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Our capacity to juggle several tasks at once is among the most important capabilities of the human cognitive system.
Just consider a typical day in the life of a modern human: you glance at your phone while waiting for coffee to brew, skim headlines while half-listening to a podcast, mentally rehearse a client pitch while walking your child to school, reply “noted” on Slack during a meeting while updating a slide deck, check your bank balance while standing in line, and, in a moment of entirely optional productivity theatre, scroll through a friend’s Facebook feed to see what their cat had for breakfast (admittedly, not the most important addition to our already heavy repertoire of multi-tasks).
If these familiar episodes of multitasking barely register as effort, it is because they have been absorbed into habit, woven into the fabric of daily life, quietly showing how often we coordinate competing goals, priorities, and impulses at once. For all the noise about AI agents, it is worth remembering that human agents remain remarkably capable.
That said, generative AI and AI agents add yet another layer of temptation to multitask, and a respectable excuse for doing so. Now we can draft an email while an agent prepares slides, ask a chatbot to summarize a report while we skim LinkedIn, generate code while answering Slack, or prompt three models at once while half-editing a memo. This feels like augmented productivity, but often becomes cognitive diffusion or an increase in work intensity. As I illustrated in I, Human, when machines take over fragments of thinking, we become supervisors of many shallow streams rather than authors of one coherent argument. The result is not just intellectual sloppiness, but a steady erosion of focus, as attention shifts from solving a problem to managing tools that promise to solve it for us.
A bad rap
To be sure, multitasking tends to get a bad rap, especially among cognitive psychologists and behavioral scientists. This skepticism is well grounded. In a widely cited meta-analysis, researchers showed that alternating between tasks produces measurable “switch costs” in both speed and accuracy, even when tasks are simple. Subsequent research also found that heavy media multitaskers performed worse on tests of attention control and working memory, suggesting that frequent task-switching may erode the very cognitive filters that make focus possible. A more recent synthesis including examination of social media effects linked media multitasking during studying to significantly poorer academic outcomes. More recent neuroscientific evidence also shows that habitual multitasking is associated with reduced grey-matter density in regions linked to cognitive control, and some scholars have pointed out that multitasking deducts the equivalent of 10-IQ points from our performance and is therefore more debilitating than smoking weed (presumably minus the benefits or self-perceived creativity!).
Taken together, the evidence is rather compelling: multitasking is not a sign of superior efficiency but a tax on attention, trading depth for the comforting illusion of productivity. It makes us feel busy, sometimes even clever, yet especially for complex, analytical, or creative work it is usually worse than doing one thing well at a time, or learning to focus.
“Supertaskers”
And yet, that is not to say that we are all equally bad at multitasking. In fact, as in most areas of cognition, there are meaningful individual differences. A small but influential line of research has even identified a group sometimes labelled “supertaskers.”
In a dual-task experiment involving simulated driving and mental arithmetic, researchers identified a minority of participants who showed virtually no performance drop when handling two demanding tasks at once. These individuals tended to score higher on measures of working memory capacity and executive control (proxies for higher IQ), suggesting that cognitive resources, more than motivation or confidence, set the ceiling on multitasking ability.
Working memory is analogous to a computer’s RAM, in that it determines how many pieces of information can be actively held and processed at once. Individuals with greater working-memory capacity possess more cognitive bandwidth to manage competing demands, though the limits remain real for everyone. In line, studies consistently show that people with higher working memory capacity, stronger attentional control, and better fluid intelligence incur smaller task-switching costs. Working memory capacity predicts resistance to distraction, while Unsworth and Engle (2007) linked it to superior performance in complex attention tasks, and executive attention explains substantial variance in multitasking performance.
The role of personality
Unsurprisingly, personality also plays a role: most notably, traits linked to self-regulation and planning, such as conscientiousness, tend to buffer against the negative effects of multitasking, while impulsivity and related tendencies are associated with poorer performance. Broader Big Five traits such as extraversion, neuroticism, and openness show mixed effects, often influencing how people approach multitasking rather than how well they actually perform it. Even training and domain expertise matter. Air-traffic controllers, surgeons, and experienced gamers show reduced switching costs in their domains because practice automates sub-tasks, freeing cognitive bandwidth.
This does not mean that people know how good they actually are at multitasking. As in most domains of competence, the share of people who claim to excel far exceeds the share who truly do. In a classic experiment, researchers found that heavy media multitaskers rated themselves as effective jugglers of attention yet performed worse on tests of working memory and attentional control. The pattern echoes a broader principle from behavioral science, familiar from the Dunning–Kruger literature: when a skill is poorly understood and rarely measured, confidence tends to rise as competence falls. Multi-tasking, like leadership or emotional intelligence, is easy to overestimate because busyness looks like effectiveness, and we remember the rare occasions when juggling worked, not the many when it quietly degraded our thinking.
Taken together, the evidence paints a nuanced picture. The average human is indeed a poor multi-tasker, especially when tasks are novel or cognitively demanding. But some individuals, by virtue of higher executive capacity (raw mental horsepower), disciplined habits, specialized training, and the right personality, are less bad at it. That distinction matters for leadership and talent assessment, because it reminds us that multitasking ability is not a universal virtue or vice. It is a measurable cognitive skill, unevenly distributed across people, and often confused with confidence, busyness, or the social theatre of productivity.
If you have ever interviewed for a job, there is a non-trivial probability that you have encountered “tricky” or quirky interview questions. These are questions that are intentionally unexpected, abstract, or only loosely related to the actual requirements of the role. Rather than systematically assessing job-relevant skills, they are designed to surprise candidates, test composure, or signal creativity.
