The Psych Files

Author: Michael Britt

  • The Secret to a Good Joke Is Silence

    The Secret to a Good Joke Is Silence

    You’ve had this happen: you tell a story you know is funny, you get to the good part, and … nothing. Somebody smiles politely. And you replay it later thinking the joke was fine, the wording was fine, so what went wrong?

    A group of researchers just spent 86 hours listening to professional stand-up comedians to answer that question, and what they found is a little uncomfortable if you’re a words person. The thing that separated the sets that killed from the sets that died wasn’t the cleverness of the material. It was the silence. Specifically, the pause right before the punchline.

    I’ve played a lot of comic roles over the years — Bottom in A Midsummer Night’s Dream, Dogberry, Nathan Detroit in Guys and Dolls — and the thing you learn on stage fast is that the laugh almost never comes from the funniest word. It comes from the beat of nothing you leave in front of it. But if you’d asked me to prove that, I couldn’t have. It was a feeling. This study is the first time I’ve seen somebody put a number on the feeling.

    What the researchers actually did

    The work comes from Yuxi Ma, Yongqian Peng, and their colleagues at Peking University, and I like that they named the paper after the cliché: Timing is Everything.

    They pulled together 828 professional stand-up sets from three big Chinese comedy competition shows that aired between 2017 and 2025 — about 86 hours of material. The nice thing about competition shows is that every performance already comes with an audience appreciation score, so the researchers weren’t sitting around arguing about what was funny. They had the crowd’s verdict built into the data.

    Then they broke each performance into two kinds of measurements. One set was about content: how surprising was each line given what came before it, how big was the jump from setup to punchline. The other set was about timing: how long were the pauses, how much did the pauses vary, how fast was the comedian talking.

    Then the question was simple. When you try to predict how hard an audience responded, which measurements do the work?

    Timing won, and it wasn’t close

    Average pause duration and the variability of those pauses were the two strongest predictors of audience appreciation in the whole dataset. Both of them beat every content measure the researchers looked at. Pause length alone correlated with audience votes at r = 0.36, which for messy real-world behavioral data is a solid signal.

    Here’s the detail I keep coming back to, though. Speaking rate mattered too, and it ran in the direction most of us would guess wrong. Slower delivery was associated with better audience response. The comedians who took their time did better.

    That makes sense once you think about what a punchline needs. A punchline needs something to knock over. When you slow down, you’re giving the audience’s brain time to build the expectation you’re about to demolish. Rush the setup and there’s nothing standing there to hit.

    Why silence does so much of the work

    To see why the pause matters, you have to look at what your mind is doing while it listens to a joke.

    When a comedian sets something up, you quietly start building a prediction about where this is going. If you’ve taken a psych course you’ve met Jean Piaget, and this is his idea of assimilation — taking new information and fitting it into a mental framework you already have. That’s what a good setup does. Every line invites you to fill in the picture and assume you know the destination.

    Then the punchline blows the picture up. The thing you assumed no longer fits, and your brain has to build a new one on the spot. Piaget had a word for that too: accommodation, changing your framework because the new information won’t go into the old one.

    So a joke, looked at closely, is a tiny controlled crash of your own prediction followed by a very fast repair. Setup, assimilation. Punchline, accommodation. That whiplash is a good chunk of what makes you laugh.

    The researchers built a small example in the paper to show the shape of it, and I want to walk through it because it makes the whole thing click. I should say up front that this is a joke they invented themselves to illustrate the mechanism — the real bits from the study were all in Chinese, and the researchers measured the timing rather than publishing the material. But here’s theirs.

    Imagine a comedian says: I’m a psychology professor. I study what drives human behavior. I wrote a book on reverse psychology.

    And then — this is the part that matters — a pause. A beat longer than you were expecting.

    Don’t buy it. Seriously, do not read it.

    Two things just broke at once. The meaning broke, because you expected an author to promote his book and instead he told you to skip it. That’s the gag. But the rhythm broke too, and the rhythm is what the study is really about. The setup got you into a steady beat, the silence stretched a little too long, and that stretch is what set you up for the turn. Take the pause out, rush straight to don’t buy it, and the whole thing goes flat. The joke lives in the gap.

    There’s a memory angle here as well. That extra half-second of silence gives your brain time to fully encode the setup — encoding being the first step of memory, where information gets registered well enough to actually use. The better you’ve encoded the setup, the harder the twist violates it, and the bigger the payoff. And that payoff runs partly on dopamine, which is tied not only to reward but to the anticipation of reward. The setup builds the anticipation. The pause stretches it. The punchline pays it off.

    The difference between the pros and the rest of us

    Now here’s the finding that really got me.

    Both the great comedians and the mediocre ones do the same instinctive thing: they stretch the pause before a big laugh line. Across the whole dataset, pauses before high-surprise content ran about 35.6% longer than pauses before ordinary lines. Everybody feels this.

    But the expert performers stretched their pauses by about 41.2%. The weaker performers stretched theirs by only about 27.4%.

    Same instinct. Different nerve. The pros simply trust the silence more. They’re willing to let it sit there a little longer, and that willingness turns out to be a big piece of what makes them pros.

    Which is a hopeful result, honestly. It means comic timing isn’t a gift you either got or didn’t. It’s a skill — a coupling of what you say and when you say it — and you can work on it on purpose. That matches what I’ve watched in community theatre for years. The actors with the best timing aren’t the ones handed the funniest lines. They’re the ones brave enough to wait.

    What to do with this

    You don’t have to be a comedian for this to be useful. Telling a story at dinner, giving a toast, teaching a class, landing a point in a meeting — same rule.

    Resist the urge to rush your best line. We rush when we’re nervous, and we step on our own punchlines because the silence feels like failure. It isn’t. That silence is you loading the spring.

    So: set the idea up clearly, give people enough to build an expectation, and then right before the payoff, stop. Let the pause run one beat longer than feels comfortable. The discomfort you’re feeling is exactly the tension building on the other side, and when you do deliver, it lands harder.

    Try it once this week and watch what happens.

    Psychology Terms in This Article

    Assimilation: Taking in new information by fitting it into a mental framework you already hold. In this research, the setup of a joke works by assimilation — each line lets you slot the story into a familiar pattern and quietly predict where it’s heading, which is what gives the punchline something to violate.

    Accommodation: Changing your mental framework because new information won’t fit inside the old one. The punchline forces accommodation, and the researchers’ Dual Prediction Violation framework treats that forced rebuild — of both meaning and rhythm — as the engine of the laugh.

    Encoding: The first stage of memory, in which information is registered well enough to be stored and used. The study’s central finding, that longer pauses predict stronger audience response, has an encoding explanation: the silence buys your brain time to lock the setup in, and a well-encoded setup is a more satisfying thing to have overturned.

    Dopamine: A neurotransmitter tied to reward and, importantly, to the anticipation of reward. The pause before the punchline is anticipation being stretched out, which is why a delayed payoff can feel better than an immediate one — and why the slower comedians in this dataset did better than the fast ones.

    Speech rate and pause variability: The timing measures the researchers used — how quickly a performer speaks and how much the length of their silences fluctuates. Both outperformed every measure of the joke’s content in predicting how much the audience appreciated the set.

    Reference

    Ma, Y., Peng, Y., Lyu, J., Zhang, C., & Zhu, Y. (2026). Timing is everything: Temporal scaffolding of semantic surprise in humor. arXiv. https://arxiv.org/abs/2605.00143

  • Who’s Actually Choosing What You Watch Next?

    Who’s Actually Choosing What You Watch Next?

    You open the app to check one thing. Twenty minutes later you are still there, watching videos you never went looking for, and somehow you have “decided” to buy something you didn’t know existed when you picked up your phone. So whose decision was that, really?

