God and Design

The Teleological Argument and Modern Science

Neil A. Manson

• Publisher: Routledge
• Year: 2003
• Print ISBN: 9780415263443
• eBook ISBN: 9781134574599
• Edition: 1
• Topic: Theology & Religion
• Subtopic: Theology

Recent discoveries in physics, cosmology, and biochemistry have captured the public imagination and made the Design Argument - the theory that God created the world according to a specific plan - the object of renewed scientific and philosophical interest. This accessible but serious introduction to the design problem brings together new perspectives from prominent scientists and philosophers including Paul Davies, Richard Swinburne, Sir Martin Rees, Michael Behe, Elliot Sober and Peter van Inwagen.
It probes the relationship between modern science and religious belief, considering their points of conflict and their many points of similarity. Is the real God of creationism the 'master clockmaker' who sets the world's mechanism on a perfectly enduring course, or a miraculous presence who continually intervenes in and alters the world we know? Are science and faith, or evolution and creation, really in conflict at all? Expanding the parameters of a lively and urgent debate, God and Design considers how perennial questions of origin continue to fascinate and disturb us.

Part I

General Considerations

1

The Design Argument

Elliott Sober

The design argument is one of three main arguments for the existence of God; the others are the ontological argument and the cosmological argument. Unlike the ontological argument, the design argument and the cosmological argument are a posteriori. And whereas the cosmological argument could focus on any present event to get the ball rolling (arguing that it must trace back to a first cause, namely God), design theorists are usually more selective.

Design arguments have typically been of two types—organismic and cosmic. Organismic design arguments start with the observation that organisms have features that adapt them to the environments in which they live and that exhibit a kind of delicacy. Consider, for example, the vertebrate eye. This organ helps organisms survive by permitting them to perceive objects in their environment And were the parts of the eye even slightly different in their shape and assembly, the resulting organ would not allow us to see. Cosmic design arguments begin with an observation concerning features of the entire cosmos—the Universe obeys simple laws, it has a kind of stability, its physical features permit life and intelligent life to exist. However, not all design arguments fit into these two neat compartments. Kepler, for example, thought that the face we see when we look at the moon requires explanation in terms of intelligent design. Still, the common thread is that design theorists describe some empirical feature of the world and argue that this feature points towards an explanation in terms of God’s intentional planning and away from an explanation in terms of mindless natural processes.

The design argument raises epistemological questions that go beyond its traditional theological context. As William Paley (1802) observed, when we find a watch while walking across a heath, we unhesitatingly infer that it was produced by an intelligent designer. No such inference forces itself upon us when we observe a stone. Why is explanation in terms of intelligent design so compelling in the one case, but not in the other? Similarly, when we observe the behavior of our fellow human beings, we find it irresistible to think that they have minds that are filled with beliefs and desires. And when we observe nonhuman organisms, the impulse to invoke mentalistic explanations is often very strong, especially when they look a lot like us. When does the behavior of an organism—human or not—warrant this mentalistic interpretation? The same question can be posed about machines. Few of us feel tempted to attribute beliefs and desires to hand calculators. We use calculators to help us add, but they don’t literally figure out sums; in this respect, calculators are like pieces of paper on which we scribble our calculations. There is an important difference between a device that we use to help us think and a device that itself thinks. However, when a computer plays a decent game of chess, we may find it useful to explain and predict its behavior by thinking of it as having goals and deploying strategies (Dennett 1987b). Is this merely a useful fiction, or does the machine really have a mind? And if we think that present-day chess-playing computers are, strictly speaking, mindless, what would it take for a machine to pass the test? Surely, as Turing (1950) observed, it needn’t look like us. In all these contexts, we face the problem of other minds (Sober 2000a). If we understood the ground rules in this general epistemological problem, that would help us think about the design argument for the existence of God. And, conversely, if we could get clear on the theological design argument, that might throw light on epistemological problems that are not theological in character.

What is the Design Argument?

The design argument, like the ontological argument, raises subtle questions about what the logical structure of the argument really is. My main concern here will not be to describe how various thinkers have presented the design argument, but to find the soundest formulation that the argument can be given.

The best version of the design argument, in my opinion, uses an inferential idea that probabilists call the likelihood principle (LP). This can be illustrated by way of Paley’s (1802) example of the watch on the heath. Paley describes an observation that he claims discriminates between two hypotheses:

(W)	O1:	the watch has features G1…Gn.
	W1:	the watch was created by an intelligent designer.
	W2:	the watch was produced by a mindless chance process.

