to understand it better in opposition.  

ANNE-LAURE LE CUNFF: Yes, mindless productivity, I think, is best defined by the outcome. What happens when you do that, right? And it’s simply burnout, overwhelm, for a lot of people. And the reason why they don’t notice those early signs is because they are mindlessly grinding and hustling and going through their to-do lists and never paying attention to how they actually feel. The focus in mindless productivity is really just on the output itself, how efficient you are, how quickly you can produce the work, but not on all of the other factors that are incredibly important if you want your work and your pace to be sustainable.  

MOLLY WOOD: Okay, so then we have these two frameworks, enter AI and a whole new level of conversation about productivity. How do you think AI will help us, or hinder us, in terms of fostering this idea of mindful productivity?  

ANNE-LAURE LE CUNFF: That’s what I find fascinating with AI, is that depending on how you use it, it could really support either mindful productivity or mindless productivity. I like ending on a positive note, so let me start with mindless productivity and how, unfortunately, that might be the most tempting approach in terms of using AI. And that’s really just trying to get AI to do your job, whatever it is you’re doing, in a mindless way, trying to use it to replace you. In order to—again, that’s where the focus is, the focus is on output, right? You just want to produce your output, whatever it is, faster. You want to go through your to-do list faster. A mindful way of using AI to be more productive would be to collaborate with AI to figure out which tasks should be the priority, how to do them better, how you could collaborate with others to perform these tasks in ways that might have been difficult for you to imagine because you didn’t have access to all of that information. And so, in a way you can do your work better, not faster necessarily, but better. And I think to me, that’s the mindset shift that people need to have when it comes to AI: not seeing it as a tool to necessarily just be more productive, but just produce better work.  

MOLLY WOOD: You know, at this moment, we’re talking about this kind of at the individual level. I wonder how this starts to rise up to leadership. How do business leaders foster exactly the kind of work and partnership that you’re talking about?  

ANNE-LAURE LE CUNFF: To me, that’s only possible if we remove the sense of shame there is around using AI at the moment. In a lot of organizations, a lot of individuals still have to use AI in secret, where they will perform several tasks and they will manage to finish the presentation, do the three reports, code three applications in one weekend, come back on Monday and say that they did it all on their own, because there is, again, a sense of shame around the fact that you’re not able to do all of these things. And using AI kind of, you know, is sometimes perceived by people who haven’t really used it themselves as a way to take shortcuts. So, to me, in order to harness all of those benefits of AI at a team level, leaders need to make it very clear that it is okay to use AI. And even better than that: it’s encouraged to share with others how you’re using AI so everybody can learn together. And I would go as far as creating spaces for conversations where you ask people on your team, okay, how did you use AI this week? And can you share with the team? What did you learn? Did you discover anything new, anything cool that we could use as well? If you create this culture where AI is smart and a mindful use of AI is celebrated, then you are going to harness all of its benefits. Ultimately, this is a tool that can be used in lots of different ways. And if you want your team to learn faster and better how to use this tool, it’s better if everybody’s learning together rather than hiding the fact that they’re using it.  

MOLLY WOOD: This also raises this question of this whole idea of, I think, a permission structure and support points to the fact that there is so much uncertainty and fear about this at the leadership level, and then certainly at the employee level. So talk about addressing that uncertainty so that we can create this support and permission.  

