What was the last time something bad happened in your career? Maybe you experienced a layoff or maybe you just had a difficult conversation with someone. Maybe a project ran late or you didn't get the promotion you were hoping for. These are all events that might easily be cast into the category of bad, of unfavorable. And none of these things yet is uncommon. It is not uncommon for someone to not get a promotion. It's not uncommon for a project to fail or to run late. It's not uncommon for a company to shut down, for layoffs to occur. All of these things are incredibly common. And yet because we have this inbuilt part of our brains, this observable bias, it's called the optimism bias. The optimism bias basically says that we assume that things will go favorably for us. Now, there's a lot wrong with this assumption. Hopefully, you can recognize this out of the gate. That we assume that the world will somehow make us lucky. That these events that are outside of our control, that we somehow will experience an irrationally positive version of events. And on average, this is not true. But there's another thing wrong with the favorability bias. And that is that favorability is somewhat subjective. Now, it's not entirely subjective. Things that are favorable for our survival, for example, are not usually considered subjective. Things that would have some kind of existential threat on your life. Those things not occurring, usually we would categorize those as favorable. If we are able to avoid disaster, that's a favorable outcome. But the vast majority of the things that occur in our day-to-day lives, especially in our careers, are relatively subjective. When I say relatively, I mean relative to those existential threats. And so, you not getting food for a fifth day in a row is a very different kind of favorability versus unfavorability. Because you're not getting a promotion. Now, you might say, well, if I don't get a promotion, then I don't get paid as much and I don't thrive as much. And I can tie that back to my survival. And this may be part of the pathway that makes us feel like that promotion is indeed a survival mechanism. But in reality, that promotion being a favorable event is not so cut and dry. In fact, it's very possible that you may get a promotion that causes you to spend more time at work. You may end up becoming less happy over time. You may end up becoming less physically active, perhaps having more stress in your life. And so is that a favorable outcome or not that you receive the promotion? Well, it's pretty complicated. Now, the vast majority of people would still probably categorize a promotion as a favorable event. And a lot of that is how you handle it. But let's look at another example that's a little bit more split. Let's imagine that there are two teams at your company, Team A and Team B. And Team A is working on something that you're personally particularly interested in. So you want to apply for a transfer for Team A. Is this a favorable event? If you get transferred to Team A? Well, if we look at another person who is more interested in whatever is happening on Team B, and they apply for a transfer and they get transferred to Team A, that might be an unfavorable event. You can see where this is headed. Favorability is not about the event itself. It is relative to you. What is favorable for one person may not be favorable for another person. Now, let's return to our optimism bias. We have the expectation that somehow the universe or some governing physics or metaphysical thing is going to help those things that are favorable to us occur. That somehow me getting on to Team A is more likely than another person getting on to Team A. That that favorable event is more likely to occur just for me. But this is an irrational way of thinking about probabilities. The dark side of this optimism bias, because initially it feels like a good thing. It feels like, oh, we're optimistic. We're looking forward to the good things. The dark side of this is that when a bad thing occurs, we have some sense that it shouldn't have. We have some expectation on the universe, on the world, on our lives, that the bad events, the things that are unfavorable to us, the things that, uh, irk us specifically getting on Team B instead of Team A, that these things shouldn't happen because we believe that they won't. As a part of that dark side of the optimism bias, if we believe that something is not going to happen, then we are also much less likely to prepare for the possibility that it will. We may not expect to get into a car wreck next week. So we may not expect to need an emergency fund. Due to the optimism bias, we may not expect to get laid off. And so we may not expect to need to cultivate our relationships so that we have a jumpstart when it's time to look for a new role. There are plenty of ways that optimism bias can put you behind. So in today's episode, I want to give you a few practical exercises you can take home, uh, and employ to start fighting back against this optimism bias. Now, notice that I'm not saying that you shouldn't be optimistic. Instead, we should recognize the difference between hope and expectation. If you're falling prey to the optimism bias, if you're not choosing optimism, if instead it is your default to believe that good things will happen by default, then you're not going to be prepared. If they don't, if you choose to be optimistic, however, you recognize that what you're doing is you're hoping for something to happen. And if you're not, even though you know that it's very possible that it won't. And not only is it possible, but you're prepared for if it won't. So here's the exercises. The first one is a risk log, a risk log. You could do this at whatever frequency, daily, weekly. Take a look at the various decisions that you're making or the projects that you're a part of, the teams that you're on, some kind of thing that has stakes, a decision that you are, participating in, or a direction that you're participating in that has some kind of stakes. And I want you to