    A new study by Zhean Zhu and Kai Wang at Zhejiang University of Finance and Economics, published in Frontiers in Psychology, takes that question seriously. They wanted to know how personalized recommendation feeds (the “For You” style feeds on short-video and shopping apps) shape not just what we see, but how we choose, and how much control we feel while we do it. They call their model Algorithmic Cognitive Colonization, which is a mouthful, but the idea is simple: the feed quietly becomes the architecture your choices get made inside.

    They ran two experiments. In the first, they put 200 college students on a 14-day “information diet.” Instead of a full digital detox, students kept using their apps but switched off the personalized feed and used a plain chronological or friends-only feed instead. Two things happened. The variety of content they bumped into went up noticeably. And their sense of being in control of their own choices dipped for about a week (the plain feed took more effort), then bounced back higher than where it started. Here is the part that stuck with me: the moment they turned the personalized feed back on, the variety of what they saw shrank right back to baseline within a week.

    The second study is where it gets a little uncomfortable. Students made quick shopping choices and also formed slower, more considered opinions. When a product carried a “Recommended for you” label, people went along with it far more often, but mostly in the fast decisions, not the slow ones. Adding the label more than doubled its pull in speeded choices compared to deliberate ones. Even a transparent label that explained “recommended based on your browsing history” did not reduce the effect, and a label saying other users like you had bought the item pushed people the hardest of all.

    So why does this happen? Part of it is selective attention, the way we lock onto some things and filter out the rest. The feed decides what even enters your field of view, so your attention is being aimed before you make a single choice. The bigger driver is that a recommendation label works as a heuristic, a mental shortcut. In a fast, low-friction moment, “Recommended for you” saves you the work of deciding, so the quick, intuitive part of your mind just takes the hint. Slow the decision down and the shortcut loses its grip. The wording matters too, which is plain old framing: change how the label is phrased and you change the behavior, and a social-proof frame worked best of all. And over time, repeated exposure does what it always does, the mere exposure effect, nudging us toward whatever feels familiar simply because we keep seeing it.

    Now the finding I cannot stop thinking about. Awareness did not protect people. Students who clearly knew that algorithms were steering them were no better at resisting. The researchers call this the “literacy paradox.” What did help was cognitive reflection, the habit of actually stopping to think a choice through. Knowing was not enough. Slowing down was.

    I build a fair amount of my own content, and I have caught my own attention getting quietly rerouted by these feeds more times than I would like to admit. So what can you do with this? Two things. First, do not count on “I know it is an algorithm” to save you, because this study says it will not. Second, add friction where it counts: when you are about to make a fast choice, that is exactly the moment to pause, and if you want to see more of the world, try your own information diet and switch to a chronological or following feed for a couple of weeks.

    If you are taking a psychology course, scroll down. I have pulled out the key terms this research illustrates so you can see the concepts at work.

    Psychology Terms in This Article

    Selective attention: The process of focusing on certain stimuli while filtering others out. In this research the personalized feed does the filtering for you, shaping the pool of content your attention ever lands on, so your choices are being narrowed before you consciously make them.

    Heuristic: A mental shortcut that speeds up decisions but can introduce bias. The study shows a “Recommended for you” label acting as a heuristic in fast decisions, letting the quick, intuitive part of the mind skip the effort of weighing options, which is why the label swayed speeded choices far more than deliberate ones.

    Framing: The way information is presented, which changes how we respond even when the underlying facts are the same. Here, changing the label’s wording changed behavior, and a social-proof frame (other users like you bought this) produced the strongest conformity of all.

    Mere exposure effect: The tendency to like something more just because it is familiar. Personalized feeds repeat similar content, and that repetition can tilt our preferences toward the familiar without our noticing, which helps explain why content variety snapped back so quickly once the personalized feed returned.

    References

    Zhu, Z., & Wang, K. (2026). Multimodal perceptual curation for cognitive autonomy in Generation Z decision making. Frontiers in Psychology, 17. https://doi.org/10.3389/fpsyg.2026.1868429

  • Mixed Feelings About AI: Cognitive Dissonance and the Stories We Tell Ourselves

    Mixed Feelings About AI: Cognitive Dissonance and the Stories We Tell Ourselves

    Why using AI tools leaves so many of us stuck in an uncomfortable middle — and what four psychologists can tell us about the way we manage that discomfort.

    There’s a feeling a lot of us get when we sit down to use an AI tool. You ask it for help, and a few seconds later you’ve got a draft, a summary, an answer that would have taken an hour on your own. There’s a little rush of amazement. And then, right behind it, a second feeling: should I be doing this? That second feeling doesn’t go away. I’ve been sitting with it for well over a year, and I think most people who use these tools are sitting with some version of it too.

    I heard someone on the tech podcast This Week in Tech use the phrase “mixed feelings” about AI, and it stuck with me, because that’s exactly the right phrase. There’s a spectrum. On one end are people strongly opposed to AI, and they have real reasons. On the other end are people who wave the whole thing away. But most of us live somewhere in the uneasy middle: we use these tools, we like these tools, and we feel a little bad about using these tools. That middle turns out to be an interesting psychological place to stand.

    Before getting to the psychology, it helps to name what’s actually bothering us instead of leaving it as a vague cloud of guilt. There are at least four concerns. First, every time you use one of these tools instead of hiring a person, there’s a possibility that someone didn’t get that work — the illustrator, the writer, the researcher. Second, these tools run in enormous data centers that use a staggering amount of energy. Third, those same data centers use a great deal of water to cool the computers down. And fourth, when you use one of these tools, you’re using everything it was trained on — writing, art, music — most of which the companies that built the tools almost certainly never paid for.

    That fourth concern stops being abstract for me, because I’m a content creator myself. I have a number of videos on YouTube, and I make a small amount of money from them each month. That income exists for one reason: people watch the videos and see the commercials. A lot of what I say in those videos has almost certainly been scraped to train these models. So when someone asks an AI a psychology question I happened to answer in a video, the AI just gives them the answer — they never watch, never see the commercial, and I never earn that small amount. The tool takes what I made, gives it away, and removes the one modest way I was paid for it. Which puts me on both sides of this at once: the user feeling guilty, and one of the people these tools quietly take from. If it’s happening to me, it’s happening to a lot of people who have no idea it’s going on.

    Cognitive dissonance: the attitude bends to fit the behavior

    The term most people reach for here is cognitive dissonance, which comes from Leon Festinger’s 1957 book A Theory of Cognitive Dissonance and a well-known 1959 study he ran with James Carlsmith, published in the Journal of Abnormal and Social Psychology. Most people have heard the phrase but don’t remember what the research actually showed, and the research is where it gets interesting.

    Participants were asked to do a genuinely boring task — turning pegs on a board for an hour. Afterward, they were asked to tell the next person waiting that the task had been fun. Some were paid twenty dollars to tell that little lie; others were paid one dollar. Later, everyone was asked privately how much they had actually enjoyed the task. The surprise is that the people paid one dollar were the ones who said they had enjoyed it. If you were paid twenty dollars, you had a clean reason to lie — you did it for the money. One dollar isn’t enough to justify lying to someone’s face, so those participants were stuck holding two thoughts that don’t fit: “I’m an honest person” and “I just lied for basically nothing.” That discomfort is the dissonance, and the mind resolves it by quietly deciding the task wasn’t so boring after all.

    Notice what moved. The behavior didn’t change — the lie was already told. The attitude changed to fit the behavior. That’s the piece worth carrying over to AI. Most of us aren’t carefully deciding whether to use these tools and then concluding it’s fine. We’re already using them. That’s the fixed point. So the real question isn’t whether we’ll use AI; it’s what story we’ll tell ourselves so we can keep using it and still feel like decent people.