ANNE-LAURE LE CUNFF: I think it’s useful first to understand why we fear uncertainty in the first place. It makes sense from an evolutionary perspective. Our brains were designed to help us survive. And so if you go back thousands of years, the more information you had, the more likely you were to survive. You needed to know who were the players, where the resources were, what was that weird noise in the bushes, right? Today in our world, our brains haven’t evolved that much. We also seek the sense of certainty. We want to feel like we know. We almost feel like we want to be able to predict the future, but obviously we can’t. Today’s world is changing so fast. Technology is evolving incredibly fast as well. Even us as individuals, we are exposed to so much information that we probably change faster also compared to our ancestors in terms of our identities, our values, and our desires. So the way our brain works, which was designed for survival, doesn’t work so well when what you want is not just to survive, but to actually thrive. And so just understanding this and saying, okay, thank you, brain. I know you’re trying to protect me, I understand that, but we’re actually not in great danger right now and we can actually explore and we can experiment. So I think that’s the first step, is just being okay with the fact that this is a natural response from your brain. And it’s okay if you’re feeling a little bit of anxiety when you’re in a situation that you don’t fully understand, which is the case right now in today’s world. And then the second stage is to kind of flip the script here, going back to what uncertainty is, which is a state of unknowing, you don’t have all of the information. That can actually be amazing. That can mean that you have a space for experimentation, you have a sense of possibility. Anything is possible. You can try new things and see what happens. What I recommend is to think about uncertainty like a scientist. When a scientist is faced with something they don’t understand, they don’t freeze. It’s the opposite. They look at it and they say, Huh, what can I learn from this? This is interesting. What kind of experiment could we design around this? And at an organizational level for leaders or individuals, just training yourself to approach uncertainty this way and saying, I don’t quite understand what’s going on here. I clearly don’t have all of the information. Things are changing very fast, but what can I learn? And what are some interesting possibilities that arise from the space of uncertainty?  

MOLLY WOOD: I mean, I think a lot of leaders are realizing they can use AI as a thought partner to help them with their thinking, right? Like, they can use it to help them evaluate their decision making and their strategies and their priorities. Like, this is metacognition, right?  

ANNE-LAURE LE CUNFF: Yeah, I actually write a lot about metacognition in my work, and I think this is a uniquely human skill that can actually be enhanced with AI. So, metacognition sounds like a fancy word, but all it means is thinking about thinking. And the reason why I say it’s a uniquely human skill is that we know that a lot of other animals are able to think, but we probably are the only ones that are able to observe our own thoughts, which is amazing, right? We can ask ourselves, why did I think that? Is that thought more logical than this other thought? What would happen if I shared that thought with another thinking being, and if we found the intersection of those two thoughts together? Those are the kind of things that only humans can do. And AI is amazing in the sense that instead of running around and trying to grab a colleague every time you have an interesting thought and you want to see what they think about it, you can just type it up or record it, record a voice note, and send it to an AI that will reply to you and help you. Basically, they will become this thinking partner for you and practice metacognition together.  

MOLLY WOOD: You know, AI is getting good at cognitive work, and people are using AI as a thinking partner around ideation and creation. And there is fear and pushback around that. And I wonder, you know, how do we sort of continue to talk about this as an opportunity? 

ANNE-LAURE LE CUNFF: To me, it’s actually really exciting what’s going to become possible with AI helping us with those cognitive tasks. And I think a useful parallel is to think about the discourse we had when the calculators were invented. It is absolutely true that a lot of people are not able anymore to make complex calculations just in their mind, right? You have to take a calculator and you type it up in there and you get the result. But now just look at how the world has evolved. Is that really a bad thing? Is that really something— 

MOLLY WOOD: Not for me. 

ANNE-LAURE LE CUNFF: Exactly. And I think that’s completely fine. And also, so this has allowed more people to be able to make those calculations because a lot of them would have not been able to make them in the first place. So that has given access to complex calculations to a lot of people who wouldn’t have that access otherwise. And second, it has also allowed us to work on much more complex projects that were enabled by the fact that we had access to those calculators. To me, AI is going to be the same. There are probably a lot of cognitive tasks that we’re not really going to perform anymore. But I think in a few decades, people from the next generations are going to look back on those tasks that we do today and feel like, I can’t believe you were spending all of that time on those tasks. When now we freed up that time and we’re able to actually focus on true human creativity.  

MOLLY WOOD: I want to go back to the thing that you said about approaching problems like a scientist, because we are so at this stage right now where every day you find out a new thing that you can do—a new option, a new possibility. And that is experimentation and the process of experimentation, which can be anathema sometimes in business because it raises the prospect of failure or wasted time. So talk about the importance of thinking like a scientist at work.  

