For the last few hundred years, we have become increasingly skilled at turning complex parts of life into abstractions. We take something living, contextual, and difficult to measure, then reduce it into a form that can be counted, compared, standardized, managed, or traded. Money becomes an abstraction of value, calories an abstraction of food, productivity an abstraction of work, GDP an abstraction of economic activity, while a résumé attempts to compress a person’s professional life into a page and a step count turns movement into a number we can watch accumulate on a screen.

There is nothing inherently wrong with abstraction itself. In many cases, it is useful, and some degree of simplification is necessary for a society of any real scale to function. Problems begin to emerge when the representation starts carrying more weight than the thing it was designed to represent, because eventually we stop using the abstraction merely to help us understand reality and begin reorganizing reality around the abstraction.

Work becomes hours, output, and efficiency; food becomes calories, macros, and price; education becomes test scores, credentials, and institutional affiliation; health becomes lab values, step counts, and readiness scores. Attention is translated into engagement, relationships into networks, and time itself is divided into units that can be allocated, measured, sold, and optimized. Gradually, a person becomes easier to understand through the collection of measurable outputs attached to them than as a living organism embedded within a biological, social, and physical environment that cannot be fully represented by any of those measurements.

The same process makes nearly everything easier to commodify because once something has been standardized, it becomes easier to price, exchange, optimize, and scale. Labor becomes labor-hours, land becomes real estate, food becomes inventory, attention becomes ad impressions, and human behavior becomes data that can be collected, analyzed, predicted, and sold. Even something as fundamental as sleep can be reframed as “recovery optimization,” where its value increasingly comes from its ability to improve tomorrow’s performance rather than from the simple biological reality that an animal requires sleep.

Over time, these abstractions inevitably begin shaping what we value in people as well. We reward predictability, efficiency, consistency, productivity, emotional control, and the ability to produce more while consuming fewer resources, while admiring people who can tolerate longer hours, answer faster, manage greater workloads, eliminate downtime, and continue performing despite fatigue. When those qualities become dominant measures of success, a person’s value can quietly become inseparable from what they produce and how efficiently they produce it.

Those are perfectly reasonable qualities to value in a machine, but they become far more questionable when they are allowed to define a human being.

Fundamentally, we are animals, and being an animal means living with a degree of variability that cannot simply be engineered away. We have rhythms, fluctuating energy, wandering attention, emotional needs, physical limits, and a dependence on movement, sunlight, food, relationships, play, novelty, solitude, and periods of recovery. There are times when we are capable of extraordinary effort and periods when very little useful output happens at all, because living organisms are constantly responding to changing conditions rather than operating at a fixed level of performance. Hunger, light, stress, temperature, sleep, movement, social connection, illness, seasons, and countless other signals continually alter the state of the organism, making variability an unavoidable feature of being alive.

Modern life has increasingly taught us to interpret many of those biological characteristics as inefficiencies requiring correction. Fatigue becomes a problem because it reduces output, sleep occupies hours that could otherwise be productive, boredom disrupts concentration, emotion complicates decision-making, and relationships demand time whose value is difficult to quantify. Even play, leisure, and unstructured time can begin to feel vaguely irresponsible because they produce so little that can be measured afterward.

The response has been to gradually break down what it means to be human into parts that can be measured, managed, and commodified. We track sleep, quantify movement, measure food, schedule recovery, monitor readiness, analyze our attention, and increasingly treat the body as another system whose inputs and outputs should be optimized. Hobbies turn into side businesses, leisure becomes an opportunity for self-improvement, exercise becomes another collection of performance metrics, and recovery itself can become valuable primarily because it allows us to return to being productive more quickly. Tools originally intended to help us understand ourselves can quietly reinforce the same worldview that made us feel the need to optimize ourselves in the first place.

Artificial Intelligence (AI) enters this world at an interesting moment because it excels at many of the characteristics we have spent generations elevating within ourselves. It can process information rapidly, work with enormous quantities of data, reproduce outputs consistently, remain available without needing rest, and perform certain forms of cognitive labor at a speed no human could reasonably match. If efficiency, scalability, consistency, memory, speed, and productivity continue to occupy such a large part of how we assign value, then machines will increasingly outperform us according to the standards we created.

There is something uncomfortable in what that reveals. We have spent generations trying to overcome the biological limits of being human, only to create technologies that possess many of the qualities we were unsuccessfully attempting to cultivate in ourselves. The machine does not become tired of repetition, resent the absence of meaning, need an afternoon in the sun, lose concentration because it slept poorly, or decide that spending time with someone it loves is more important than producing another widget. We experience those things because our existence is embodied, relational, and finite, yet we have spent generations treating many of them as obstacles standing between us and greater productivity.

Perhaps the inevitable, society-wide infusion of AI will finally force us to examine why we ever chose those standards in the first place and, in doing so, return us to a much more fundamental question about what it means to be human. If machines become better than us at many of the tasks around which we organize work and economic value, we will be left confronting parts of ourselves that abstraction has made increasingly easy to ignore. A human life contains experiences whose importance cannot be adequately represented by productivity, efficiency, income, status, credentials, biometric scores, or any other measurement we created to make people easier to evaluate.

We know intuitively that sitting with someone we love can matter even when nothing is accomplished, that play can be worthwhile without producing an outcome, that walking outside can have value beyond the number of steps recorded, and that a person going through a period of illness, grief, exhaustion, or uncertainty has not somehow become less human because their productive capacity has declined. Yet, much of the world we have built struggles to account for value that cannot be translated into output, perhaps because we have spent so long organizing ourselves around the parts of life that are easiest to quantify.

The arrival of AI that can outperform us across increasingly large portions of the measurable world may therefore leave us with a much older and more difficult question. Once we stop confusing our economic usefulness with the totality of our value, we still have to decide what we believe a human being is, what kind of life is appropriate for an animal like us, and which parts of our existence deserve to be protected precisely because they cannot be made more efficient.