    The menu of stories — and trivialization

    There’s a whole menu of those stories. You can add reassuring thoughts: the legal questions will get sorted out in court, everyone’s using these now, the technology is here and there’s no putting it back. There’s even research on one specific version of this move. Simon, Greenberg, and Brehm, writing in 1995 in the Journal of Personality and Social Psychology, described a strategy called trivialization: instead of arguing with the uncomfortable thought, you shrink it. The energy one search uses is nothing next to a cross-country flight. Sometimes the comparison is even sort of true — but its psychological function is to take a thought that was bothering you and make it small enough to ignore. It’s worth being honest about the difference between weighing something fairly and simply shrinking it so it stops nagging.

    Moral disengagement: how decent people take part in harm

    Cognitive dissonance is about internal consistency — my own thoughts not matching. But some of the discomfort with AI isn’t about me at all; it’s about the possibility that I’m part of something that harms other people. For that, Albert Bandura’s idea of moral disengagement fits better. In a 1999 paper in Personality and Social Psychology Review, Bandura asked how fundamentally decent people take part in things that hurt others without feeling like bad people, and he laid out the mental maneuvers that let us do it. Two of them describe AI talk almost perfectly. One is diffusion of responsibility: when millions of people are doing something, no single person feels responsible, so my contribution feels like a rounding error. The other is euphemistic labeling: we say a model was “trained on” content, which sounds clean and technical. Say instead that it “copied” a few hundred thousand books and images nobody paid for, and the feeling changes. Same event, gentler word, quiet conscience.

    Kohlberg: which floor are we reasoning on?

    Lawrence Kohlberg’s stages of moral reasoning add one more angle. Kohlberg cared less about what people decide is right and more about the reasoning behind it. At the preconventional level, morality is essentially about punishment — something is wrong if you get in trouble for it. For most casual AI users, the honest answer to “will I get in trouble?” is no, so it feels fine. But consider a student: there really can be a punishment — a failing grade, or failing the course — so a student reasoning at that same preconventional level might avoid AI purely because they could get caught. Same level of reasoning, opposite behavior, depending only on whether a punishment is waiting.

    At the conventional level, something is right if the group approves and everyone’s doing it — and a great deal of AI talk lives right here: it’s not illegal, everyone uses it, it’s normal. At the postconventional level, you reason from principle rather than from punishment or popularity, and interestingly you can land on either side. A principled “no” might say: given the harm to artists and writers, and the energy and water costs, I won’t use these tools, regardless of what’s legal or common. A principled “yes” might say: these tools can put tutoring, research, and translation help within reach of people who could never afford a human expert, so refusing to use AI is a comfortable stance for those who already have access to everything, and the fairer path is to build these tools and get their benefits to people who’ve been shut out. That “yes” isn’t “everyone’s doing it” — it’s an argument from fairness and access, which is what makes it postconventional. The honest observation is that most of our conversation about AI, mine included, sits down at the conventional level rather than up at the level of principle.

    Being skeptical of my own episode

    It would be easy to walk away thinking the psychology has solved the problem. So here’s a worry: putting the label “cognitive dissonance” on this feeling might itself be a way of feeling better. If it’s just a normal quirk of the human mind, then the discomfort isn’t a moral signal to act on — it’s just a glitch. That’s soothing, and it’s the very same move the whole discussion has been describing. Even the psychology can become one more way of getting the discomfort to leave us alone. And one more honest thought: many of the people worrying loudest about AI are knowledge workers, and these tools point straight at what we do. So when the twinge shows up, is it concern for an illustrator we’ve never met, or is some of it anxiety about our own relevance dressed in nicer clothes? Hard to say for certain.

    Local models: a partial answer

    One thing I actually did about all this was look into local LLMs. Most AI tools run in the cloud: you type something, it travels to a company’s data center, and the answer comes back. A local model runs on your own computer instead — you download it, and nothing goes out over the internet. The advantages are real. Privacy is the big one: nothing leaves your machine, so nobody stores your input or trains on it. It also lowers the environmental cost, since you’re not pinging a giant data center with every question, and there’s no subscription and no handing your material to a company.

    But the disadvantages don’t vanish. The model on your laptop was still trained on the same content that was probably never licensed, so the core ethical problem is untouched. Local models are generally less capable than the big cloud models, so you’re trading quality for principle. Running one well takes a fairly powerful computer, which carries a hardware cost and an e-waste angle. And running your own machine hard still uses energy — much less, and moved from the data center to your own electric bill, but not zero. Claiming local models use no energy would be exactly the kind of trivializing the discussion warns against. So the scorecard is honest but incomplete: privacy and much of the environmental cost improve, and the hardest problem sits there unchanged.

    Where this leaves me

    It leaves me in that uncomfortable middle. I’ll probably keep using these tools, because they’re genuinely useful. I think there’s something real in the idea that using a tool for my own work isn’t putting a specific person out of a job — though, having just told you my own story, I also know these tools do take from specific people, because I’m one of them, so I hold even that comforting thought loosely. My tentative landing is that the discomfort isn’t a problem to solve quickly. It might be doing something useful: as long as it’s there, the ethical questions stay alive. The moment the story becomes airtight and comfortable is the moment we stop paying attention. So maybe the goal isn’t to make the mixed feelings disappear, but to stay a little uncomfortable on purpose and resist resolving things too fast in either direction. That’s where a year of thinking has left me, and I hold it loosely. I’d genuinely like to hear where you land.

    The Psychology of Mixed Feelings About AI — Concept Map

    The Psychology of Mixed Feelings About AI

    Click any box to read what it means. The concerns create the discomfort; the frameworks explain how we manage it; the response is where the episode lands.

    The concerns

    What actually bothers us — the source of the discomfort.

    these create the discomfort ▼

    The frameworks

    Four psychological lenses on how we handle that discomfort.

    which lead us to a response ▼

    The response

    What we do about it — and where the episode lands.

    Select any box above to read about it.

    Key terms for students

    Cognitive dissonance. The mental discomfort of holding two inconsistent thoughts at once, especially when a behavior conflicts with a value. Because the behavior is often already done, people tend to reduce the discomfort by changing the attitude to fit the behavior rather than the other way around. Festinger and Carlsmith’s 1959 study is the classic demonstration.

    Trivialization. A specific dissonance-reduction strategy identified by Simon, Greenberg, and Brehm (1995): rather than changing the behavior or disputing the troubling thought, a person reduces the thought’s importance until it can be ignored. Watch for it whenever a real concern is answered only by comparing it to something worse.

    Moral disengagement. Bandura’s term (1999) for the mental mechanisms that let ordinarily decent people take part in harm without feeling guilty. Two relevant examples are diffusion of responsibility (no one feels responsible when many are involved) and euphemistic labeling (softer wording that makes an act feel cleaner than it is).

    Kohlberg’s levels of moral reasoning. A developmental framework focused on the reasoning behind moral judgments. At the preconventional level, right and wrong track punishment; at the conventional level, they track social approval and rules (“everyone’s doing it”); at the postconventional level, they track self-chosen principles such as fairness — which can support either using or refusing AI.

    Local LLM. A language model that runs on your own device rather than in a company’s cloud data center. It improves privacy and reduces the cloud’s energy and water footprint, but it does not resolve the unlicensed-training-data problem and comes with quality and hardware tradeoffs.

    References

    Bandura, A. (1999). Moral disengagement in the perpetration of inhumanities. Personality and Social Psychology Review, 3(3), 193–209. https://doi.org/10.1207/s15327957pspr0303_3

    Festinger, L. (1957). A theory of cognitive dissonance. Stanford University Press.