ANNE-LAURE LE CUNFF: I want to first debunk an assumption that people may have when it comes to experimenting at work. When you embrace an experimental mindset, it doesn’t mean that you have to experiment with every single thing all at once, right? There might be areas of the business where things are actually working very well, and more of the same is the right approach. Having an experimental mindset is just about being intentional, about where you keep on doing things in the same way, and where you might benefit from reopening that experimental window and questioning your assumptions and just saying, is the way we’ve been doing things really the only way to do this, and is that the best way? And so what I would recommend in general, as part of a team, is to have a couple of experiments running at all time, but that doesn’t mean everything is an experiment. So, picking a few things where you say, actually, you know what, for the next quarter or the next semester, we’re going to approach this particular area of the business or product development in a slightly different way. And at the end, we’re going to look at the data together and decide whether we want to keep going, whether we want to tweak it, or whether that was actually not working really well for us and that’s it, but now we know. So that’s the first thing, just debunking that assumption. The second one is that when you start experimenting, your very definition of success and failure starts changing. Because when you have a very linear approach to work, and you say, this is the outcome, this is the milestone that we need to get to with this—again, the sense of clarity that, this is where we want to go. We have a clear vision, a clear plan, and we’re going to get there. So there is a very binary definition of success and failure. Either you get there or you don’t. When you experiment instead of trying to climb this ladder and get to that destination, instead the mental model is a growth loop. You are going through cycles of experimentation. That means that you don’t start from a specific milestone or destination. You start from a hypothesis or a research question. You notice something interesting where you’re not quite sure. There is some uncertainty around an area of the business, something that you’re curious about, and you say, what if, what if we did things differently? What if we tried that? And the only objective when you experiment is not to get to a specific destination, it’s to learn more, just like a scientist. They collect the data and they don’t try to get a specific result, they just want to learn more. That’s the mindset shift that you want to have here.  

MOLLY WOOD: Got it. And just to repeat it, you call it a growth loop, like the idea that the more you repeat that process the bigger your loop gets, the bigger your knowledge set gets. 

ANNE-LAURE LE CUNFF: Exactly. And I compare the mental model really of the ladder and the loop: the ladder with this clear destination where you climb and you try to get there, and the loop that where you keep on growing and you can trust the process. You are going to grow. You are going to expand your expertise and your knowledge, even though you don’t have a clear five-year plan. 

MOLLY WOOD: Something about the way our brains work that you have talked about is what happens to your brain when you’re learning something new, and this phrase thirst for knowledge that I just want to capture from you because this is fascinating.  

ANNE-LAURE LE CUNFF: Yeah, absolutely. They’ve conducted some fascinating research that shows that in primates’ brains, when we feel thirst for water, the exact same networks in our brains light up than when we feel thirst for knowledge. So when we say that we’re curious and we have this thirst for knowledge—the word thirst, there couldn’t be a better word to describe that feeling that we have.  

MOLLY WOOD: What is one question you wish more people would ask you about neuroscience and its application to work and life? Like, why are we not thinking more about our brains?   

ANNE-LAURE LE CUNFF: Well, you just asked the question I would ask to other people, I think. [Laughter] Why aren’t we thinking more about our brains? I think, actually, this is a great question. I think we should think more about our own thinking. We should spend more time observing our own thoughts, connecting with our emotions, and really turning our attention inwards. 

MOLLY WOOD: And while we’re talking about our brains, you’ve actually written about this idea that you call the illusion of certainty, which is very compelling and common. What’s going on in our heads that leads to that illusion, and how do we get rid of that?  