Interviewers often defend these questions as clever ways to evaluate problem-solving ability, cultural fit, or performance under pressure. The evidence tells a different story. Decades of research in industrial-organizational psychology show that unstructured, brainteaser-style interviews have low predictive validity. They generate noise, not insight. At best, they measure how comfortable someone is with improvisation. At worst, they measure how similar the candidate is to the interviewer.
Cases in point
To illustrate the point, here are some common examples, ordered from least absurd, or at least somewhat defensible, to most absurd:
1. What is your biggest weakness?
Nominally job-related, though usually answered strategically rather than honestly. The only rational way to respond is to disguise a strength as a flaw. It is less a test of self-awareness than an audition for plausible humility.
2. Sell me this pen.
Some relevance for sales roles, but still an artificial performance detached from real context. Popularized by The Wolf of Wall Street, it reinforces the myth that great sales is about fast talk rather than listening, diagnosing needs, and building trust.
3. Tell me about a time you failed.
In principle, a legitimate behavioral question. In practice, often an invitation to narrate a carefully curated setback that highlights resilience, grit, and eventual triumph. It rewards storytelling ability more than learning agility.
4. How many tennis balls can fit inside a Boeing 747?
A classic “guesstimate” puzzle meant to test structured thinking. Geeks may love it, but it predicts little beyond prior exposure to similar puzzles. If you want to measure cognitive ability, there are far more reliable and validated tools.
5. How many windows are there in New York City?
Same logic, further removed from any realistic job task. For what it’s worth, large language models estimate the number in the tens of millions, depending on assumptions. Which illustrates the deeper point: if ChatGPT can answer it in seconds, why are we using it to judge human potential?
6. If you were an animal, which one would you be and why?
A thinly veiled personality quiz. It feels like a BuzzFeed throwback disguised as talent assessment. The answer often reveals more about the interviewer’s projections than the candidate’s traits.
7. If you could have dinner with any historical figure, who would it be?
A pleasant icebreaker masquerading as a values assessment. It doubles as a signaling exercise: how curious, cultured, contrarian, or provocative can you appear in under 30 seconds? Say Nelson Mandela and you signal virtue. Say Steve Jobs and you signal ambition. Say Machiavelli and you signal strategic depth. But say Stalin and suddenly the interview turns into a moral inquiry. Was that intellectual curiosity, dark humor, or deeply questionable judgment? The question reveals less about your leadership potential than about your risk appetite for reputational self-sabotage.
8. If you were a kitchen utensil, which one would you be?
At this point, the exercise has drifted into sheer parody – shows like The Office come to mind. Spoon suggests reliability. Knife signals edge. Spork implies versatility. The real variable being tested may simply be how badly you want the job, signaled by the fact that you haven’t just walked out of the room.
The science
So, what does the actual science of interviewing say?
First, there is evidence that some interviewers are not merely misguided, but derive a certain Machiavellian pleasure from putting candidates on the spot. Research on interviewer behavior shows that individuals higher in everyday sadism or dominance are more likely to ask stress-inducing or intentionally uncomfortable questions. In other words, the brainteaser may sometimes be less about assessing you and more about interviewers’ enjoying the deviant power dynamic.
Second, the predictive validity of unstructured interviews is consistently low. Meta-analyses spanning decades show that traditional, free-flowing interviews correlate only modestly with later job performance. The problem is not conversation per se, but inconsistency. Different candidates get different questions. Interviewers rely on intuition. Evaluation criteria shift midstream. The result is noise, bias, and overconfidence, and unfortunately, these issues often go undetected because of the subsequent confirmation bias or failure to admit mistakes by hiring managers. In essence, if an interviewer likes you, they will either continue to like you after you are hired or pretend you are doing a great job to avoid looking like a fool.
By contrast, structured interviews work. The formula is hardly mysterious: define the competencies that matter for the job; ask all candidates the same job-relevant questions; anchor evaluations to predefined scoring rubrics; and combine interview data with other validated predictors such as cognitive ability or work samples. Behavioral questions about past actions and situational questions tied to realistic job scenarios consistently outperform seemingly clever riddles and quirky brain teasers.
The role of AI
And then there is AI, not so much the elephant in the room as the bull in the china shop, already rearranging the furniture while we are still debating the seating plan.
In a world where candidates can rehearse flawless answers with generative tools, the theatrical interview becomes even more obsolete. Chatbots can generate polished responses to “biggest weakness” or “sell me this pen” in seconds. Ironically, the more predictable and formulaic the question, the easier it is to game. This raises the bar for employers: assessment must shift toward observable skills, simulations, job trials, and multi-source data.
This does not mean interviews become irrelevant. It means they must evolve. When information is abundant and answers are cheap, the premium shifts from rehearsed narratives to demonstrated capability. Instead of asking candidates what they would do, employers can observe what they actually do: solve a real problem, analyze a live case, critique a flawed strategy, or collaborate with a future teammate. AI can help candidates prepare, but it cannot fully fake sustained performance in a realistic simulation.
There is also a deeper irony. The very tools that allow candidates to polish their answers can help employers design better assessments. AI can assist in standardizing questions, generating competency-based scenarios, flagging bias in evaluation, and even predicting which interview questions correlate with outcomes. In other words, AI exposes the weakness of theatrical interviewing while simultaneously offering the tools to fix it. The real risk is not that candidates use AI. It is that employers fail to upgrade their methods accordingly.
In sum, the future of interviewing is not about trickier questions. It is about better design. The uncomfortable truth is that quirky interview questions persist because they are fun, easy, and ego-affirming. But hiring is too important to be left to entertainment. If organizations are serious about talent, they must replace improvisational theatre with evidence-based assessments, and have the humility and self-critical honesty to truly test the outcome of their decisions to acknowledge when they are wrong, and make an effort to tweak things and improve.
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