    Festinger, L., & Carlsmith, J. M. (1959). Cognitive consequences of forced compliance. The Journal of Abnormal and Social Psychology, 58(2), 203–210. https://doi.org/10.1037/h0041593

    Kohlberg, L. (1981). The philosophy of moral development: Moral stages and the idea of justice. Harper & Row.

    Simon, L., Greenberg, J., & Brehm, J. (1995). Trivialization: The forgotten mode of dissonance reduction. Journal of Personality and Social Psychology, 68(2), 247–260. https://doi.org/10.1037/0022-3514.68.2.247

  • Why the Whites of Your Eyes Shape a Stranger’s First Impression

    Why the Whites of Your Eyes Shape a Stranger’s First Impression

    You meet someone for the first time, and within a second or two you’ve already decided something about them — whether you’d trust them, whether you’d want to keep talking. You didn’t run through a checklist. It just happened. And it turns out one of the things your brain quietly picks up on is something you’ve probably never once thought about on purpose: how much of the white of a person’s eyes you can see.

    A study published in PLOS One by Mathias Boyer-Brosseau, Simon Rigoulot, and Sébastien Hétu looked at exactly that — the sclera, the white outer layer of the eyeball — and how the amount of it we can see shapes our first impressions. I came across this one on PsyPost, in a write-up by Eric W. Dolan, and it’s a great example of how a feature you’d never mention out loud can be doing real work behind the scenes.

    Here’s what they did. They took photos of faces with neutral expressions from a well-known set called the Karolinska Directed Emotional Faces database. Then they digitally created two versions of each face — one showing a smaller amount of visible white (about 31.5% of the visible eye) and one showing more (about 43.8%) — while keeping everything else about the face identical. Then 162 adults rated the faces on four things: how much they’d trust the person, whether they’d interact with them, how attractive they found them, and where they’d place them in the social pecking order.

    The result was remarkably consistent. Faces showing more of the white of the eye were rated as more trustworthy, more attractive, more sociable, and higher in social rank. And this wasn’t a quirk of one group — it held for male and female faces, and for male and female raters alike. A cue you never consciously register nudged four separate judgments in the same direction.

    So why would the amount of white matter at all? Part of the answer is that these judgments are fast and effortless — a textbook case of automatic processing, the mental work that happens without conscious awareness or intent. You’re not deciding to evaluate someone’s sclera; your brain does it for you and hands you a feeling. The researchers offer two evolutionary psychology explanations — the idea that some mental traits stuck around because they helped our ancestors solve social problems. Humans are unusual in having such visible whites, which makes it easy to follow exactly where someone is looking, and reading gaze is a huge part of getting along with other people. On top of that, scleral exposure tends to peak in our early twenties and shrink as we age, so more white may quietly read as youth, health, and vitality.

    There’s another layer here worth naming. A surface feature swaying a bunch of deeper judgments is basically peripheral route persuasion — attitude change that runs on superficial cues like attractiveness rather than on any real evidence about the person. And the ratings all moved together: faces judged attractive were also judged trustworthy, the classic attractiveness halo effect, where one good impression bleeds into all the others.

    I have to admit, as a former college professor this one landed a little uncomfortably. I formed quick reads on students and colleagues all the time, and I’m sure I told myself those reads were based on something substantial. Studies like this are a good reminder that a chunk of my “gut” was probably running on cues about this superficial.

    One honest caveat, and it’s a good one for anyone studying research methods: to add more visible white, the team had to make the eye itself a little bigger, so they couldn’t fully separate “more white” from “bigger eyes.” That’s a confounding variable — a second factor riding along with the one you care about, muddying the cause. The faces and raters were also mostly White, so we don’t yet know how far this travels across cultures.

    What do you actually do with this? You can’t change your sclera, and please don’t try. The useful move runs the other direction: knowing your snap judgments can hinge on something this trivial should make you hold them more loosely. Next time you get an instant read on a stranger, treat it as a first guess, not a verdict — and give the person a second data point before you trust it.

    If you’re taking a psychology course, scroll down — I’ve pulled out the key concepts this research illustrates, so you can see how a real study maps onto the terms you’re studying.

    Psychology Terms in This Article

    Automatic processing — Cognitive processing that happens without conscious awareness, intention, or effort, like recognizing a familiar face. In this study, participants weren’t deliberately measuring anyone’s sclera; the judgments of trust, attractiveness, sociability, and rank formed instantly and effortlessly, which is exactly why a cue this subtle could move them.

    Evolutionary psychology — An approach that treats psychological traits as adaptations that evolved to solve recurring problems for our ancestors. The researchers use it to explain why we’d care about the white of the eye at all: highly visible sclera makes gaze-following easier (crucial for cooperation), and more white may signal youth and health — both things it would have paid off to notice.

    Peripheral route persuasion — Attitude change driven by superficial cues, such as attractiveness or surface features, rather than by the quality of any real information. The whole effect here is peripheral-route in miniature: a small change to one facial feature shifted people’s overall impression of a stranger without adding a single fact about who that person actually is.

    Confounding variable — An extra factor that varies along with the variable you’re studying, offering an alternative explanation for the result. Because increasing the visible white also slightly enlarged the eye, eye size is a confound here — the researchers can’t be fully certain whether it was the extra white or the bigger eye driving the friendlier ratings.

    References

    Boyer-Brosseau, M., Rigoulot, S., & Hétu, S. (2026). Scleral exposure influences social judgments of trustworthiness, attractiveness, sociability, and social rank in White faces. PLOS One. https://doi.org/10.1371/journal.pone.0348193

    Dolan, E. W. (2026, July 28). People judge faces with more visible eye whites as more trustworthy and attractive. PsyPost.

  • Why Nobody Pushed the Button: The Psychology Behind a Subway Tragedy 

    Why Nobody Pushed the Button: The Psychology Behind a Subway Tragedy 

    When someone collapses in a public place, will anyone actually help? It’s one of the oldest questions in social psychology, and the newest research gives a surprisingly hopeful answer. But a recent death in a Boston subway station complicates that answer in a way worth understanding — not because it proves people are heartless, but because it shows exactly where helping breaks down. A quick note before going further: this post describes a real death, and some of it is hard to read.

    Steven McCluskey was forty. He was a carpenter who ran his own home improvement business, a father of two boys, and by his family’s account someone who did his best every day to show up for the people he loved. His family also shared that in recent years he had been struggling with addiction — a detail that matters here, though not in the way it might first seem. A little before five in the morning, at the Davis Square T station in Somerville, Massachusetts, Steven stepped onto a downward escalator, lost his balance at the bottom, and fell. His clothing was pulled into the machinery at the base. The escalator kept running, and he couldn’t free himself.

    The station had surveillance cameras, and NBC Boston’s investigative team obtained the footage. Less than a minute after Steven fell, someone came down, appeared to briefly try to help, then continued through the fare gates. Over the next several minutes, more than a dozen people passed by. Some stopped and stared. One man pulled on Steven’s legs for a few seconds and gave up. About eighteen minutes passed before anyone called 911, and more than twenty-two minutes before an MBTA employee pressed the emergency stop button — the red button at the top and bottom of every escalator that anyone standing there can push. Steven was taken to the hospital and died ten days later. His mother, shown the video by the news team after the family had been denied it during the investigation, said they treated him like he didn’t exist, and that if someone had taken one minute, he’d still be here.

    Here is the tension. The most recent and most convincing research on bystander behavior says the opposite of what that footage seems to show. Richard Philpot and his colleagues, publishing in American Psychologist, coded real surveillance footage of public conflicts on real streets across three countries — the Netherlands, the United Kingdom, and South Africa. In roughly nine out of ten of those conflicts, at least one bystander stepped in to help, and usually several did. The old story that nobody helps, that we all freeze, that a crowd guarantees inaction, turns out to be far too pessimistic. So how can that be true and this also be true?