think about a decision that you feel fairly confident in. Something that you've done recently that you say, that you would endorse, that you would put your name behind it. Now with that decision that you made, I want you to outline the risks. Start with at least two or three risks that you are consciously aware of, and you start to think about, what are the risks that you're making? And then you start to think about the risks that you're making. Now, what this is doing is it's trying to break up that binary categorization. It's a common habit that we have to try to categorize things. And especially when we're trying to say whether a decision is good or bad, we believe this decision is good because it will lead us towards a favorable outcome. This is what your brain is telling you. But in all reality, every decision, virtually every meaningful decision, has a trade-off. There is a risk involved with every decision you make that is meaningful. So I want you to write down those risks. You can write them down for decisions. You could write them down for the team that you're on, for example, right? Let's say you're a manager of a team of software engineers. Write down the risks that you are accepting right now. The risks you're accepting in your role. Maybe the risks that your company is accepting in the market. There's a lot of ways that you can, kind of get closer to, and, you know, face those risks a little bit more head on. Once again, this is kind of blurring the line. So you don't have that binary categorization of good or bad, right? That this company is, you know, impenetrable, a perfect company. No, it's not. It's not perfect because there are risks involved in you being in that company. Identify those risks and face them head on instead of trying to only look at the positives, right? This is part of that, that optimism bias that we don't really want to, you know, confront the fact that there isn't a perfect answer to almost any question that we face. The second exercise is a broadly applicable technique in decision making, and that is a probability tree. Developing a probability tree for a major decision or let's say two major outcomes, three or four major outcomes, whatever you're trying to evaluate, really what you're trying to look at is what is the likelihood, right? What is my believed by the belief that I have in this particular outcome? What likelihood am I using as a basis for that belief? In this case, we're using belief as the term for expectation, right? So if you have an expectation that something is going to happen, then, then, then you're going to have to make a decision. And that's the second part of the exercise. It makes sense to assign in this, at least in this exercise, it makes sense to assign a statistical likelihood. What percentage likelihood does this carry? Is it 90% likely? Is it 55% likely? Or do you have a percentage likelihood? And that's the second part of the exercise. How do you justify the probability that you're assigning? And a lot of times what we'll recognize is that we're pulling these probabilities from some kind of gut estimation or maybe some experience, which doesn't necessarily have to be discounted, but it's worthwhile to explicitly identify what is making you believe that a particular outcome will occur. You may be able to directly observe that you have a belief that you don't have evidence to support. You have a belief, that let's say it's 75% likely, and you try to back that up, but you don't really have any reasons to believe that. Now, recognizing this, you may be able to then change your belief, saying that you're kind of updating your, your probability estimates, or you can identify that that gap between the evidence that you have and what you believe will occur, is based on something that you can't quite put your finger on. Again, at least you are able to assign, uh, that belief to some underlying rationale. In this case, the rationale is that you have some level of experience and you're using that experience to, uh, to inform your guesses. On this exercise, there is one final note of caution, and that is if you go seeking evidence for your, your claim, in other words, if you say, well, I have 85%, uh, confidence that this will happen, and you ask yourself to produce, you know, some proof, some rationale for that 85%, you're likely to seek out information that confirms your rationale. And this makes sense, right? We're trying to justify our belief and therefore we go and seek out information that justifies our belief rather than seeking out counterfactual information. So, be aware of this going in, uh, that instead of trying to seek out that information on demand, uh, you need to have a belief established when you walk in, uh, based on some kind of evidence, right? So your, uh, your probability tree, if you assign a number, it doesn't make sense for you to assign a number and then go and gather the evidence. Uh, try to gather the evidence before you assign the number. This won't completely eliminate the evidence. Uh, that confirmation bias, uh, but it will at least try to tamp it down, uh, by giving you the opportunity to set your number at something that, uh, that aligns with the evidence that you found. Thanks so much for listening to this episode of developer T. I hope this is insightful and insightful way to think about optimism bias and the dark side of optimism bias. If you enjoyed this episode, then you can join us on our developer T discord community. That's at developer T.com slash discord. Also, if you enjoyed this episode and you don't want this podcast to disappear, uh, we don't have any plans of disappearing, but one way to help us not disappear is to leave a review in iTunes or whatever podcasting platform you use. This helps other engineers, other managers, other creative people like you find developer T and choose to subscribe. Thanks so much for listening. And until next time, enjoy your tea. See you soon. See you soon. See you soon. See you soon. See you soon. See you soon. 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