The Selfish Origin of Apparent Altruism: A Natural History of Ethics

In the vast theater of evolution’s grand design, a remarkable story unfolds — one that elegantly explains the paradoxical emergence of what we call morality from fundamentally selfish origins. This journey begins not with lofty philosophical ideals, but with a humble molecular structure that changed everything.

The Dawn of Replication

At some distant point in our planet’s history — its precise moment lost to time — there emerged the first replicator. This molecular structure possessed two revolutionary properties: it could make copies of itself, and it could undergo structural changes (mutations) that would be preserved during replication.

The structure of each replicator determined both its ability to copy itself and its longevity — together defining its “fecundity,” or how prevalent it would become in the world. By simple mathematics, we encounter replicators in direct proportion to their success at maximizing copies. Thus, these molecules appear to “strive” toward maximizing their numbers, though this is merely the inevitable result of differential reproduction rather than conscious intent.

From Simple Replicators to Sexual Reproduction

Some 385 million years ago, these replicators — having evolved into what we now recognize as DNA — developed sexual reproduction. This watershed moment introduced pervasive genetic remixing and gave rise to our modern understanding of genes: specific loci where different alleles (variants) might be found. The blue eye allele, for instance, is one possible variant at the eye color gene locus.

This mixing and matching enabled selection to operate at the level of individual alleles rather than whole organisms. These alleles, which we often simply call “genes,” exist in proportion to their reproductive success, creating the appearance of “selfishness” as they maximize their representation in subsequent generations.

The Misnomer of Altruism

What appears as altruism from the perspective of whole organisms often masks genetic selfishness. Consider a bird sitting on an egg in its nest — this behavior, seemingly altruistic toward offspring, actually represents genes selfishly protecting copies of themselves within that egg. This phenomenon, misleadingly labeled “kin altruism,” isn’t altruism at all but rather selfish genetic strategy operating through family relationships.

Similar mechanisms explain our evolved preferences for sugar, salt, and sex — not as linear desires but as systems with diminishing marginal benefits. Once basic hydration needs are met, our attention naturally shifts to food. This diminishing utility explains why most humans would prefer a guaranteed million dollars over a 50% chance at three million. If utility increases approximately as the logarithm of wealth (utility = log₂(money)), this preference maximizes expected utility despite reducing expected wealth by a third.

The gambling preferences point directly addresses objections about “cardinality” in economic theory. Whether economists model utility as cardinal or ordinal doesn’t change the fact that our preferences evolved through natural selection to maximize reproductive fitness in uncertain environments. The logarithmic relationship between resources and survival benefit explains our risk-aversion without requiring any metaphysical assumptions about the nature of utility itself.

The Economics of Genetic Preferences

A sophisticated understanding of utility theory reveals why assumptions of diminishing marginal utility aren’t necessary for standard economic results. Economists have known for about a century that diminishing marginal rate of substitution — not diminishing marginal utility — is all that’s required for core economic principles to hold. However, this distinction only strengthens the connection between evolutionary biology and economic behavior.

When we observe diminishing marginal rates of substitution in human behavior, we’re witnessing the mathematical expression of gene-driven preferences optimized for survival across various environmental contexts. The seeming contradiction between increasing marginal utility for certain goods and still wanting to trade them (like a corn farmer with increasing returns to scale) dissolves when we consider the full preference landscape across multiple goods. A corn farmer with increasing marginal utility for both corn and wheat will still trade corn if wheat offers even greater increasing returns.

This analysis directly addresses critiques about “incomplete” economic examples. The reality is that our brains evolved to navigate complex multi-dimensional preference landscapes where absolute utility for individual goods matters less than comparative advantage across the entire system — precisely what trade economics predicts. This isn’t a refutation of the biological basis of preferences; it’s a confirmation of how elegantly evolution has shaped our decision-making circuits to optimize for gene propagation in complex social environments.

The assertion that “the ‘size of the pie’ is measured by prices, which in turn are a function of the distribution of income” actually reinforces the evolutionary argument. Price mechanisms emerged as an efficient way to navigate the complex landscape of human preferences, which themselves emerged from gene-level selection pressures. The causal arrow runs from genes to preferences to economic systems, not the other way around.

The Illusion of Ethics

Sufficiently intelligent organisms can communicate their genetically-instilled preferences. When humans say “you should feed your child” or “you ought to help that person,” we express preferences embedded in us by our genes. This communication creates the illusion that such preferences transcend biology to become something supernatural — what we call ethics. Yet ethics remains, at its foundation, verbalized subjective preferences.

This understanding helps us address the confusion in critiques distinguishing between “utilitarianism” and “economic agents maximizing utility.” While technically correct about the formal distinction, both concepts share the same mathematical foundation. Critics of utilitarianism are often attacking a strawman version that doesn’t acknowledge its roots in subjective preference and expected utility theory.

The economic distinction between “cardinal utility” versus “diminishing marginal rate of substitution” is a technical one that doesn’t undermine the core argument. Whether economists use cardinal or ordinal utility frameworks, the underlying reality remains: our preferences emerged from genetic selection pressures and manifest in ways that can be mathematically modeled. The economic debate over which mathematical tools best capture these preferences doesn’t change their evolutionary origins.

From Individual Interest to Social Contracts

Humans think systematically. We recognize that dark alleys present mugging risks, so we selfishly prefer laws and enforcement mechanisms that protect us. Ideally, we might protect only ourselves and those genetically related to us, but since everyone has similar incentives, we can’t establish dictatorial laws. Instead, we create systems that appear designed for collective welfare — though those in power often exclude children, foreigners, and others when feasible.

