Vučko’s argument begins with a simple observation about the structure of human experience. Nearly everything people do, from careers to hobbies to relationships, involves investing psychological or physical resources toward outcomes that are not guaranteed in advance. A surgeon operates without knowing exactly how the patient will recover. A novelist writes without knowing whether the book will find readers. A climber ascends a wall that might defeat them. These two features—effort and uncertainty—are usually treated as costs to be minimized. Technological progress, in its idealized form, promises precisely that: machines that work harder than we do and predict outcomes better than we can. But Vučko asks what remains of an activity once both parameters are optimized away.

To answer that question, he grounds his analysis in self-determination theory, one of the most influential frameworks in contemporary motivation science. Developed by psychologists Edward Deci and Richard Ryan, the theory holds that human well-being depends on satisfying three basic psychological needs: autonomy, competence, and relatedness. Crucially, the sense of competence is not fed by easy successes. It grows from challenges that demand genuine investment and from outcomes that could plausibly have gone otherwise. When an activity requires no effort and carries no risk of failure, the psychological machinery that generates satisfaction from achievement has nothing to work on. Vučko contends that effort and uncertainty are therefore not incidental annoyances but prerequisites for any sufficiently meaningful activity.

The thought experiment at the heart of the paper imagines extreme automation taken to its logical endpoint. Suppose technology advanced to the point where machines outperform humans at every task—diagnosing disease, writing legal briefs, composing music, driving vehicles, even conducting scientific discovery. There are already signs of this trajectory. GPT-4 has been shown to pass the bar exam, and AI systems for breast cancer screening have matched or exceeded human radiologists in international evaluations. Moravec’s paradox, the observation that tasks easy for humans remain hard for machines even as machines conquer tasks humans find difficult, is steadily eroding as artificial intelligence encroaches on domains once considered exclusively human.

What happens to such activities in a fully automated world? Vučko’s answer is that they do not disappear, but they change character. Activities in which humans can no longer compete with technology become, in his terms, recreation. A chess player today already inhabits this condition: since Deep Blue defeated Garry Kasparov in 1997, no human seriously claims to play chess better than a machine, yet millions still play. The game has become something played for enjoyment rather than objective achievement. Vučko argues that this transformation is sufficient to conditionally erode the subjective meaningfulness of activities for some individuals. Knowing that your best effort is objectively trivial compared with what a machine can do changes the texture of the experience, even if the pleasure remains.

The erosion does not stop with obviously competitive pursuits. Vučko emphasizes that no activity exists in isolation. Even autotelic activities—those done for their own sake, such as socializing, self-reflection, or reading fiction for the pleasure of emotional transportation—can be negatively affected by the awareness of one’s diminished capacity for objective contribution. A person might still enjoy a long walk in the mountains, but if they know that no physical accomplishment of theirs carries any weight in a world where machines handle everything, the background sense of being a capable, contributing agent begins to thin. Meaning, on this account, is not generated activity by activity in a vacuum; it depends on a broader self-understanding in which one’s efforts matter.

This leads to what may be the paper’s most striking implication: there is a limit to how much human distress technology can alleviate without producing a new kind of suffering. Much of the motivation for automation is the reduction of toil, risk, and anxiety. But if Vučko is right, the sources of distress he targets—uncertainty about outcomes and the strain of effort—are the same sources from which meaningful activity draws its nourishment. Eliminating all sources of distress also eliminates the potential for meaningful activities. The utopian project, pursued without limit, becomes self-defeating. Limited automation, by contrast, is conducive to meaningful lives: it removes drudgery while leaving humans room to strive, fail, and achieve on their own terms.

The argument engages a rich philosophical tradition. Robert Nozick’s famous experience machine thought experiment anticipated the intuition that pleasurable experiences divorced from genuine achievement feel hollow. Albert Borgmann’s philosophy of technology distinguished between the shallow comforts of the device paradigm and the deeper satisfactions of focal practices that demand engagement. More recently, John Danaher has explored whether life in a world without work can be worth living, and L. Scripter has defended the possibility of meaningful lives alongside artificial intelligence. Vučko’s contribution is to identify a specific mechanism—the joint minimization of effort and uncertainty—and to trace its consequences systematically, rather than relying on general appeals about the dignity of labor.

