Jonathan Cutrell

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The Error of Discounting the Unexpected

We don't think about the unexpected as a category of possible outcomes. This leads us to assign overestimated probabilities to things that are front of mind, and discount the likelihood of things we don't expect. This may lead us to prepare for expected events without consideration for what we'll do in the face of the unexpected.

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Transcript (Generated by OpenAI Whisper)
I want you to think about everything that could happen today. Think about the to-do list that you have, the different decisions you have to make. How will they go? How could they go? Imagine just one of those decisions. Take a moment if you can, and write down a couple of options, a couple of ways that that decision could go, and assign probabilities to each of those outcomes. This information that you are generating is incredibly nuanced, but it's also incredibly valuable. And getting really good about thinking about these kinds of probabilities could totally change your life and your career. But I can almost guarantee you're missing something. And we're going to talk about what that is in today's episode. My name is Jonathan Cutrell listening to Developer Tea. My goal on this show is to updriven developers like you find clarity, perspective, and purpose in their careers. As we've talked about many times on this show, trying to make a decision is an exercise, it's an exercise in trying to predict the future. You imagine that you have some intended outcome, and that you want the decision to produce that outcome. We know, of course, we've talked about this even recently on the show and in the distant past, that outcomes are not always indicative of a good decision. We talked about this in the last episode, actually. And a good decision is not determined based on the outcome for a given instance. Over time, if you make statistically good decisions, if you make decisions that are in your favor, then your decision should match the profile of those statistics. That doesn't mean that you're going to win most of the time. Maybe you take a lot of bets, and you really only need to win once. But ultimately, if you're assigning these probabilities, you can almost guarantee that you're missing something. The reason for this is because we tend to assign probabilities based on what we imagine could happen. We imagine that we know all of the possible outcomes, but this discounts a very large portion of outcomes that we never thought about at all. We're going to talk about a way to try to correct for this error in thinking, right after we talk about today's response. This episode of Developers is brought to you by Square. There are millions of sellers across the globe using Square. You already know that because you've almost certainly bought something, spent money through Square. They're using it to run every aspect of their business, but you can come in and help them build custom solutions so they can integrate more deeply with their business in the first place. They're looking for these custom solutions, and that's your opportunity. You can build your business. You can grow your business by extending or integrating with Square using their free APIs and SDKs. These are tools that you can build for sellers. It's waiting for you at slash Square. There's a huge opportunity. slash Square, you can build these deeply connected tools, these custom solutions for sellers, millions of sellers across the globe. It's slash Square, thanks again to Square for sponsoring today's episode of Developer Tea. The error in our thinking about the statistical likelihood, like the probability that a given thing will happen, a given outcome will take place. Typically, we have an idea of the different categories of potential outcomes, but we often are wrong in sometimes minor, but often very large, major ways. This is especially true if the outcome depends on nuance. If it depends on, for example, what another human will decide to do, and many of our outcomes do indeed depend on this. For example, you could imagine having a conversation with a coworker and the intended outcome that you'd like to have and assigning a probability to that intended outcome. Then other outcomes that are not intended or other outcomes that are not ideal. You could assign those probabilities, and I'm guessing that most of the time, your probabilities come close if you were to sum them all up, and come close to 100%. But the truth is, there's a very large array of options of outcomes that are not in your list of predicted outcomes. In other words, you imagined a set of outcomes, but the list of all possible outcomes is much larger. And the ones that are not on your list deserve some level of probability. If they are possible, then they have some probability. Now, I want to be very clear here. It is not necessary to imagine every possible outcome. For many outcomes, the probability is so low that it's not necessarily worth considering. But this often becomes justification for imagining that the probability of all of those uncertain outcomes or unlikely outcomes is low enough to not consider at all. So here is an exercise to observe this in action. I want you to take a mental field trip. Try to remember what it was like to be you ten years ago. Try to embody that for a second. Remember what you were listening to, what you were wearing, where you were, what a typical