Ambiguity Effect: The Hidden Reason Your Roadmap Keeps Playing It Safe

Speaker A: But let me offer you a bet. Two features in the roadmap. You can only ship one. The first one, your team knows inside and out. You built something like this last quarter. You've got the metrics, you've got the benchmarks. You've got a clean story for leadership. You can see exactly how it plays out, and you can make a good estimate of the overall impact. Well, the second one? No idea. Could be your biggest hit of the year. It could be a total flop. Your team has never built anything like it. There's no precedent. There's just a hazy fog where the certainty is supposed to be. Let's assume they've got the same potential upside. On paper, both could win. So which one do you pick? Well, if you're like almost everybody, you go for the feature that you know, not because it's a better bet, but because the other one is a mystery. And your brain really, really doesn't like mysteries. And here's the part we'll dig into today. You didn't choose the safer option. You chose the clearer one. And those aren't the same thing. The unknown feature might have been the smarter play. You'll just never find out because the ambiguity scared you off before you gave it a fair shot. That instinct has a name, and it's quietly steering more of your decisions than you'd guess. So stick around. What's up UX Fam? Welcome to another edition of the Cognition catalog, where every week or so we'll dig into a new cognitive bias and explore how that bias can impact how our team works together and what we can do to ensure we don't get caught up in the pitfalls. Because working with people is hard, and the more insights we have into the human condition make it just a little bit easier. Learn more about the ambiguity effect. You can find More resources@cognitioncatalog.com Sign up for the newsletter to get a new bias in your inbox every week. And make sure to subscribe wherever you listen to podcasts so you never have to worry about falling for any of these cognitive biases again. And if you think you're getting something out of the show, then I would love it if you left a five star review. That would help me out so much. And shout out to this week's sponsor, Maubin. If your team is tired of reinventing the wheel every time a new project kicks off, well, give Maubin a try. Maubin gives you access to over 600,000 beautifully designed US screens and user flows, all searchable with AI it's the kind of tool that makes the whole team faster. So visit mabin.com beyond ux to get 20% off momin pro and see why more design teams are making it a company wide staple in 2026. And as always, thanks so much to Chris, Siroquan, Stacy, Radu, Megan, Andrew, John, Mark, Kevin, Jason, Michelle, Marty, Tino, Adena and Zoe for all their support. And for more information how you can support the show and help more people find out about what we're doing, make sure to check out beyond uxdesign.com support. And of course if you think the show's worth sharing then I would love it if you told some friends so that roadmap bet isn't really a one time choice. It's a pattern. And once you see it, you'll spot it everywhere. Hello, frequency illusion. Picture a normal planning meeting. Now the team's deciding what to build next quarter and two ideas bubble up to the top. Uh, the first one? Familiar territory. Maybe it's an improvement to a feature that you've already shipped. Everybody can picture it. Leadership was excited about the results last time. The estimates feel solid, the risks are known. The second one is newer, it's fuzzier. It might open up a market that you've never touched or solve a problem that nobody's cracked yet. But there's no playbook for it. The projections are just guesses and nobody can say with confidence how it will land. So watch what happens next. The conversation will almost always drift towards the familiar one, not through some big debate, but but it'll likely happen more quietly. That new idea gets some excitement at first, then a few more questions than the safe one gets. People start to ask for a little more data before we commit. Then it'll start to just slide down the list. Other features get pushed above it, and by the end of the meeting, the known option is green lit and the unknown one is parked safely below the line. And everybody walks out feeling responsible, feeling measured. Like they made the disciplined call. But here's what actually happened. The team didn't weigh both ideas evenly and pick the stronger one. They picked the one they could safely predict. The fuzzy idea never lost on its merits. It lost because it was harder to predict, and that discomfort of not knowing did the rest. This is the ambiguity effect and it doesn't announce itself. It hides inside reasonable sounding caution. Let's wait for more signal. Let's start with something proven. Each one sounds smart in the moment. Together they quietly tilt the whole team toward the familiar. Almost Every single time. And it's not just roadmaps. It's that new hire who's work gets a little bit more scrutiny. That unfamiliar tool feels riskier than the one that everybody left. Those stack overflow comments about the bold research direction loses to the safe one because the safe one is easier to defend. Now, the thing the team keeps avoiding isn't risk. It's the unknown. And those two things are not the same. So what is the ambiguity effect? Well, we tend to avoid the unclear when we can't see how something will turn out or even read what's happening right now. Our brains treat that fog as a threat, and it steers us towards whatever feels more defined. The discomfort isn't really about the odds. It's about not being able to make sense of the situation at all. And we'll trade a better but blurry option for a clearer one almost every time. The research behind this bias starts with a clean little thought experiment about gambling. The bias got its formal start with economist Daniel Ellsberg In 1961, almost a whole decade before he published the infamous Pentagon Papers. And in a paper on decision making, he laid out a thought experiment built around two jars of colored balls and predicted how people might