The Meaning of Human Existence (17 page)

The claim that the regression method identifies the causes of allele frequency change cannot be correct, because regression can only identify correlation, and correlation does not imply causation. Moreover, because the regression method attempts to find additive social fitness effects that match given data, we should expect it to yield misleading results when social interactions are not additive, or when fitness variation is caused by other factors. Based on this principle, we present three hypothetical scenarios in which the regression method mischaracterizes the reasons for frequency change.

In the first hypothetical scenario, a “hanger-on” trait leads its bearers to seek out and interact with individuals of high fitness.
We suppose that these interactions do not affect fitness. However, this seeking-out behavior leads fitness to become positively correlated with having a hanger-on as a partner; thus the regression method yields
B
> 0. According to the proposed interpretation, hangers-on should be understood as cooperative, bestowing high fitness on their partners. However, of course this gets causality backward—the high fitness causes the interaction, not the other way around.

Variants of this hanger-on behavior may occur in many biological systems. A bird may choose to join the nest of a high-fitness pair, with the goal of eventually inheriting the nest. Similarly, a social wasp may be more likely to stay at its parents’ nest if the parent has high fitness, also with the goal of eventual inheritance. Applying the regression method to these situations would lead one to mistake purely self-interested behaviors for cooperation.

The second example is a “jealous” trait. Jealous individuals seek out high-fitness partners and attack them with the aim of reducing their fitness. We suppose that these attacks are costly to the attacker but only mildly effective, so that the attacked individuals still have above-average fitness after the attacks. The regression method yields
B
,
C
> 0, suggesting that the jealous individuals are engaged in costly cooperation. Again, this interpretation is wrong: the attacks are harmful, and the positive fitness correlation is due to the choice of interaction partners and the ineffectiveness of the attacks.

The third example is a “nurse” trait. A nurse will seek out
low-fitness individuals and make costly attempts to improve their fitness. We suppose, however, that this aid is only mildly effective, so that the aided individuals still have below-average fitness. The regression method yields
B
< 0,
C
> 0, misinterpreting this remaining low fitness as due to costly sabotage on the part of the nurses.

“Assumption-Free” Approaches

Finally, we turn to the claim that inclusive fitness theory is “as general as the genetical theory of natural selection itself.” The argument is that, because the regression method can be applied to an arbitrary change in allele frequency (regardless of the actual causes of this change), it follows that every instance of natural selection is explained by inclusive fitness theory.

However, as we have seen, the regression method yields a “just-so story” that does not predict or explain anything about the given scenario or any other. Of course, there can exist cases for which the regression method yields correct causal explanations, and there can also exist cases for which the results obtained for one scenario are approximately accurate for certain others. However, the regression method provides no criteria to identify these cases—indeed, to formulate such criteria would require additional assumptions about the underlying processes. Without such assumptions, the results of the regression method do not answer any scientific question
about the situation under study. The claim of generality is therefore meaningless.

This lack of utility is not due to any technical oversight. Rather, it arises from the attempt to extend Hamilton’s rule to every instance of natural selection. This impulse is understandable, given the intuitive appeal of Hamilton’s original formulation. However, the power of a theoretical framework is derived from its assumptions, thus a theory with no assumptions cannot predict or explain anything. As Wittgenstein argued in his
Tractatus Logico-Philosophicus
, any statement that is true in all situations contains no specific information about any particular situation.

There Is No Universal Design Principle

The concept of inclusive fitness arises when one attempts to explain the evolution of social behavior at the level of the individual. For example, inclusive fitness theory seeks to explain the existence of sterile ant workers in terms of the behaviors of the workers themselves. The proposed explanation is that workers maximize their inclusive fitness by helping the queen rather than producing their own offspring.

The claim that evolution maximizes inclusive fitness has been interpreted as a universal design principle for evolution. This claim is based on an argument by Hamilton that evolution maximizes the mean inclusive fitness of a population, and a separate argument by Alan Grafen that evolved
organisms act as if to maximize their inclusive fitness. Both of these arguments depend on restrictive assumptions, including additivity of fitness effects. Because experiments have shown that fitness effects in real biological populations are nonadditive, these results cannot be expected to hold in general. Moreover, both theory and experiment have shown that frequency-dependent selection can lead to complex dynamic phenomena such as multiple and mixed equilibria, limit cycles, and chaotic attractors, ruling out the possibility of general maximands. Thus, evolution does not, in general, lead to the maximization of inclusive fitness or any other quantity.

Commonsense Approaches to Evolutionary Theory

Fortunately, no universal maximands or design principles are needed to understand the evolution of social behavior. Rather, we may rely on a straightforward genetic approach: Consider mutations that modify behavior. Under which conditions are these mutations favored (or disfavored) by natural selection? The target of selection is not the individual, but the allele or the genomic ensemble that affects behavior.