day looked like. Now imagine the next two or three years. What did you think was going to happen? Where did you think you were going to go? What kind of job did you expect to take at that time? Or what kind of project did you think you were going to work on? Did you think you would progress faster or slower in your career than you did? For almost everyone listening to this show right now, the picture that you had ten years ago of where your life would be even just seven years ago was wildly inaccurate. Now this will prove it even further. Imagine that same feeling of ten years ago. Trying to predict where you would be today. Where will you be in ten years? Now here is the proof at work. What is your confidence that you could predict where you would be today ten years ago? In other words, if you could rewind time, not knowing anything about the last ten years of your life, did the version of you ten years ago accurately predict with any level of confidence what would happen in the next ten years? Where would you be even what job do you have? It doesn't have to be every aspect of your life, but maybe just the five most important ones that define what those ten years look like. Almost everyone that I've talked to that I do the exercise with answers that they could never have imagined where they are today ten years ago. They never would have imagined that they listened to the music they listened to. They participated in the hobbies that they're participating in. They live in the kind of house or the kind of apartment. They own that particular kind of car they never could have predicted it ten years ago. Now where will you be in ten years from today? Do you have a higher confidence? This is the critical question. Do you have a higher confidence in your ability to predict where you'll be in ten years from today then you have in your ability to predict ten years ago where you would be now? In other words, do you think you've gotten better at this prediction? Setting aside the fact that we have a lot more variability in our younger years, let's say from age 18 to 28, that we might have from 28 to 38, there is still a large possibility of variation over the course of ten years. And so if you have a drastically higher confidence in your current ability to predict the next ten years, then you have in your past self to be able to predict where you are today, then there's a mismatch. This is a very common bias that we have. We imagine that somehow our predictions of where we are now and where we're going are more informed or we have more experience, something has given us a better prediction engine today than we had before. This is why retrospective is so important to our work. This is why looking back on decisions that we've made and the outcomes that were generated from those decisions, it's why it is so critical. How often does an outcome surprise you? Amazingly, even this is a hard question to answer because we have such a sense-making bias. This is the tendency to make sense out of the world. That when we see an outcome, we post-rationalize. In other words, we look back and we draw conclusions about what we should have predicted. This changes whether or not we feel surprised about a given outcome. The only way to know for sure if we are telling the truth to ourselves, if we should say that we were surprised, is to look at those predictions. Take that list that you generated today and compare it to the real outcome. What you'll likely feel is that you should have predicted a given outcome based on your post-rationalization, but you didn't. For some reason, things didn't go as you expected them to go. If there's any takeaway that I want you to take from this episode, if there's anything I want you to remember, it's that the category of outcomes that you're not explicitly expecting is often much larger and much more likely than you could imagine. The possible outcomes, that category of potentials, this category is larger and more likely than you expect. Now, this has implications into how we make decisions in our daily lives. For example, if there's something that has a high potential for an uncertain outcome, if there's something that we don't know a lot about, it's a new decision, a new area that we've never explored, then maintaining flexibility has a higher premium. In other words, your ability to respond to an unexpected outcome, that becomes more important when there is a larger chance of the outcome being unexpected. Ultimately, we would all stand to benefit if we had a little less confidence in our ability to predict and a little more belief that unexpected things happen more often than, well, we expect. Thanks so much for listening to today's episode of Developer Tea. Thank you again to today's sponsor Square to get started with their SDKs and APIs for developers, head over to slash square. If you enjoyed this episode and you don't want to miss out on future episodes, make sure you subscribe and whenever podcasting up your currently using, and if you want to join in on the conversation with other software engineers who are looking to improve in their lives and in their careers every day, head over to slash discord. This is a discord community that's totally free to join. There's no hooks, there's no catches to that. It's just a community of people who are improving on a daily basis, sharing their ideas, their questions, their stories with you, that's slash discord. Thanks again for listening and until next time, enjoy your tea.