Paley’s idea is that O₁ would be unsurprising if W₁ were true, but would be very surprising if W₂ were true. This is supposed to show that O₁ favors W₁ over W₂; O₁ supports W₁ more than it supports W₂. Surprise is a matter of degree; it can be captured by the concept of conditional probability. The probability of observation (O) given hypothesis (H)—Pr(O|H)—represents how unsurprising O would be if H were true. LP says that comparing such conditional probabilities is the way to decide what the direction is in which the evidence points:

(LP) Observation O supports hypothesis H₁ more than it supports hypothesis H₂ if and only if Pr(O|H₁)>Pr(O|H₂).

There is a lot to say on the question of why the likelihood principle should be accepted (Hacking 1965; Edwards 1972; Royall 1997; Forster and Sober 2003); for the purposes of this essay, I will take it as a given.

We now can describe the likelihood version of the design argument for the existence of God, again taking our lead from one of Paley’s favorite examples of a delicate adaptation. The basic format is to compare two hypotheses as possible explanations of a single observation:

(E)	O2:	the vertebrate eye has features F1…Fn.
	E1:	the vertebrate eye was created by an intelligent designer.
	E2:	the vertebrate eye was produced by a mindless chance process.

We do not hesitate to conclude that the observations strongly favor Design over Chance in the case of argument (W); Paley claims that precisely the same conclusion should be drawn in the case of the propositions assembled in (E).¹

Clarifications

Several points of clarification are needed here concerning likelihood in general and the likelihood version of the design argument in particular. First, I use the term “likelihood” in a technical sense. Likelihood is not the same as probability. To say that H has a high likelihood, given observation O, is to comment on the value of Pr(O|H), not on the value of Pr(H|O); the latter is H’s posterior probability. It is perfectly possible for a hypothesis to have a high likelihood and a low posterior probability. When you hear noises in your attic, this confers a high likelihood on the hypothesis that there are gremlins up there bowling, but few of us would conclude that this hypothesis is probably true.

Although the likelihood of H (given O) and the probability of H (given O) are different quantities, they are related. The relationship is given by Bayes’s theorem:

Pr(H|O)=Pr(O|H) • Pr(H)/Pr(O).

Pr(H) is the hypothesis’ prior probability—the probability that H has before we take the observation O into account. From Bayes’s theorem we can deduce the following:

Pr(H₁|O)>Pr(H₂|O) if and only if Pr(O|H₁) • Pr(H₁)>Pr(O|H₂) • Pr(H₂).

Which hypothesis has the higher posterior probability depends on how their likelihoods are related, but also on how their prior probabilities are related. This explains why the likelihood version of the design argument does not show that Design is more probable than Chance. To draw this further conclusion, we would have to say something about the prior probabilities of the two hypotheses. It is here that I wish to demur (and this is what separates me from card-carrying Bayesians). Each of us perhaps has some subjective degree of belief, before we consider the design argument, in each of the two hypotheses (E₁) and (E₂). However, I see no way to understand the idea that the two hypotheses have objective prior probabilities. Since I would like to restrict the design argument as much as possible to matters that are objective, I will not represent it as an argument concerning which hypothesis is more probable. However, those who have prior degrees of belief in (E₁) and (E₂) may use the likelihood argument to update their subjective probabilities. The likelihood version of the design argument says that the observation O₂ should lead you to increase your degree of belief in (E₁) and reduce your degree of belief in (E₂).

My restriction of the design argument to an assessment of likelihoods, not probabilities, reflects a more general point of view. Scientific theories often have implications about which observations are probable (and which are improbable), but it rarely makes sense to describe them as having objective probabilities. Newton’s law of gravitation (along with suitable background assumptions) tells us that the return of Halley’s comet was to be expected, but what is the probability that Newton’s law is true? Hypotheses have objective probabilities when they describe possible outcomes of a chance process. But as far as anyone knows, the laws that govern our universe were not the result of a chance process. Bayesians think that all hypotheses have probabilities; the position I am advocating sees this as a special feature of some hypotheses.²