    The honest answer isn’t that the research is wrong or that people are worse than the studies claim. It’s that the study and the case describe two different kinds of situations, and the difference between them is the whole lesson. Philpot’s footage captured public conflicts — fights, arguments, assaults. That kind of event is loud and obvious. There’s a clear aggressor, a clear victim, yelling, shoving. A bystander doesn’t have to work to figure out that something bad is happening. The situation announces itself, and much of the reason the intervention rate ran so high is that the ambiguity had been stripped out. Everyone could see exactly what was going on.

    Now picture Steven at the bottom of that escalator at five in the morning: a man lying still, not moving much. From thirty feet away, to someone half-awake on the way to a train, what does that look like? This is where his family’s mention of addiction becomes relevant, and it deserves care, because it’s precisely the psychology at work. A person lying motionless in a subway station early in the morning is, sadly, a sight many commuters have learned to walk past. Their brain files it under he’s sleeping, he’s intoxicated, this isn’t an emergency. Not because they’re cruel, but because the brain does what brains do with an unclear situation: it reaches for the most familiar explanation. And the most familiar explanation, the one that lets you keep walking, was the wrong one.

    This is the oldest finding in the bystander literature, and it survives all the new research intact. It goes back to John Darley and Bibb Latané in the years after the Kitty Genovese case. They mapped the steps that have to happen before a person helps, and the first real hurdle, once you’ve noticed something at all, is interpreting it as an emergency. Study after study showed that helping quietly dies right there — not because people are heartless, but because an unclear situation gives everyone permission to assume it’s nothing. Darley and Latané gave part of this a name: pluralistic ignorance. You look around to gauge whether a situation is serious, but everyone else is doing the same thing, keeping a calm face while they check — so the whole crowd reads each other’s calm as proof there’s nothing wrong. Fifteen people pass a man on an escalator, and each one sees fourteen others who didn’t stop, and each concludes it must be fine.

    Layered on top of that is diffusion of responsibility: the more people around, the less any one person feels it’s their job to act. Surely someone already called. Surely one of them knows something I don’t. And here’s the cruel irony that ties this back to Philpot’s study. In a loud, obvious street fight, more bystanders means a better chance someone helps, because the situation is clear and all those extra people form a larger pool of potential helpers. But in an ambiguous situation, more bystanders can cut the other way — each additional person who walks past without reacting becomes one more piece of evidence, for the next person, that this is normal. Same crowd size, opposite result. The variable that flips it is whether the situation is clear or ambiguous.

    So when Steven’s mother says they treated him like he didn’t exist, it’s easy to see why it looks that way, and no one should argue with a grieving mother about what she saw. But the psychology suggests the footage doesn’t show fifteen heartless people. It shows fifteen people whose brains each made the same ordinary, understandable, catastrophically wrong call. Any one of them, alone, at five in the morning, might well have stopped. It was the combination — ambiguity, the crowd, the early hour, and the assumptions we’ve all absorbed about a still figure in a transit station — that produced twenty-two minutes of nobody pressing a button that was right there.

    It’s worth staying skeptical of any tidy explanation, including this one. This reading comes from a news report and edited surveillance video; no one knows what was in the mind of each person who walked past. Maybe someone did call. Maybe someone assumed the man tugging on Steven’s legs had it handled. Reconstructing a psychological story from the outside is exactly the kind of thing to be careful about, because we love neat explanations for other people’s behavior. And this isn’t only a psychology story — there are real questions about the escalator’s safety design and how quickly the MBTA responded, questions the family is right to ask and ones psychology doesn’t answer. The claim here is narrow: it explains the part about the people on the stairs.

    The reason the psychology is worth understanding at all comes down to this. If you decide the people who walked past were simply bad people, there’s no lesson in it for you — because you’re not a bad person, so it could never be you. That’s the trap. Fifty years of bystander research keeps landing on the same point: it isn’t about bad people. It’s about ordinary people in a situation structured to produce inaction. Which means it could be any of us. And that’s the hopeful part, because if the cause is the situation and not the character, you can prepare for the situation and inoculate yourself against it in advance.

    A few things make a real difference, and they come straight out of the research. Knowing about the bystander effect changes behavior; people who’ve learned about it are more likely to act, because a small alarm goes off — everyone’s walking past, and that’s exactly when I might talk myself out of helping. Resolve the ambiguity out loud: if you see something and you’re unsure, say so, ask are you okay, because the moment someone answers or doesn’t, the situation stops being ambiguous — not just for you, but for everyone else standing there who was privately uncertain. And if you ever need help, or you’re helping and need others to join, get specific. Don’t call out for somebody to phone 911. Point at one person: you, in the gray coat, call 911 right now. The research is consistent here — the instant help is assigned to a specific person, it can’t be diffused to anyone else.

    That red button stays with me. It sits at the top and bottom of every one of those escalators, and anyone can push it. It’s the whole thing in miniature: help was physically within reach the entire time. What was missing wasn’t the ability to help but the interpretation — the click in someone’s mind that says this is an emergency and it’s mine to handle. That click is what fifty years of research is really about, and it’s something a person can practice making. Steven McCluskey died in the gap between seeing something and understanding it as an emergency. The most useful thing any of us can do with a story this painful is to let it close that gap a little — to be the one who asks are you okay, who says it out loud, who pushes the button. Not out of heroism, but because we thought about it in advance, on an ordinary day, before ever finding ourselves half-awake at the bottom of a staircase looking at someone who needs us.

    Bystander intervention: The act of a witness stepping in to help someone in an emergency. Research increasingly focuses not on whether a lone individual helps, but on the aggregate likelihood that at least one person in a group does.

    Bystander effect: The finding, first demonstrated by John Darley and Bibb Latané, that an individual is less likely, or slower, to help when other people are present than when alone.

    Interpreting the emergency: The step in Darley and Latané’s model where a person decides whether an ambiguous event actually is an emergency. This is where helping most often fails — an unclear situation invites the assumption that nothing is wrong.

    Pluralistic ignorance: A situation in which each person privately feels unsure but reads everyone else’s outward calm as evidence that there’s no emergency — so the group collectively concludes there’s nothing to worry about, even when there is.

    Diffusion of responsibility: The tendency for personal responsibility to feel divided among everyone present, so the more bystanders there are, the less any single person feels that helping is their job.

    Individual versus aggregate likelihood: A distinction the bystander literature often blurs. The individual likelihood that any one person helps can drop as a crowd grows, even while the aggregate likelihood that at least someone helps rises — because a larger crowd is a larger pool of potential helpers, at least when the situation is clear.

    Situational versus dispositional explanation: Whether behavior is explained by the situation a person is in or by the kind of person they are. The bystander research consistently points to the situation — which is why ordinary people, not just callous ones, fail to help.