To investigate these questions theoretically, one needs modeling assumptions. These assumptions can be highly specific, applying only to particular biological situations, or broad, applying to a wide range of scenarios. Modeling frameworks that rely on general (yet precise) assumptions have
recently emerged as a powerful tool for studying the evolution of populations structured spatially, by groups, and physiologically; the evolution of continuous traits; and inclusive fitness theory itself (in cases where fitness effects are additive and other requirements are satisfied). Although these frameworks can be used to obtain general results, none of them is universal or assumption-free. Instead, they draw upon their assumptions to make well-defined, testable predictions about the systems to which they apply.

Discussion

Inclusive fitness theory attempts to find a universal design principle for evolution that applies at the level of the individual. The result is an unobservable quantity that does not exist in general (if additivity is required) or has no predictive or explanatory value (if the regression method is used). If instead we take a genetic perspective and ask whether natural selection will favor or oppose alleles that modify social behavior, there is no need for inclusive fitness.

The dominance of inclusive fitness theory has held up progress in this area for many decades. It has consistently suppressed reasonable criticism and alternative approaches. In particular, the attempt to eschew the requirement of additivity using regression methods has led to logical obfuscation and false claims of universality. Reasonable inclusive fitness calculations that assume additivity represent an alternative
method to account for fitness effects in some limited situations, but this method is never necessary and often needlessly complicated. There is no problem in evolutionary biology that requires an analysis based on inclusive fitness.

Having realized the limitations of inclusive fitness, sociobiology now has the possibility to move forward. We encourage the development of realistic models grounded in a firm understanding of natural history. With the aid of population genetics, evolutionary game theory, and new analytic procedures to be developed, a strong and resilient sociobiological theory can emerge.

Acknowledgments

I am grateful to John Taylor (Ike) Williams for his unwavering support and advice, to Robert Weil for his editorial guidance on this as on my earlier books published by W. W. Norton, and to Kathleen M. Horton for her invaluable assistance in research, editorial work, and manuscript preparation.

Chapter 2
, “Solving the Riddle of the Human Species,” is a modification of the author’s “The Riddle of the Human Species,” in
The New York Times Opinionator
, February 24, 2013.
Chapter 3
, “Evolution and Our Inner Conflict” was modified from an article of that name by the author, in
The New York Times Opinionator
, June 24, 2012.
Chapter 11
, “The Collapse of Biodiversity,” is a modified version of “Beware the Age of Loneliness,” in
The World in 2014, The Economist
, November 2013, p. 143.

Index

Page numbers listed correspond to the print edition of this book. You can use your device’s search function to locate particular terms in the text.

Absolute Paradox (Kierkegaard), 157–58

academia, Harvard, 40–41

Age of Loneliness (Eremocene), 123

alien life, 45, 53–55, 102–4, 106

Allen, Benjamin, 74, 189–202

allomones, 81–82

anole lizards, 138

Antarctica, life, 104

Anthropocene, 123

anthropocentricity, 42–43

ants, 65, 83, 86–88, 95–97, 166

arachnophobia, 139–40

archaeans, 47, 104, 108, 111

artificial life, 58

australopiths, 175

Bacon, Francis, 38, 133, 136

bacteria, communication, 89
see also
microbes

BAM (Brain Activity Map), 163–64

biodiversity, 46–50, 123–32

biosphere, 46–50

bird song, 81

BNR (biology, nanotechnology, robotics), 58

brain, human,
see
mind

Bruller, Jean, 135

campsites, 21–22

Carlson, Anton J., 153

causation, proximate versus ultimate, 15

chimpanzees, 175

Churchland, Patricia, 161

confliction, moral, 27–34

confabulation, 167–68

conquest of galaxy, 119–22

conscience, origin, 27–34, 179–80

consciousness, 159–70

consilience (unity of knowledge), 35–75

continuum, concept, examples, 44–52, 167, 186

cooperation, origin, 21–22, 29–31

Copernicus, 46

Creationism, 183–85

creation stories, 12, 18, 151–58, 181–85

creative arts, 17, 22, 35–75, 79, 186

culture, origin, 37–75, 80, 100, 105, 141–46

Darwin, Charles, 29, 162–63, 178, 183

Dawkins, Richard, 70, 73

Deinococcus
, 104–5

Dennett, Daniel, 161

driver ants, 92–94

driving forces of evolution, 23–24, 61–75, 189–202

dysfunction, innate human property, 176–80

ecosystems, 105, 120, 124–26, 144

Edelman, Gerald, 159

emergent evolution, 165

emotion, 167
see also
mind; phobias

Enceladus, 105–6

Enlightenment, 37–40, 51–52

Eremozoic Era, 123

E.T., 104–22

eugenics, 58–59