choose. The first jar held exactly 50 red and 50 black balls. You could see the split. The second jar also had 100 balls, but the mix was hidden. It could have had anything from all red to all black, with no way to know. Now, picture being offered a bet on pulling a red ball. Which jar would you choose? Now, think about what's actually hidden in the jar. It might be stacked in 99 black and one red button, which would be awful for you. It might be 99 red and 1 black, which would be great for you. Now, with no information pointing either way, every lopsided possibility is balanced by an equally likely opposite. Your best guess for the hidden jar lands right back at 50 50, every time the same as the jar that you can actually see. Now, on paper, the two bets are worth the same. So why do most of us still choose the visible jar? Because the jar you can see hands you 50% for sure. The hidden jar gives you 50% on average. But the real odds are out of sight, and they might be terrible. Now, that unseen possibility, the chance that you've badly misjudged the whole thing, is what people are running from. Not bad odds. It's unseen odds. And that's essentially the ambiguity effect. People take a, uh, guaranteed coin flip over a mystery, even when the mystery is, on average, exactly as Good of a deal. Ellsberg actually sketched out a second, more complicated version too, with a single jar of red, black and yellow balls. And this is the one that most people tend to cite today. But the two jar setup is way easier to explain here, so we'll just stick with that. Anyway, almost everyone reaches for the one that they can see. Ellsberg predicted exactly that, and the researchers who tested his idea over the years found that he was right. This held up across decades of follow up work. Researchers ran variations on Ellsberg's setup and the preference for the known option kept showing up. Even when they explained the logic to people and walked them through their own reasoning. The pull towards the visible jar shrank, but it never fully went away. Humans are just sort of stubborn that way. And it kind of drives me nuts when I hear economists talk about how rational humans are. Because obviously humans are anything but rational. Now, here's an important distinction and it's worth holding onto for the rest of this episode. Risk is when you know the odds, even when they might go against you. Ambiguity is when you don't even know the odds at all. Now, uh, those are two different things, and the second one bothers us a whole lot more than the first one. We can often stand to deal with a known long shot more easily than we can stand to deal with a complete unknown. Now, why is the unknown harder to stomach? Because missing information gets processed by less like a math problem and more like a threat. When we can't fill in the gaps, an older part of our brain assumes that the gaps are hiding something dangerous. So we default to the option that we can fully picture and we steer clear of the one that we can't. It's a remnant of our old hunter gatherer brains. And that's also why the effect gets stronger as the stakes go up. A trivial guess doesn't really bother us all that much. But when the outcome matters, the discomfort with the unknown gets even sharper and the instinct to retreat to the familiar gets even stronger. But when the outcomes matter, the discomfort with the unknown gets even sharper and the instinct to retreat to the familiar gets stronger. And the more threatened we feel, the more we crave a clear picture and the more we'll give up to get, uh, one. Now, long ago, in a world where the unknown genuinely could be dangerous, avoiding the unknown was a decent survival bet. The trouble is that the same reflex follows us into the modern day, into meeting rooms where the unknown is just a new idea, an untested market or a person that we can't read. Yet the people most exposed to it are the ones whose jobs jobs are built around making hard decisions with often incomplete information. Designers, product managers, engineers, researchers. The art of our craft is making decisions before everything is clear. Which means the ambiguity effect is quietly influencing every one of those decisions. Now, Team Wang the roadmap has a familiar feature for a known market with clear benchmarks competing for time and resources with a new feature for a new market with a fuzzy projections but maybe real upside. That familiar one is crystal clear. It comes with a story that you can tell leadership. So it tends to win, not because it's a better bet, but because the other jar is the hidden jar and nobody wants to stick their hand into it. The ambitious opportunity gets filed under too speculative and quietly shifts below the line. A genuinely novel design pattern has no precedent to point to. No pattern library entry, no competitor doing it already. And that absence is seen as a negative even when the idea is strong. The safer, more conventional direction wins because it's easier to explain. And easy to explain gets interpreted as more likely to work. That novelty gets penalized for the crime of being unfamiliar. A, uh, proven engineering framework with years of stack overflow answers feels safer than a newer tool that might be a better fit simply because the unknowns are visible in one and hidden in the other. The hidden unknowns feel scarier than the known limitations. So teams stick with what they can fully see, sometimes long past the point where it actually serves them. Now, so far, this is all about ambiguous things. Market an idea, a tool. Now, when the unknown is a person, more biases stack up and amplifies all of it. When the unknown idea comes from somebody that you don't know well, you're reading two blanks at once. That idea is unproven and so is the person behind it. A trusted teammate floats a half formed concept and everybody gives them the benefit of the doubt. Where a newer colleague floats the same concept and they get a wall of questions. That idea didn't change your ability to read. The source did. Now we tend to field this one a lot with new leaders. A new director, a new vp, a new executive, or even a new PM joins the team. And nobody can read