    Sources and References

    Darley, J. M., & Latané, B. (1968). Bystander intervention in emergencies: Diffusion of responsibility. Journal of Personality and Social Psychology, 8(4), 377–383. https://doi.org/10.1037/h0025589

    Kath, R. (2026). How did a man die after getting caught in an MBTA escalator? NBC10 Boston. https://www.nbcboston.com/investigations/mbta-davis-escalator-death-investigation/3948562/

    Latané, B., & Darley, J. M. (1968). Group inhibition of bystander intervention in emergencies. Journal of Personality and Social Psychology, 10(3), 215–221. https://doi.org/10.1037/h0026570

    Manning, R., Levine, M., & Collins, A. (2007). The Kitty Genovese murder and the social psychology of helping: The parable of the 38 witnesses. American Psychologist, 62(6), 555–562. https://doi.org/10.1037/0003-066X.62.6.555

    Philpot, R., Liebst, L. S., Levine, M., Bernasco, W., & Lindegaard, M. R. (2020). Would I be helped? Cross-national CCTV footage shows that intervention is the norm in public conflicts. American Psychologist, 75(1), 66–75. https://doi.org/10.1037/amp0000469

  • Why People Step Out of the Plane — and Go Back Up the Next Day

    Why People Step Out of the Plane — and Go Back Up the Next Day

    Picture standing in the open door of a plane, wind roaring, the ground a long way down. Almost every part of you is shouting one thing: do not do this. Some people hear that voice, nod, and jump anyway. And here’s the part that really gets me — after a terrible accident, some of them go back up the very next day. Why?

    That question came roaring back for me after a recent New York Times feature by Kurt Streeter and Nicholas Bogel-Burroughs, which opened on a single brutal weekend: a skydiving plane crash in Missouri, a fatal BASE jump near Moab, and a rope jump in Brazil where the crew forgot to clip the harness. Strip away the details and the victims all faced the same thing — a brain built to keep them safe, screaming the obvious — and each went anyway.

    I’ve actually talked about the people who do this kind of thing before. A while back I interviewed Dr. Kenneth Carter, a psychology professor at the Oxford College of Emory University and the author of the book Buzz: Inside the Minds of Thrill-Seekers, Daredevils, and Adrenaline Junkies. He studies exactly this — and the same New York Times piece quotes him too.

    The first thing Carter told me is that “adrenaline junkie” mostly gets it wrong. The trait at the center of this is sensation seeking — the pull toward novel, varied, and intense experiences, and a willingness to take risks to get them. It traces back to Marvin Zuckerman, who discovered it almost by accident while running sensory-deprivation studies. Some people sat for hours in a quiet, blank room and felt fine; others couldn’t last minutes. No test at the time could predict who was who, so Zuckerman built one.

    Here’s the piece most people miss: high sensation seekers don’t feel the same panic you and I would. Carter’s work shows they tend to run on a different chemistry — less cortisol, the stress hormone, and more dopamine, the brain’s reward and motivation signal. So the moment that would flood you with dread becomes, for them, a moment of clarity. Time stretches, the noise drops away, and they describe picking out every crack in the rock as they fall past.

    Zuckerman’s scale breaks the trait into four parts, and I think this is the most useful way to understand it. The first two tell you what kind of seeker someone is: thrill and adventure seeking (the skydiving, the wingsuits) and experience seeking (fearless eating, far-flung travel, even striking up debates with strangers). The last two tell you how much trouble they might find: disinhibition, the tendency to leap before looking, and boredom susceptibility, how badly they need stimulation. As Carter put it to me, the danger usually isn’t the activity itself — it’s doing it impulsively. “It’s good to look before you leap,” he said, “if you’re leaping off a bridge.”

    A couple of things surprised me. Sensation seeking lines up with openness — the Big Five trait about curiosity and appetite for the new — but it is not the same as extraversion. Plenty of high seekers are quiet introverts. And I’ll admit I have skin in this game: I took Carter’s scale and scored a 13, which is low (he scored even lower, an 8). The few points I earned all came from experience seeking — I like exploring strange places. I’m also someone who gets a real jolt of nerves before stepping on stage for community theater, then loves it. Not the same as jumping off a cliff, but maybe a cousin of it.

    So what do you do with this? Two things. If you love someone who’s wired this way, understanding the trait helps — it isn’t recklessness for its own sake, and a calmer partner often becomes the “anchor” who keeps the risk in check. And if you’re the seeker, Carter’s warning is the practical gold: the trait isn’t the problem, impulsivity is. Build in the pause. Look before you leap.

    If you’re studying psychology, scroll down — I’ve pulled out the key concepts this research illustrates, in plain language you can use for an exam.

    Psychology Terms in This Article

    Sensation seeking — A personality trait describing how strongly someone is drawn to novel, varied, and intense experiences, and how much risk they’ll accept to have them. Zuckerman’s scale runs from about 8 to 40, with most people near 25; the extreme athletes in Carter’s work often score in the high 30s, which is why the same jump reads as terror to one person and joy to another.

    Dopamine — A neurotransmitter tied to reward, motivation, and the anticipation of something good. High sensation seekers appear to get a bigger dopamine payoff (with less of the stress hormone cortisol) from risky, novel situations, which helps explain why danger can feel energizing rather than frightening to them.

    Openness — One of the Big Five personality traits, marked by curiosity, imagination, and willingness to try new things. Sensation seeking correlates with openness, which is why the experience-seeking side of the trait shows up in adventurous eaters and travelers, not just cliff jumpers.

    Extraversion — The Big Five trait covering sociability and seeking stimulation from other people. The surprising research point is that sensation seeking is not reliably linked to extraversion — many high seekers are introverts — so the two traits should not be confused on an exam.

    Trait theory — The approach to personality that explains behavior through stable characteristics that show up across situations and over time. Sensation seeking is a textbook example: it’s measurable, fairly consistent within a person, and even shifts predictably with age, peaking in adolescence and easing as we get older.

    Yerkes-Dodson law — The principle that performance improves as arousal rises, but only up to a point, after which it drops — an inverted-U, with the ideal level differing by person and task. It offers a neat way to picture sensation seekers: they may need a much higher level of arousal to hit their personal sweet spot than the rest of us do.

    References

  • Your Muscles Are Talking to Your Brain — and It Might Be Why Exercise Fights Depression

    Your Muscles Are Talking to Your Brain — and It Might Be Why Exercise Fights Depression

    You already know what people tell you when you say you’re feeling low: go for a walk, get some exercise, you’ll feel better. And maybe part of you bristles at that, because it sounds too simple to be real. How is moving your legs supposed to touch something as heavy as depression? Well, scientists have just traced the actual messenger that carries the news from your muscles up to your brain — and it turns out the advice has a real chemical backbone.

    The study appeared in Molecular Psychiatry and was led by Suk-Yu Yau, an associate professor in the Department of Rehabilitation Sciences at Hong Kong Polytechnic University, working with a team across several institutions. They zeroed in on a protein called apelin. When you work your muscles, they don’t just burn calories — they release proteins into the bloodstream that act like messengers to the rest of the body. Apelin is one of those messengers, and your muscles pump out more of it when you push them.

    Here’s what the team did. They took mice and put them through a few weeks of mild, unpredictable stress until the animals showed the rodent version of major depressive disorder — the persistent low mood and loss of interest in pleasure that defines the condition in people. The stressed mice stopped preferring sugar water, groomed themselves less, and gave up faster in a swim test. Then some of them got a running wheel. After four weeks of voluntary running, the exercising mice bounced back on all three measures, and their blood and brains were noticeably richer in apelin. The biggest source? The calf and shin muscles of the hind legs.

    Then came the clever part. The researchers bred mice whose muscles couldn’t make apelin at all. Those mice ran just as much — and got nothing for it. No mood improvement, and no growth of new brain cells. Flip it around: when they used a virus to force ordinary muscles to crank out apelin without any running, those couch-potato mice improved just like the runners did. That’s about as close as biology gets to saying “this one molecule is doing the work.”

    So how does a muscle protein lift your mood? The apelin crossed the blood-brain barrier and reached the hippocampus — a structure deep in the brain that’s central to memory and mood regulation. Once there, it triggered neurogenesis, the birth of brand-new neurons, which the depressed non-runners never got. It also strengthened the connections between existing neurons by boosting their glutamate signaling, the kind of synaptic strengthening researchers call long-term potentiation — the same cellular process behind learning and memory. In other words, exercise wasn’t just making the mice feel better in some vague way. It was physically rebuilding the brain’s wiring, a clear demonstration of plasticity, the brain’s lifelong ability to reshape itself in response to what the body is doing.

