There is a tendency to think of science as a production system: resources are invested, experiments are conducted, and those experiments are expected to produce useful outcomes. The better the system, the more efficiently it should convert investment into useful products. Under this model, an unsuccessful experiment is a failed investment, and a scientist who cannot articulate the eventual application of their work is difficult to justify funding.
But science was never meant to function as an enterprise for producing predictable returns. At its core, science is a formalized way of exploring the unknown.
Exploration is inherently uncertain. It is costly, resource-intensive, and often futile.
Most attempts will not produce anything immediately useful. But exploration has an asymmetric payoff: a small number of discoveries can generate benefits vastly greater than the resources invested in the many attempts that fail. The possibility of those discoveries—and the knowledge they add to civilization—justifies maintaining a capacity for exploration despite its uncertainty. You cannot know in advance which questions will matter, where an unexpected observation will lead, or what value a discovery may hold in the future. This is not a flaw; it is merely the nature of exploration.
Part I — The Value of Science to Society
The pursuit of scientific knowledge creates several distinct forms of value for society.
1. Instrumental value
Scientific discovery has enabled more efficient agriculture, reduced food waste, improved housing and infrastructure, and transformed the prevention, diagnosis, and treatment of disease. It has expanded our capacity to improve the material conditions of human life in ways that would have been unimaginable to previous generations.
This is the form of scientific value that society tends to recognize and encourage most readily because its outcomes are comparatively tangible. A new therapy can be evaluated by the number of patients it reaches. A new technology can be measured by the efficiency or productivity gains it generates. These outcomes are visible, quantifiable, and relatively easy to translate into the language of policy and economics. Yet measurability is not synonymous with significance.
An invention can solve an immediate problem while creating consequences whose broader or longer-term effects remain unknown. Antibiotics, for example, transformed the treatment of infectious disease while simultaneously creating evolutionary pressure for antimicrobial resistance. AI illustrates the same broader principle: technologies developed to increase productivity, expand access to information, and automate difficult tasks may also introduce forms of misinformation, dependency, concentration of power, and social disruption that were difficult to anticipate at the outset.
Neither example makes the underlying scientific or technological advance a mistake. Rather, they illustrate how difficult it is to assess the ultimate value of an intervention when its consequences unfold across complex systems and over long periods of time.
The question of whether a scientific advance is ultimately good for humanity is therefore considerably more complicated than we often acknowledge.
2. Epistemic value
Science also produces something more fundamental: knowledge about the world.
We learn something that we did not previously know. That knowledge may have no obvious application when it is discovered, but that does not mean its eventual value can be assessed as zero.
Scientific knowledge is cumulative and interconnected. A seemingly obscure observation can become the missing piece that makes a later discovery possible. A biological mechanism that appears irrelevant to human disease may become important when another researcher discovers how it interacts with a different pathway. A mathematical principle developed without any practical purpose may eventually become foundational to a technology that did not yet exist.
This is one of the fundamental difficulties of evaluating scientific knowledge by its immediate utility: we rarely know which pieces of knowledge will become useful until we have accumulated enough of them to see the connections.
Science serves not only to solve the problems we currently recognize, but to expand the body of knowledge from which future questions and solutions can emerge.
There is also a deeper reason to value the pursuit of knowledge. Exploration is one of the ways civilization has learned to confront the fundamental uncertainty of existence. We want to know where we came from, how life emerged, whether we are alone in the universe, and what governs the world around us. Science does not necessarily provide comforting answers to these questions, but it gives us a way to ask them rigorously and replace some measure of uncertainty with understanding.
In this sense, the pursuit of knowledge serves a purpose beyond its eventual applications. It helps us make sense of the world we inhabit. A civilization that can investigate its origins, understand its place in the universe, and continually expand the boundaries of what it knows is better equipped to confront the uncertainty inherent in existence.
This gives scientific inquiry an existential dimension: some questions are worth answering not for their practical utility, but because understanding our existence is itself a human concern.
3. Aesthetic value
There is a third form of value that is harder to quantify: aesthetic value.
Scientific training teaches us to observe—to look carefully, notice patterns and differences, and remain attentive to phenomena that might otherwise seem ordinary. In doing so, it changes not only what we know about the world, but how we see it.
A microscope can transform a drop of water into an ecosystem. Evolution can transform a forest from a collection of trees into the product of billions of years of history. Astronomy can transform the night sky from a scattering of lights into a universe containing billions of galaxies.
In this sense, science is not merely a way of understanding or controlling the world. It is a way of experiencing it. And there is value in that experience. Human beings spend much of their lives moving through a world that can easily become familiar and unremarkable. Scientific observation offers a way of continually rediscovering it.
Perhaps this is one reason the pursuit and teaching of science matter even when they produce no immediate practical benefit. To teach someone how to observe the world is, in a small way, to give them more of the world to experience.
The reward is not merely greater knowledge, but a richer encounter with the world and the complexity and beauty it contains.
If science creates value in ways that cannot always be predicted, then we must also reconsider how we decide who should be entrusted to pursue it.
Part II — Who Should Perform Science?
Scientific exploration is expensive. It consumes public and private money, specialized infrastructure, equipment, institutional capacity, and enormous amounts of human time. Every scientific project therefore carries an opportunity cost.
If exploration is costly, then society has a responsibility to be selective about who is entrusted with it.
What should we select for? Not simply intelligence, technical competence, nor the ability to publish. A good scientific explorer should posess the following:
Curiosity: an insatiable need to ask questions and a desire to understand the world more deeply.
Independence: the ability to resist intellectual conformity and pursue contrarian questions on the strength of one’s own judgment.
Judgment: discernment of signal from noise, promising questions from trivial ones, and productive failures from wasted effort.
Humility: the willingness to recognize the limits of one’s knowledge and revise one’s assumptions when evidence demands it.
Tolerance for uncertainty: comfort with pursuing questions whose answers—and even their value—may remain unknown for years.
Imagination: the creative capacity to look beyond established questions and envision what might be possible.
These qualities are difficult to measure using conventional academic metrics and are unevenly distributed among scientists. Although they can be cultivated, they cannot be reliably produced through training alone. Many scientists can conduct rigorous experiments; far fewer can identify consequential questions, pursue them independently, and generate genuinely unexpected insights. Yet as the number of researchers pursuing independent work grows, our academic system increasingly relies on metrics such as publications, citations, grants, and demonstrated impact to evaluate scientific potential—precisely because these are easier to measure than the qualities that make someone an effective scientific explorer.
The problem, therefore, is not that too many people participate in science, but that independence has become the default endpoint of scientific training rather than something earned through demonstrated capacity for exploration.
This does not mean that independent scientists should be expected to produce predictable outcomes. They should, however, be held to a high standard of intellectual honesty, rigor, and judgment even when the outcomes of their work are uncertain. Failure is inevitable. A failed hypothesis is not necessarily a failed scientist. What matters is whether uncertainty is approached with rigor, judgment, and a willingness to learn from the outcome.
We cannot predict which questions will prove fruitful. We can, however, become better at identifying the explorers best equipped to pursue them.