them. They don't have a track record. There's no sense of how they'll handle pressure, no shared history. And that's ambiguity in human form. And the brain does its usual thing and fills the blanks with caution instead of giving them the benefit of the doubt. The trust has to be earned, not because the new leader did anything wrong, but because I can't read you yet quietly tells our brains to stay guarded. And that's the second bias that's worth naming so we don't blur them together. The new leader isn't just ambiguous. They're often part of the out group, not yet one of us. In group bias already shorts the trust that we extend to outsiders. So the two effects kind of stack. The person is hard to read and not part of the tribe. And that's a big reason leadership transitions feel so destabilizing and why an outside hire spends months earning trust that an internal promotion would have been handed on day one. But notice what's really driving all of this. It isn't that the new market is bad or that the new idea is weak, or that the new leader is untrustworthy. It's that we don't know yet. And we treat we don't know as probably bad. Now that's the thing I want you to really think about here. We are not neutral in a blank space full of unknowns. Our brains want to fill the space, and so it fills it with the least generous reading that it can. That new PM's point of question tends to look territorial instead of curious. That unfamiliar tool becomes a liability instead of an upgrade. That untested market becomes a risk instead of an opportunity. Now, we haven't uncovered any clarifying information yet, so our brains supply a placeholder. And that placeholder tends to skew dark dark and it pushes us to avoid it in favor of the known quantities. But that said, don't start thinking that the fix is pretending that everything's clear or trusting everything and everyone blindly. Instead, I want you to notice when I don't have a read on this yet is starting to shift into that's probably a problem. And ask whether anything actually justifies that jump, or whether your brain is just doing what it always does when it doesn't have all the facts. So what do we actually do about it? Well, here are a few places that you can start. First, treat I don't understand as neutral, not negative. The core piece of the ambiguity effect is filling a blank blank with the least generous guess available. An unfamiliar tool becomes a liability. An untested market becomes a risk. A new hire becomes a question mark. All before any real evidence shows up. Catch uh, the moment that your brain converts I don't have a read on this into this is a problem. That initial gut reaction is rarely true, and naming it out loud gives that unclear option. The fair hearing that it usually doesn't Get. Next. Separate unfamiliar from weakness. A new idea has no precedent to point to. No pattern library entry, no competitor already doing it. And that absence feels like a flaw. But it's just that newness appears to us that way sometimes. Now, before you reject something for being hard to explain or hard to predict, ask whether you're reacting to a genuine weakness or only to the discomfort of not knowing. Next, Give unproven people the same benefit of the doubt. An identical idea lands differently depending on who it comes from. Newer voices draw more skepticism purely because you don't know them yet. Before pil unreasonable questions and pushback onto a new teammate's proposal, ask whether you'd scrutinize it that hard coming from somebody that you trust. Pay, uh, extra attention with outsiders, since unfamiliarity and outsider status compound into a distrust that many of us don't intend. Judge the idea on its merits, not on how well you happen to know the person behind it. Next. Extend more grace during transitions than feels natural. When a new leader arrives, the team faces maximum unknown at the worst possible time. Our initial instinct is often to stay guarded until they prove themselves. Now, the trouble is that that guardness interprets the leader's every neutral move in the worst possible light. And this makes earning your trust harder than it should be. That natural amount of grace that you extend to a newcomer is artificially low because your brain is treating unfamiliarity as a warning sign. Your gut will tell you to hold back and wait. But give a little more than that, knowing that your initial reading is skewed low by unfamiliarity alone. And then lastly, shrink the unknown instead of avoiding it. You don't have to choose between blind faith and playing it safe. When something feels too ambiguous to commit to look for a cheap way to reduce the fog. A small pilot for the untested market. A, uh, trial run with a new tool. A low stakes first project that lets you actually read a new hire. Turning a big murky bet into a small one buys you meaningful information instead of leaving your brain to fill in the gap with worst case guesses. But most of the time, nobody's making a bad call on purpose. They're just reaching for the option they can see clearly and backing away from the one that they can't. And that's what makes the ambiguity effect so hard to catch. It doesn't feel like a bias. It feels like being careful. And it feels like good judgment. But careful and clear aren't the same thing. The safest looking choice is just the one with the fewest blanks and the blanks are often with a better idea and the opportunities are hiding. You don't have to chase every unknown, you just have to notice when your aversion to ambiguity is quietly making that decision for you, and give the unfamiliar a fair shot before you pass on it. Well, all right y', all, that's it for the Cognition catalog for today. I hope I helped to shed a little bit of light on the ambiguity effect and how we can avoid some of those pitfalls at work. But I'm curious, have you run into the ambiguity effect before? How did it impact your team? How'd you get through it? I'd love to hear about it. Let me know what you think on LinkedIn or shoot me an email at hello beyond uxdesign.com I'd love to hear from you to learn more about the ambiguity effect. 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