    I spent years as a college professor telling students that exercise helps with mood, and honestly, I always felt a little hand-wavy saying it — like I was repeating folk wisdom. Reading this, I finally have the mechanism I wished I’d had back then. It’s a small thing, but it’s satisfying to see a piece of everyday advice turn out to have real machinery underneath it.

    What can you do with this? The finding points to something specific: leg-driven movement seems to matter, since the hind-leg muscles were the main apelin factories. Walking, cycling, stair climbing, squats — the stuff that loads your lower body — looks especially worth keeping in your week. And the researchers stress that holding onto muscle strength as you age may help protect your mood, not just your mobility. You don’t have to run a marathon. You just have to keep your muscles in the conversation.

    One honest caveat: this was done in male mice. The authors are upfront that female, older, and human studies still need to happen before anyone promises results, partly because hormones and muscle mass differ by sex and could change how much apelin the body makes.

    If you’re studying psychology, scroll down — I’ve pulled out the key concepts this research illustrates, with a plain-language definition and a note on how the study demonstrates each one.

    Psychology Terms in This Article

    Major depressive disorder — A mood disorder marked by persistent sadness, hopelessness, and a loss of interest in activities that used to feel rewarding. The researchers induced a rodent model of it through chronic mild stress, then measured it through reduced interest in sugar water (a stand-in for the loss of pleasure called anhedonia) and faster giving-up in a swim test.

    Hippocampus — A structure in the brain’s limbic system that’s essential for forming new memories and helps regulate mood. In this study, the muscle-made apelin traveled all the way to the hippocampus, and that’s where it produced its antidepressant effects — a reminder that this region isn’t just about memory.

    Neurogenesis — The formation of brand-new neurons, which we now know continues in certain brain regions throughout adult life. Exercising mice grew new hippocampal neurons while the non-exercising depressed mice did not, and mice without muscle apelin showed no new growth even when they ran.

    Long-term potentiation (LTP) — A lasting strengthening of the connection between neurons based on recent activity, considered a core cellular mechanism of learning and memory. Apelin enhanced glutamate signaling and the function of NMDA receptors in the hippocampus, strengthening neural connections in exactly the way LTP describes.

    Plasticity — The brain’s capacity to change and reorganize itself in response to experience throughout life. This whole study is a case study in plasticity: a behavior (exercise) sent a chemical signal that physically remodeled brain tissue and shifted mood.

    References

    Yu, J., Cheng, T., Guo, H., Song, Z., Zhong, Y., Lee, T. H., Li, J., Formolo, D. A., Hussain, A., Le, K., Yao, Y., Abel, R. L., Cheung, W.-H., Lin, K., Xu, A., Cheng, K. K.-Y., & Yau, S.-Y. (2026). How muscle talks to brain: apelin protein mediates exercise-induced antidepressant effects. Molecular Psychiatry. https://doi.org/10.1038/s41380-026-03651-y

  • Does Your Dog or Cat Need Closure? Pet Grief and the Psychology of Loss

    Does Your Dog or Cat Need Closure? Pet Grief and the Psychology of Loss

    We hear the word “closure” everywhere — in true crime shows, in news coverage of trials, and in the well-meaning advice of friends after a loss. But where did this idea come from, and does the research actually support it? In this episode I trace the surprising history of closure, from the Gestalt psychologists of the 1920s, to Arie Kruglanski’s research on the “need for cognitive closure,” to its takeover by talk shows, the victims’ rights movement, and even the funeral industry in the 1990s. Along the way we look at what the science really shows: the craving for answers is real and measurable, and confirming the reality of a death does help people grieve. But sociologist Nancy Berns, family therapist Pauline Boss (who coined the term “ambiguous loss”), and a striking study comparing homicide survivors in death penalty and life-sentence states all point to the same conclusion — grief doesn’t have a finish line, and expecting one may do more harm than good.

    And then there’s my cat. After I brought one of my cats to be euthanized, several people asked whether I’d brought my other cat along “so she could have closure.” That question sent me into the research on animal grief: recent studies show that surviving dogs and cats really do change their behavior after a companion dies — seeking attention, eating less, even searching the house for their missing friend. But the one study that looked directly at whether viewing the body makes a difference found no effect at all. So is pet closure real science, or are we projecting a contested human concept onto our animals? Listen in and decide — and then ask yourself who that goodbye ritual is really for.

    References & Resources for This Episode


  • Why Your Favorite Playlist Eventually Bores You — and the Algorithm Is Part of the Problem

    Why Your Favorite Playlist Eventually Bores You — and the Algorithm Is Part of the Problem

    You know that feeling when Spotify hands you a song you instantly love, you play it into the ground for a week, and then somewhere around day ten you can’t stand to hear it again? That’s not just you being fickle. A new study suggests the very algorithm that found you that perfect song might be the thing quietly draining the fun out of your listening — and out of your movies, your shows, and your reading too.

    The research comes from Samsun Knight, an assistant professor at the University of Toronto’s Rotman School of Management who also happens to be a published novelist. His paper, “Engagement-based curation and the evolution of taste,” appeared in the Journal of Cultural Economics. Knight started wondering about this after his own odd experience with Spotify: he’d fall in love with a recommended song, and then the app would keep shoving that same song at him until he couldn’t bear it. Why, he asked, would a company that badly wants you to stay happy keep making you miserable?

    Here’s the core idea. The more you listen to a certain style of music, the better you get at appreciating it — Knight borrows the economists’ term consumption capital for this. But appreciation follows an upside-down U. A moderate amount of exposure makes you like something more. Too much exposure makes you sick of it. This is really a story about the mere exposure effect — the well-documented tendency to like things more simply because they’ve become familiar — running straight into its own limit. Familiarity builds liking, right up until it tips over into “please, anything but this.”

    Now here’s the problem Knight built a mathematical model to expose. Recommendation algorithms optimize for what keeps you clicking today. They test content over a few weeks or months. But real human taste evolves over ten or twenty years. So Knight ran simulations — a thousand separate trials — pitting different kinds of algorithmic “curators” against a simulated listener whose tastes slowly shifted over time. One curator naively assumed that high engagement just meant high quality. It never realized that its own past recommendations were the reason a song felt familiar and got clicked in the first place.

    What happened? The precise, engagement-hungry algorithm stopped exploring almost entirely. When it showed the listener something unfamiliar and got a lukewarm response, it decided that whole genre was bad and buried it. Its exploration rate dropped to zero. Then it played the safe favorites until the listener was thoroughly bored — a self-fulfilling prophecy of monotony. There’s even a name in the paper for the trap: straddling, where the system overplays a great song until you’re sick of it, while occasionally testing a mediocre one just enough to confirm it’s mediocre, never realizing that simply resting the good song would bring the joy back.

    And the punchline, the part I found genuinely surprising: a worse algorithm did better. When Knight added a little random noise — forcing the system to occasionally toss in something unfamiliar — the simulated listeners discovered new styles, built appreciation for them, and got a break from their overplayed favorites. The slightly imperfect system made people happier in the long run. His sharpest example is hip-hop. It took a lot of listeners years to learn how to hear it; early on it sounded abrasive to ears raised on rock and roll. Knight points out that if a 1980s Spotify had ranked hip-hop by people’s initial distaste, the genre might have been buried before it ever got off the ground.

    I spent years in e-learning and watched my own son disappear into video games that were engineered to keep him engaged minute by minute, and this paper put words to something I’d half-noticed for a long time. The systems that are best at giving us what we want right now can be terrible at helping us become people with bigger, richer tastes later. There’s a real difference between a tool that satisfies you and a tool that helps you grow.