Notably, the paper does not claim that a highly automated future must be bleak. Moderate automation, which relieves people of tedious and dangerous work while preserving domains of genuine human challenge, could expand the space for meaningful activity rather than contract it. The concern is specifically with unlimited automation—the endpoint at which no domain of human striving retains objective significance. Vučko also acknowledges an important boundary condition: transhumanist scenarios in which humans merge with technology warrant separate consideration. If the striving agent is itself augmented, or partially constituted by the machines, the analysis of who is investing effort and bearing uncertainty changes fundamentally, and the existential calculus may differ.

For readers watching generative AI reshape creative and professional landscapes, the analysis offers a framework for anxieties that are often dismissed as mere nostalgia or Luddism. Creative displacement anxiety—the unease felt by artists and writers whose skills seem suddenly replicable—may reflect a genuine psychological injury, not simple economic fear. If competence, effort, and uncertainty are pillars of meaning, then watching machines master one’s craft after years of dedicated practice strikes at something deeper than income. Vučko’s paper suggests that societies racing toward maximal automation should ask not only what tasks can be automated, but what human capacities for meaning they are quietly dismantling—and whether some friction is worth keeping.

Subject of Research: The impact of extreme technological automation on effort, uncertainty, and the meaningfulness of human activities

Article Title: The limits of technological progress: effort, uncertainty, and meaningful activities

Article References: Vučko, D. (2026). The limits of technological progress: effort, uncertainty, and meaningful activities. AI & SOCIETY. https://doi.org/10.1007/s00146-026-03356-4

Image Credits: AI Generated

DOI: 10.1007/s00146-026-03356-4

Keywords: automation, technological progress, meaning in life, self-determination theory, artificial intelligence, human obsolescence, effort, uncertainty, recreation, philosophy of technology, well-being, transhumanism

The study belongs to a growing class of research that relies on ecological momentary assessment, or EMA, a method in which participants are prompted repeatedly on their smartphones or other devices to report on their current state as they move through real environments. Rather than asking people in a laboratory to recall how tired they were last week, EMA captures fatigue, cognitive performance and behavior in near real time, dozens of times per participant across several days. This matters because fatigue is notoriously unstable: it rises and falls with sleep, workload, time of day and countless small events. By sampling these fluctuations intensively, researchers can model how a person’s state at one moment relates to their choices at the next, a question that one-shot questionnaires simply cannot answer.

Coordinated analysis adds a further layer of rigor. Instead of pooling raw data from different studies into a single giant dataset — an approach that can be confounded by differences in measures, sampling schedules and populations — the researchers analyzed each of the six studies separately using an identical analytic plan, then combined the results. If an effect appears consistently across independently collected datasets with different participants, designs and instruments, the odds that it is a statistical fluke of any one study shrink dramatically. In an era when psychology has been forced to confront replication failures, this strategy has become one of the field’s most trusted tools for separating robust phenomena from artifacts.

The central result concerns the temporal ordering of states and behavior. At each prompting occasion, participants rated their current fatigue and completed brief tasks or self-reports indexing their processing speed — essentially, how rapidly they could take in and respond to information. The analysis then examined whether these momentary measurements predicted fatigue override at a subsequent occasion: instances in which participants engaged in demanding activity despite reporting being tired. Across the six studies, higher momentary fatigue and slower processing speed each forecast a greater likelihood of subsequent override. In other words, the very signals that would seem to argue for rest — feeling drained and thinking sluggishly — were the states that most often preceded a decision to push on anyway.

That counterintuitive pattern is precisely what makes the finding scientifically interesting. A simple homeostatic account of fatigue would predict the opposite: the more exhausted people feel, the more they should disengage and recover. Instead, the data suggest that fatigue often functions as a signal to be weighed rather than an automatic command to stop. When tiredness is high, the question of whether to continue becomes salient, and many people resolve it in favor of continued effort. The authors’ coordinated design showed that this relationship was not an artifact of any single study’s sample, measure or analytic choice, lending the pattern the kind of cross-contextual consistency that single studies rarely achieve.