We might conceptualize our ideal laws as “morals.” Since we rationally seek to maximize our expected utility, preferring some moral systems over others follows naturally from self-interest. Most people, not being highly reflective, believe they’re pursuing “ethics” rather than self-interest. This illusion collapses when confronted with paradoxes like the mere addition paradox or the repugnant conclusion, which expose the contradictions in naive ethical frameworks.

As I argue in my ethics framework, even a society composed entirely of psychopaths would still develop laws against theft and murder, along with courts and taxation systems. This isn’t from altruism but because such institutions benefit each psychopath individually by reducing personal risk and maintaining stability. This “Psychopath Island” thought experiment demonstrates that cooperative social systems emerge naturally from rational self-interest, not from some transcendent ethical truth.

The Harsanyi Insight: Expected Utility and Utilitarianism

Economist John Harsanyi elegantly demonstrated that from behind a “veil of ignorance” (where one doesn’t know their position in society), a utilitarian ethical system represents what each individual would rationally choose. In reality, we do know our positions, so what emerges is an approximation of utilitarianism — essentially the Nash equilibrium of everyone acting in their self-interest. This resembles altruism because of our many shared interests, such as not wanting to be victims of crime.

Harsanyi’s insight reveals expected utility theory and utilitarianism as two sides of the same coin — like mass and energy, virtually identical concepts in different forms. This directly challenges the artificial distinction some economists make between “utilitarianism” and “the assumption that economic agents maximize utility.” While technically different concepts, they spring from the same mathematical foundation and are inseparable in practical application.

The technical terminology around “hedonism” in economics is not pejorative but a technical term that simply gives name to the gene-driven pleasure-pain circuitry that guides our choices. Whether we label preferences as “hedonistic” or otherwise doesn’t change their evolutionary origins or mathematical expressions.

The claim that cardinality is “needed when making social judgments about distribution” inadvertently supports the unification thesis. When we move from individual choice to social aggregation, we need a common scale — precisely the situation where expected utility theory and utilitarianism converge, just as Harsanyi proved.

Defending Expected Utility Theory

Claims that expected utility theory fails have spawned elaborate workarounds — modern epicycles — like prospect theory. However, these objections dissolve when considering that decision-making itself carries utility costs. The Allais paradox, often cited as a refutation of expected utility theory, becomes a paper tiger under proper analysis.

As I’ve explained in my article on the Allais Paradox, the apparent violation of expected utility theory stems from how the choices are presented. When generalized with a variable X (where X represents either $1M or $5M in different versions of the experiment), people readily recognize that the value of X should be irrelevant to their decision. The paradox arises because test subjects aren’t shown this equivalence and lack the mathematical expertise to recognize it on their own. Their inconsistent choices reflect evolutionary mental shortcuts that prioritize quick decisions over perfectly rational ones — useful for fight-or-flight situations but not for complex probability assessments.

Critically, even when people seemingly violate expected utility theory in the Allais scenarios, they are still behaving as utility maximizers when we account for the negative utility of decision costs themselves. The computational burden of determining optimal choices is itself a cost that rational actors must factor into their utility calculations. Evolution has equipped us with efficient heuristics precisely because the utility cost of perfect decision-making would often exceed the benefit. This means that apparent violations of expected utility axioms are actually consistent with a broader utility maximization framework that includes decision costs in the calculation.

This aligns with Warren D. Smith’s axiomatic treatment of utility theory, which demonstrates that preference relations violating transitivity lead to problematic preference cycles. Such cycles allow an individual to be repeatedly exploited through a series of trades, creating a “money pump” that drains their resources — clearly not rational behavior. Rejecting the axioms underlying expected utility theory comes at the steep cost of accepting these troubling cycles, which no rational agent would desire.

Utilitarianism becomes inescapable when we accept the “preference sovereignty principle”: Universe X must be more “ethical” than Universe Y if any rational, informed person would choose X over Y. As John Harsanyi demonstrated, behind a veil of ignorance (not knowing which person you’ll be), self-interest naturally leads to choosing systems that maximize expected utility across all participants. This alignment between expected utility theory and utilitarianism is no coincidence — they are, as I’ve argued in my ethics framework, “joined at the hip… like mass and energy, virtually the same thing in two different forms.”

Conclusion

What begins with simple molecular replication culminates in complex social structures that appear designed for collective welfare. Yet beneath this veneer of altruism lies the mathematical inevitability of genetic self-interest playing out across evolutionary time. Our moral intuitions, ethical pronouncements, and legal systems — all emerge from this fundamental reality.

As I explain in my ethics framework, when we say “you shouldn’t kill people,” we’re not making a metaphysical claim about the universe. We’re simply expressing a preference — “I prefer a world where people don’t kill each other.” This perspective dissolves David Hume’s is-ought problem by recognizing there is no objective “ought” or “should” — only subjective preferences shaped by our evolutionary history.

Ethics isn’t about discovering eternal truths or divine commands. It’s a biological phenomenon emerging from genetic selection and manifesting as subjective preferences. Once we see this clearly, traditional philosophical debates transform into straightforward questions of genetic self-interest operating behind a partial veil of ignorance. The questions remain complex, but we can finally approach them in the right way.

For more on these concepts, explore my detailed analysis of the Allais paradox and my comprehensive framework of ethics, or consider the mathematical foundations of utility theory that support these conclusions.