The Misconception of Utilitarianism

And the solution to the is–ought problem in light of evolution

Introduction

“If one has one’s why in life, one can cope with almost any how. Man does not strive for happiness; only the Englishman does.”

Friedrich Nietzsche, Twilight of the Idols, Maxims and Arrows, § 12 (translation from the German)

People endure extreme suffering when they have a compelling why. They even risk their own lives for their children. When this why is missing, a more pleasant life itself becomes the supposed ultimate goal. This confusion shapes many contemporary ethical approaches.

Hedonism and utilitarianism are among the most widespread ethical theories. Hedonism (from the Greek “hedonē,” meaning pleasure or joy) declares pleasure to be the highest good and pain the greatest evil. This raises the question of whose happiness should be maximized and whose suffering minimized. Utilitarianism (from the English “utility,” meaning usefulness) turns this into a general principle for society by demanding that the total happiness of all those affected be maximized and their total suffering minimized (Bentham, 1789; Mill, 1861).

These approaches, however, confuse an evolutionary regulatory mechanism with its underlying goal. Reconstructing this goal leads to the solution to the is–ought problem, which I can only outline here. The complete argument can be found in my paper (Delor, 2026).

1. Sam Harris and the Failure of Utilitarianism

In The Moral Landscape (2010), Sam Harris posits the well-being of conscious creatures as the ultimate goal. To illustrate this, he introduces the image of a moral landscape. Each point in this multidimensional landscape is meant to represent a possible state of conscious creatures. Its valleys would correspond to deep suffering, its peaks to high levels of well-being. Science is supposed to show which actions could lead us to the highest peaks.

Yet Sam Harris already presupposes well-being as the ultimate goal here and does not explain why it should take precedence over other goals. Empirical scientific investigations could indeed show which conditions increase the well-being of particular individuals or groups. Why we should pursue this well-being, however, and whose well-being should count would first need to be established. Agreement or consensus cannot replace this justification, since neither is a criterion of truth.

A Map Without a Goal

This model also raises several questions. Whose well-being and happiness are to be represented here? How can we develop an objective measurement procedure and an objective scale for this? Which suffering counts more than other suffering? The same applies to happiness.

But let us assume that we could produce such an objective map. Which point on this map should we actually strive to reach? Do its points apply to society as a whole or to individual people? How deep may the valleys be on the way to a higher peak? How many sacrifices may we therefore make to achieve greater well-being in the long term or overall?

Such a map could be useful if we had already determined our goal and knew that it lay somewhere on this map. Producing the map alone, however, does not yet give us that goal.

Similar proposals involving idealized knowledge do not solve this problem either. Peter Railton, for example, developed an approach according to which a person’s good would be determined by what their ideally informed self would advise them to desire under their actual circumstances (Railton, 1986). Yet even this complete knowledge does not answer the question of which goal we should pursue. At most, it could help us find the best route to a goal already determined.

Moreover, both models face the problem that our actual knowledge of the moral landscape and the consequences of our actions can never be complete. We do not even know what proportion of it we know. In practice, therefore, such a model could not show us a reliable route even if the goal were known. Most of the map remains unexplored and unknown in advance, and along the way we encounter unexpected events and black swans (Taleb, 2007).

For Whom?

An individual’s well-being can conflict with that of their community. Anyone seeking to weigh the two against each other needs a standard for assigning those weights.

Individual landscapes do not yet provide this common standard. A shared landscape already presupposes it. Including future creatures adds further uncertainty. We can only estimate to a limited extent what needs they will have under living conditions that are still unknown.

Centralization and Abuse

The scientific optimization of overall well-being suggests centralized control. A panel of experts could claim to bring together the necessary information and make decisions for everyone.

However, the knowledge required for this is distributed and often tied to specific circumstances of life (Hayek, 1945). A central body can capture it only incompletely. Its errors can nevertheless affect an entire society.

If decision-makers bear little of the consequences of their own mistakes, they also lack an incentive to exercise caution (Taleb, 2018). Under the banner of the greatest common good, they may also pursue their own advantage.

Confusing the Reward Mechanism with the Goal

Happiness and suffering regulate our behavior. Under the conditions in which they evolved, these signals favored behaviors that served an underlying goal. The fact that people strive for happiness therefore does not yet explain its status as an ultimate goal.

On a journey to the sea, the odometer reading usually increases. Anyone who declares this reading to be the actual goal can increase it by driving around endlessly. The reading rises while the sea remains unreached.