Not only do likelihood considerations leave open what probabilities one should assign to the competing hypotheses; they also don’t tell you which hypothesis you should believe. I take it that belief is a dichotomous concept—you either believe a proposition or you do not. Consistent with this is the idea that there are three attitudes one might take to a statement—you can believe it true, believe it false, or withhold judgment. However, there is no simple connection of the matter-of-degree concept of probability to the dichotomous (or trichotomous) concept of belief. This is the lesson I extract from the lottery paradox (Kyburg 1961). Suppose 100,000 tickets are sold in a fair lottery; one ticket will win and each has the same chance of winning. It follows that each ticket has a very high probability of not winning. If you adopt the policy of believing a proposition when it has a high probability, you will believe of each ticket that it will not win. However, this conclusion contradicts the assumption that the lottery is fair. What this shows is that high probability does not suffice for belief (and low probability does not suffice for disbelief). It is for this reason that many Bayesians prefer to say that individuals have degrees of belief. The rules for the dichotomous concept are unclear; the matter-of-degree concept at least has the advantage of being anchored to the probability calculus.

In summary, likelihood arguments have rather modest pretensions. They don’t tell you which hypotheses to believe; in fact, they don’t even tell you which hypotheses are probably true. Rather, they evaluate how the observations at hand discriminate among the hypotheses under consideration.

I now turn to some details concerning the likelihood version of the design argument. The first concerns the meaning of the intelligent design hypothesis. This hypothesis occurs in (W₁) in connection with the watch and in (E₁) in connection with the vertebrate eye. In the case of the watch, Paley did not dream that he was offering an argument for the existence of God. However, in the case of the eye, Paley thought that the intelligent designer under discussion was God Himself. Why are these cases different? The bare bones of the likelihood arguments (W) and (E) do not say. What Paley had in mind is that building the vertebrate eye and the other adaptive features which organisms exhibit requires an intelligence far greater than anything that human beings could muster. This is a point that we will revisit at the end of this essay.

It is also important to understand the nature of the hypothesis with which the intelligent design hypothesis competes. I have used the term “chance” to express this alternative hypothesis. In large measure, this is because design theorists often think of chance as the alternative to design. Paley is again exemplary. Natural Theology is filled with examples like that of the vertebrate eye. Paley was not content to describe a few cases of delicate adaptations; he wanted to make sure that even if he got a few details wrong, the weight of evidence would still be overwhelming. For example, in Chapter 15 he considers the fact that our eyes point in the same direction as our feet; this has the convenient consequence that we can see where we are going. The obvious explanation, Paley (1802:179) says, is intelligent design. This is because the alternative is that the direction of our eyes and the direction of our gait were determined by chance, which would mean that there was only a 1/4 probability that our eyes would be able to scan the quadrant into which we are about to step.

I construe the idea of chance in a particular way. To say that an outcome is the result of a uniform chance process means that it was one of a number of equiprobable outcomes. Examples in the real world that come close to being uniform chance processes may be found in gambling devices—spinning a roulette wheel, drawing from a deck of cards, tossing a coin. The term “random” becomes more and more appropriate as real-world systems approximate uniform chance processes. As R.A.Fisher once pointed out, it is not a “matter of chance” that casinos turn a profit each year, nor should this be regarded as a “random” event. The financial bottom line at a casino is the result of a large number of chance events, but the rules of the game make it enormously probable (though not certain) that casinos end each. year in the black. All uniform chance processes are probabilistic, but not all probabilistic outcomes are “due to chance.”

It follows that the two hypotheses considered in my likelihood rendition of the design argument are not exhaustive. Mindless uniform chance is one alternative to intelligent design, but it is not the only one. This point has an important bearing on the dramatic change in fortunes that the design argument experienced with the advent of Darwin’s (1859) theory of evolution. The process of evolution by natural selection is not a uniform chance process. The process has two parts. Novel traits arise in individual organisms “by chance”; however, whether they then disappear from the population or increase in frequency and eventually reach 100 percent representation is anything but a “matter of chance.” The central idea of natural selection is that traits which help organisms survive and reproduce have a better chance of becoming common than traits that hurt. The essence of natural selection is that evolutionary outcomes have unequal probabilities. Paley and other design theorists writing before Darwin did not and could not cover all possible mindless natural processes. Paley addressed the alternative of uniform chance, not the alternative of natural selection.³

Just to nail down this point, I want to describe a version of the design argument formulated by John Arbuthnot. Arbuthnot (1710) carefully tabulated birth records in London over eighty-two years and noticed that, in each year, sligh...

Table of contents

• Cover Page
• Half Title page
• Title Page
• Copyright Page
• Contents
• List of Illustrations
• Notes on Contributors
• Preface
• Introduction
• Part I General Considerations
• Part II Physical Cosmology
• Part III Multiple Universes
• Part IV Biology
• Index