    So what can you actually do with this? Be your own source of randomness. Once in a while, hand the keys to a human — a friend’s playlist, a librarian’s pick, a critic whose taste runs different from yours. Deliberately rest the songs and shows you love instead of binging them flat. And when an algorithm keeps serving you the same comfortable loop, treat that as a signal to go wander somewhere it would never send you. The boredom you’re feeling might not be a sign that there’s nothing good left — it might just be a sign that you’ve been fed the same thing one too many times.

    If you’re studying psychology, scroll down — I’ve pulled out the key concepts this research illustrates, with plain-language definitions you can use for an exam.

    Psychology Terms in This Article

    Mere exposure effect — The tendency to develop a preference for things simply because we’ve encountered them repeatedly. This study is built on the upside of that effect: the more you’re exposed to a style of music or art, the more you learn to appreciate it. The twist is that the same familiarity that builds liking eventually overshoots into boredom — so an algorithm that maximizes familiar content rides the mere exposure effect right past its sweet spot.

    Habituation (satiation) — A decrease in responsiveness to a stimulus after repeated or prolonged exposure. In the model, listeners get “sick of” a favorite song because their response to it weakens every time it’s replayed. Knight’s “straddling” trap is essentially habituation in action: the algorithm keeps replaying a great song until the listener habituates, never realizing a rest period would reset the response.

    Reinforcement — In operant conditioning, any consequence that strengthens the behavior it follows. Recommendation systems treat your clicks and plays as reinforcement signals, “rewarding” whatever you engage with by serving more of it. The paper shows the danger of a system that only follows immediate reinforcement: it optimizes for the next click while quietly narrowing the range of things you’ll ever enjoy.

    Sensation seeking — A personality trait describing the drive to pursue novel, varied, and stimulating experiences. The research highlights what gets lost when an algorithm refuses to explore: the novelty that lets tastes evolve. The “noise” that improved long-term satisfaction in the simulation is essentially a manufactured dose of novelty — the thing sensation seeking naturally pushes us toward and that over-precise systems strip away.

    References

    Knight, S. (2026). Engagement-based curation and the evolution of taste. Journal of Cultural Economics. https://doi.org/10.1007/s10824-026-09591-3

    Reporting by Eric W. Dolan, PsyPost (June 2, 2026).

  • Does Spoiling Your Kids Actually Create Narcissists? Here’s What the Research Says

    Does Spoiling Your Kids Actually Create Narcissists? Here’s What the Research Says

    You’ve probably heard it before — maybe you’ve even said it yourself: “That kid is going to grow up to be a real handful.” We have a strong gut sense that giving children everything they want, never saying no, removing every obstacle before they can encounter it — all of that leads to something dark in adulthood. But is that actually true? And more interestingly, what specifically does it lead to?

    A new study published in Current Psychology took a careful look at exactly this question. Researchers Jennifer Vonk, Virgil Zeigler-Hill, and Nyla Griffin at Oakland University asked 720 college students to recall how their parents treated them during childhood — specifically whether their caregivers offered praise, gave them whatever they wanted (indulgence), or pushed them toward status and prestige. Then they measured something called the Dark Triad: three personality dimensions that psychologists consider socially difficult — psychopathy, Machiavellianism, and narcissism.

    What they found is striking — and the key is in the distinction between two things parents often confuse: praise and indulgence. These are not the same thing, and it turns out they lead to very different outcomes. Recalled childhood praise — being told you are valued, capable, and worthwhile — predicted lower levels of hostility, impulsivity, and cruelty in adulthood. It was associated with what the researchers call adaptive social traits: healthy confidence, social agency, and emotional stability. Praise, it seems, builds people up in a genuinely useful way.

    Recalled childhood indulgence — being given everything you asked for, having no real limits set, being treated as though rules don’t apply to you — predicted something very different. Higher psychopathic meanness. Higher narcissistic antagonism. Higher impulsivity, or what researchers call disinhibition: acting on impulses without considering consequences. The child who was never told “no” grew up with less capacity to regulate behavior and a greater tendency toward cruelty and entitlement.

    What makes this research stand out is how precisely it breaks down these personality dimensions. Rather than treating narcissism or psychopathy as a single block, the researchers measured specific facets — antagonism, emotional vulnerability, boldness, meanness — and found that indulgence and praise had opposite effects on nearly every one of them. As lead researcher Vonk told PsyPost: “The fact that high indulgence and low praise seem to predict higher levels of pathological traits… points to the importance of providing children with affirming feedback without engaging in over-indulgence.”

    I find this genuinely useful — not just as a piece of research, but as a practical distinction. We tend to think of giving kids positive experiences as one thing. But there is a real difference between affirming a child’s worth and removing every obstacle from their path. One builds self-esteem — an authentic sense of one’s own value that doesn’t depend on always getting what you want. The other builds entitlement, which is something else entirely.

    Of course, the study has limits. It relied on how adults remember their childhoods, which isn’t the same as how those childhoods actually were. Memory is reconstructive, and people high in hostile traits may simply recall their parents more negatively. The sample was also mostly white, female, and American college students — so we should be cautious about generalizing. But the pattern is consistent with what developmental psychologists have suspected for a long time.

    If you’re studying psychology, I’ve pulled out the key concepts this research illustrates — scroll down to the terms section.

    Psychology Terms in This Article

    Narcissistic personality disorder — A pattern of grandiosity, a deep need for admiration, and a lack of empathy for others. In this study, childhood indulgence predicted higher scores on narcissistic antagonism — a facet involving entitlement, hostility toward others, and exploitation. This shows how overindulgence may feed the entitlement component of narcissism without producing the full clinical disorder.

    Antisocial personality disorder — Characterized by disregard for others’ rights, impulsivity, deception, and lack of remorse. The psychopathic meanness and disinhibition facets measured in this study overlap directly with antisocial traits. The finding that indulgence predicted higher meanness and impulsivity suggests that failing to set limits during development may contribute to the callousness and poor impulse control seen in antisocial behavior.

    Self-esteem — A person’s overall evaluation of their own worth and value. The study found that parental praise predicted lower hostile traits and higher social confidence — essentially healthier self-esteem. This supports the idea that self-esteem built on authentic affirmation functions very differently from the inflated self-regard produced by overindulgence.

    Trait — A relatively stable characteristic that influences how a person thinks, feels, and behaves across situations. This study used a multi-dimensional trait approach, measuring specific facets of the Dark Triad rather than treating psychopathy or narcissism as single traits. When psychologists study personality, they increasingly break broad traits into narrower components, because different facets can have entirely different developmental origins.

    Nature-nurture issue — The long-standing debate about whether psychological characteristics are shaped more by genetic inheritance or by environmental experience. This study is firmly on the nurture side — it examines how specific parenting behaviors correlate with adult personality outcomes. That said, children’s pre-existing temperaments may influence both how parents treat them and how they recall that treatment in adulthood, which is the nature-nurture issue in action.

    Temperament — The early-appearing, biologically influenced emotional dispositions that form the foundation of personality. A child’s temperament may partly drive parenting behavior — a difficult child may elicit different parenting than an easy one. This is why correlational studies like this can’t fully separate what parents cause from what parents respond to.

    References

    Vonk, J., Zeigler-Hill, V., & Griffin, N. (2026). Praise the light, indulge the dark: Parenting strategies and dark personality traits. Current Psychology. https://doi.org/10.1007/s12144-026-09418-6

    Dolan, E. W. (2026, May 30). New study links parental indulgence to psychopathic and narcissistic traits in adulthood. PsyPost.