Likewise, a pleasant sensation can become detached from its original function. An addiction rewards behavior that destroys the affected person’s foundations of life. The reward signal remains effective even though the behavior undermines the underlying goal.

Conversely, people accept great suffering for a higher goal. And why well-being should be the ultimate standard remains unanswered.

2. The Is–Ought Problem

2.1 Two Seemingly Insurmountable Barriers

The search for this standard leads to the is–ought problem. Two claims are commonly advanced to rule out a solution. The is–ought gap is said to be fundamentally unbridgeable. Furthermore, any attempt to provide a natural grounding for ethics is said to commit a naturalistic fallacy.

In my paper, I show why both claims are untenable (Delor, 2026). The so-called naturalistic fallacy concerns a problem of definition (Frankena, 1939). A definition cannot replace the examination of the chosen standard. Moore’s appeal to intuitions does not escape this problem either (Moore, 1903).

The formal proofs concerning the is–ought gap, in turn, depend on the assumptions of their respective systems. They show the limits of particular reconstructions of normative concepts. A general impossibility of any connection between facts and normative statements does not follow from them.

2.2 Outline of the Solution

There is no good in itself. Neither an action nor a state can be good in and of itself. Likewise, nothing can be unconditionally obligatory. Such one-place concepts of “good” and “ought” are untenable because they specify no conditions by which their correspondence with reality could be tested. They therefore say nothing about reality. Something can be good only for a subject in achieving a goal under the given boundary conditions (Bunge & Mahner, 2004). The same applies to “ought.” An action ought to be performed when, under the given boundary conditions, it offers the best chances of achieving an existing goal.

Goals are hierarchically ordered. We can choose instrumental goals ourselves. We cannot freely choose an ultimate goal, since this would require libertarian free will, which is logically impossible (Schopenhauer, 1839/1841).

Which ultimate goal actually exists can only be reconstructed empirically. Since all life, and thus our desires and goals as well, arose through evolution, this ultimate goal must be explicable in terms of evolutionary theory.

Indeed, an evolved, teleonomic ultimate goal shared by all living organisms can be reconstructed. “Teleonomic” means that it arose naturally without a goal-setter. This ultimate goal is the long-term preservation of the genetic lineage. I call it lineage fitness. Organisms with such a goal function were able to prevail over organisms without it.

Our dispositions, desires, and goals are proximate mechanisms that serve the attainment of this ultimate goal. These include the pursuit of happiness and the avoidance of unnecessary suffering. Under the altered environmental conditions of our modern society, however, these natural regulatory mechanisms often no longer function as they did under the conditions in which they evolved. This gives rise to misguidance, known as evolutionary mismatch (Yong & Kanazawa, 2026). However, we possess the cognitive capacity to correct such misguidance, at least in part, through conscious value judgments (Delor, 2026).

Conclusion

Utilitarianism confuses happiness and suffering as reward and punishment mechanisms with the ultimate goal and adds a generalized maximization maxim that can neither be justified nor be empirically testable and substantive. Anyone seeking to reconstruct ethics objectively must do so on the basis of the goals that actually exist in living systems. Lineage fitness provides precisely this objective standard and remains open to criticism and empirically testable in both its derivation and its normative consequences. The is–ought problem is thus solved for the first time under the best epistemological assumptions we know, which also underlie modern science and the Enlightenment (Delor, 2026).

Serious criticism is welcome. It must identify errors in the argument or its foundations. An alternative framework must solve the problem better. Merely appealing to the paradigm being challenged is insufficient.

References

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• Bunge, M., & Mahner, M. (2004). Über die Natur der Dinge. S. Hirzel.
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• Frankena, W. K. (1939). The naturalistic fallacy. Mind, 48(192), 464–477.
• Harris, S. (2010). The Moral Landscape: How Science Can Determine Human Values. Free Press.
• Hayek, F. A. (1945). The use of knowledge in society. American Economic Review, 35(4), 519–530.
• Mill, J. S. (1861). Utilitarianism. First published in Fraser’s Magazine.
• Moore, G. E. (1903). Principia Ethica. Cambridge University Press.
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• Taleb, N. N. (2018). Skin in the Game: Hidden Asymmetries in Daily Life. Random House.
• Yong, J. C., & Kanazawa, S. (2026). Why evolutionary mismatches are ubiquitous while evolutionary matches are rare when humans use technology. Evolutionary Behavioral Sciences, 20(1), 88–102. https://doi.org/10.1037/ebs0000383