The role of processing speed adds a cognitive dimension to the story. Processing speed is one of the most basic markers of cognitive efficiency, and it is known to degrade under sleep deprivation, illness and sustained mental effort. The finding that slower processing at one moment predicts later fatigue override hints at a possible internal logic: people may notice their thinking has become labored and interpret that slowing as evidence that they need to compensate — working harder, pushing longer, or forcing themselves through tasks they would normally finish easily. Alternatively, slowing may simply co-occur with the kinds of demanding days, heavy workloads and poor nights of sleep that also generate obligations that cannot be dropped. The coordinated analysis cannot fully adjudicate between these interpretations, but by demonstrating that the association holds across six datasets, it establishes that the link is real enough to deserve that closer scrutiny.

Methodologically, the study illustrates why momentary designs are transforming the science of self-regulation. Traditional between-person studies compare tired people with rested people and conclude that fatigue changes behavior. But such comparisons confound stable traits — some people are chronically more tired, more conscientious or more burdened — with the within-person dynamics that actually drive decisions in the moment. EMA designs flip the question: within the same person, when fatigue rises above their own typical level, what happens next? The answer from this coordinated analysis is that both the subjective feeling of tiredness and the objective-ish marker of slowed cognition carry predictive information about the person’s own subsequent behavior, above and beyond their average tendencies. This within-person framing is crucial for anyone hoping to intervene: you cannot change someone’s average fatigue easily, but you can detect and respond to momentary spikes.

The practical implications reach into occupational health, medicine and everyday self-management. Fatigue override is a double-edged phenomenon. On one side, it underwrites resilience — the parent who still cooks dinner after a brutal shift, the clinician who finishes rounds despite exhaustion, the student who keeps studying when every instinct says stop. On the other, chronic overriding of fatigue is implicated in burnout, sleep debt accumulation, medical errors and the stubborn persistence of overwork cultures. If momentary fatigue and processing speed reliably flag when override is likely, they could be built into early-warning tools: wearable or smartphone-based systems that notice when a user’s tiredness and cognitive slowing are peaking and prompt a deliberate decision about whether continuing is truly necessary. Such tools would not forbid effort; they would simply make the trade-off visible at the moment it is being made.

The findings also speak to theoretical debates about the function of fatigue itself. One influential view treats fatigue as a motivational signal — an internal computation about the costs and benefits of continued effort — rather than as a simple depletion of a finite resource. The new results fit that framework: fatigue does not mechanically shut behavior down; instead, it changes the landscape of decisions people face, and both the intensity of the feeling and the accompanying cognitive slowing inform how people respond. That fatigue and processing speed each contributed predictive power suggests the brain may be integrating multiple channels of information — how drained the body feels and how well the mind is running — when calibrating whether to persist. Future work, the authors and observers note, will need to test which downstream consequences follow from override in these moments: does pushing through restore a sense of control, or does it deepen the fatigue that prompted it?

For now, the study’s quiet contribution is to make an everyday drama measurable. Six datasets, each capturing the texture of ordinary days, converge on the same conclusion: the moments before we override our fatigue are not silent. They are marked by feelings we can report and cognitive changes we can measure, and together those signals foreshadow the choice to keep going. As experience sampling methods spread through psychology, medicine and workplace research, the boundary between feeling exhausted and acting exhausted is becoming an object of precise science — one that may eventually help people decide, more deliberately, when pushing through is worth it and when rest is the smarter move.

Subject of Research: Predicting subsequent fatigue override from momentary fatigue and processing speed using coordinated analysis of six ecological momentary assessment studies

Article Title: Fatigue and processing speed predict subsequent fatigue override, evidence from a coordinated analysis of six EMA studies

Article References: Hernandez, R., Schneider, S., Hoogendoorn, C. J., Kratz, A. L., Yang, C.-H., Ehde, D. M., Stone, A. A., Jin, H., Fanning, J., Hakun, J. G., Fritz, N. E., Gonzalez, J. S., & Moore, R. C. (2026). Fatigue and processing speed predict subsequent fatigue override, evidence from a coordinated analysis of six EMA studies. Communications Psychology. https://doi.org/10.1038/s44271-026-00537-1

Image Credits: AI Generated

DOI: 10.1038/s44271-026-00537-1

Keywords: fatigue, fatigue override, processing speed, ecological momentary assessment, coordinated analysis, self-regulation, effort, cognitive performance, burnout, experience sampling, Communications Psychology, replication