ANNE-LAURE LE CUNFF: Yes, that connects back to what we discussed earlier about why our brains really try to resolve uncertainty as quickly as possible. And because of that, we will try to hoard information. We will try to get as quickly as possible to the most immediate answer, the one that is going to give us that sense of certainty. But unfortunately, that sense of certainty is very often an illusion, because we went for the most obvious answer because we’re basing our sense of certainty of the fact that we spend three days reading nonstop about all of the news about a topic, which is not really how you build certainty. And so just accepting that being a hundred percent certain about what the future looks like is impossible. That’s impossible. All you can do is make predictions, know that these are just predictions, and then adjust your direction based on those predictions.  

MOLLY WOOD: You have given an example, again, just in terms of interacting and thinking through issues and processing, if you will, this example of how you have conversations with research papers. Can you tell us more about that?  

ANNE-LAURE LE CUNFF: This is one of my favorite features when it comes to using AI. So, in my academic research, I’m supposed to read dozens of research papers every week—that can take a lot of time. And unfortunately, sometimes you get to the end of the paper and you realize that there was nothing relevant or interesting in there that you can use for your work. So what I’m doing now is that I take the paper, I upload it to AI, and then I ask questions. I have a conversation with the paper and I can ask, okay, tell me what research methods were used here, and because the AI knows what I’m working on also, what are points that you think are relevant based on what I’m working on right now? And another one that I find absolutely amazing is asking, what are the limitations that are mentioned in the paper explicitly, and what are limitations that you notice that are not mentioned in the paper explicitly? And in this way, the AI is really helping me having those conversations. I feel like I’m having a coffee chat with the researchers that tell me all of the juicy stuff that they didn’t include in the paper. Because papers are so short, sometimes you don’t have that much space, and I can use those insights to make decisions as to whether I’m going to use this paper in my own research or not. But it’s not only saving me time, it’s making the entire process of finding that information and reading papers a lot more enjoyable.  

MOLLY WOOD: What’s sort of one question that you wish more people would ask about the potential of AI at work, right? This is like really a mindset question. What should they be asking about how to use this well?  

ANNE-LAURE LE CUNFF: If you could focus a hundred percent of your time and energy on the things that are at the intersection of what you’re good at and what the world needs, what would that look like? Because I think that’s what AI can unlock: freeing your time, freeing your energy, freeing your attention from the things that are, that should not be your main area of focus and creating more space for your creativity.  

MOLLY WOOD: If our listeners could take away one actionable insight from your work, just one, what would you want it to be? 

ANNE-LAURE LE CUNFF: I would like for them to look at the way they’re doing their work at the moment and, or the way they’re living their life in general, and ask themselves, what’s one area where I could be a little bit more experimental?  

MOLLY WOOD: So we love to ask our guests how they’re using AI in their work and maybe some use cases and techniques that have really been a game changer. Do you have any examples for us?  

ANNE-LAURE LE CUNFF: Oh, absolutely. I use AI a lot at work. It’s really a thinking partner. Anytime I’m in doubt, and I would normally grab someone at the coffee machine and just say, hey, can I pick your brain? That’s AI now. I just do that, and I explain I’ve been facing this challenge, I’m feeling a little bit stuck, and do you have any ideas? And usually even when the AI comes back with just a few bullet points, that’s enough sometimes just to give me something to think about and getting unstuck. And very similarly in my personal life as well, I will use it as a tool for brainstorming. I think across the board, really getting unstuck for me is the key phrase in terms of how I use AI at the moment. It makes me think more creatively. It suggests avenues for exploration that I might not have considered in the first place on my own. And it also helps me clarify sometimes my own thoughts, where I can just dump literally anything that’s on my mind and it will come back with a more structured version of what I’ve been thinking about, which is incredibly helpful. 

MOLLY WOOD: Okay. Fast-forward three to five years. What do you think will be the most profound change in the way we work?  

ANNE-LAURE LE CUNFF: I think a lot more people will have the beautiful privilege to be able to explore their creativity and to do work that feels meaningful to them, thanks to AI.  

MOLLY WOOD: And then, what do you think will be hallmarks of organizations that do this well—frontier organizations that will really pull ahead in this new era?  

ANNE-LAURE LE CUNFF: You probably know what I’m going to say, but I’m going to say it anyway, because I think it’s so important, but creating safe spaces where it’s okay to explore your curiosity, where it’s okay to use AI in experimental ways, and where it’s okay to make mistakes and learn in public. To me, those are going to be the hallmarks of any organization that is at the frontier of what’s possible with this new technology.  

MOLLY WOOD: I mean, it seems easy, but how do you create those spaces? Like, how do you foster creativity and let people feel safe throwing out what might actually be bad ideas?  

ANNE-LAURE LE CUNFF: I love that you’re asking this because it’s the same with embracing uncertainty. When you tell people, embrace uncertainty, they tell you, what do you mean? Am I supposed to just relax my shoulders and embrace it? And it’s the same with curiosity, right? How do you actually foster a culture of curiosity and experimentation? And in a very, very practical way, what I would encourage leaders to do is to block some time—you can call it curiosity hour—block some time, put it in your team’s calendar, and say that that’s the hour where every two weeks or three weeks or every month, whatever works for you, everybody is going to share something they experimented with and the results. Did it work? Did it not work? What can we learn together from this? And that’s it. That would be the simplest small steps that they could start taking right now.  

MOLLY WOOD: And then if I were going to try to tap into my curiosity with an AI thought partner, let’s say I’m stuck. What might I say?   

ANNE-LAURE LE CUNFF: Well, first you can tell the AI, I’m stuck. I think that’s a great place to start. It’s okay to just type I’m stuck. Here’s the issue. Here are some things that I’ve been thinking about, some options, some ideas. None of them feel quite right. What do you think? I’m stuck. Insert problem. What do you think?  

MOLLY WOOD: Just building off of curiosity one last time, how do you tap into yours? Do you have a favorite method?  

ANNE-LAURE LE CUNFF: So I have several methods. The main one for me is to journal. I journal every morning, and sometimes just for five minutes. And part of the prompts that I’m using is, what am I feeling curious about today? And so I always try to have that little connection with my curiosity every day. And then outside of that, I really try to treat my curiosity with a lot of respect, actually. I listen to it. If I feel like I’m curious about a topic, if I’m curious about an idea, a new product, a new technology, even if I feel like right now is not the right time to explore this, that it could distract me from something else, I have a curiosity inbox in my note-taking tool where I will just type that, put it in there, and then I have dedicated time that is a little bit like opening a box of candies where I can pick something and then go and explore. 

MOLLY WOOD: Thank you so much. Anne-Laure Le Cunff is a neuroscientist, educator, author of the Ness Labs newsletter, which I’m sure you have been convinced to read if you are not already, and also author of the new book, Tiny Experiments. Thank you again so much for the time.  

ANNE-LAURE LE CUNFF: This was great. I really loved our conversation. Thank you.  

MOLLY WOOD: Thank you all for joining us, and keep checking your feeds. We have more fascinating guests on the way with actionable insights that can help leaders develop an AI-first mindset, reorient their business for an era of abundant expertise, and maximize the ROI of AI. If you’ve got a question or a comment, please drop us an email at worklab@microsoft.com, and check out Microsoft’s Work Trend Indexes and the WorkLab digital publication, where you’ll find all our episodes along with thoughtful stories that explore how business leaders are thriving in today’s new world of work. You can find all of that at microsoft.com/worklab. As for this podcast, please, if you don’t mind, rate us, review us, and follow us wherever you listen. It helps us out a ton. The WorkLab podcast is a place for experts to share their insights and opinions. As students of the future of work, Microsoft values inputs from a diverse set of voices. That said, the opinions and findings of our guests are their own, and they may not necessarily reflect Microsoft’s own research or positions. WorkLab is produced by Microsoft with Godfrey Dadich Partners and Reasonable Volume. I’m your host, Molly Wood. Sharon Kallander and Matthew Duncan produced this podcast. Jessica Voelker is the WorkLab editor.