One of the arguments commonly advanced for the necessity of an Intelligent Creator is the Intelligent Design (ID) syllogism. Briefly, the argument goes that the complexity and sophistication of the universe -- particularly in the context of biological systems -- is so advanced that it must have been designed by an intelligent entity.
Most man-made objects -- a chair, a corkscrew, a computer -- possess two features: 1) complexity -- by which I mean the arrangement of matter in a nontrivial manner and 2) utility which emerges from that complexity -- the four legs of a chair enable it to stand firmly on the ground; its seat allows a person to sit comfortably.
A naturally occurring phenomenon with only one of these factors -- i.e. only complexity or only utility -- will not necessarily engender the feeling that it was designed in an intelligent fashion. The weather patterns of Earth’s atmosphere are highly complex, resulting from large numbers of variables interacting in a chaotic way. But most people wouldn’t immediately assume the fact that it was sunny yesterday and rainy today is the result of an intelligent agent manipulating all those myriad variables in order to ruin their picnic. [I suppose if you lived in a Bronze Age agrarian society, the unpredictable behavior of the rainy season would serve as the foundation of your religious beliefs. But that’s a different line of thinking than ID.] Conversely, “unsophisticated" objects such as rocks do not give the impression that they were engineered even though they are very useful for throwing at people that you don’t like. Only when utility is combined with complexity do we get the sense that there must have been some kind of intelligence at play.
It is probably for this reason that proponents of ID tend to focus on biology, rather than chemistry or physics, to support the notion that the universe must have had a designer. Biological organisms are undoubtedly quite complex, even at the level of a single cell, but what makes biology truly seem engineered is the fact that the complexity usually serves a well-defined purpose. This is not to say that biological organisms are “useful” in a cosmic sense -- the galaxy would get along just fine without the red-eyed tree frog -- but rather that the different components within an organism clearly play a useful role in the survival of that organism. The frog’s eyes help it to see flies; its long tongue allows it to catch and eat them. The complexity of the frog organism is clearly intended to serve the purpose of ensuring frog survival. So ID comes along and says, “Aha! The frog has complexity and utility, therefore intelligence must have been involved.”
The problem with this line of reasoning is that the presumption of intelligence being a prerequisite for complexity and utility stems from an observation of man-made things. If we start from the vantage point of artificial objects, it is easy to say “all complex, useful man-made objects require intelligence, therefore every complex and useful object requires intelligence.” However, If we start by looking at the world as a whole, we realize that there are ab initio two types of things that possess both complexity and utility: artificial, man-made objects and the biological mechanisms of living organisms. Objects in the first category are produced by the ostensibly intelligent homo sapiens, but it is not immediately apparent that objects of the second category were built by an intelligent artificer.
It is probably for this reason that proponents of ID tend to focus on biology, rather than chemistry or physics, to support the notion that the universe must have had a designer. Biological organisms are undoubtedly quite complex, even at the level of a single cell, but what makes biology truly seem engineered is the fact that the complexity usually serves a well-defined purpose. This is not to say that biological organisms are “useful” in a cosmic sense -- the galaxy would get along just fine without the red-eyed tree frog -- but rather that the different components within an organism clearly play a useful role in the survival of that organism. The frog’s eyes help it to see flies; its long tongue allows it to catch and eat them. The complexity of the frog organism is clearly intended to serve the purpose of ensuring frog survival. So ID comes along and says, “Aha! The frog has complexity and utility, therefore intelligence must have been involved.”
The problem with this line of reasoning is that the presumption of intelligence being a prerequisite for complexity and utility stems from an observation of man-made things. If we start from the vantage point of artificial objects, it is easy to say “all complex, useful man-made objects require intelligence, therefore every complex and useful object requires intelligence.” However, If we start by looking at the world as a whole, we realize that there are ab initio two types of things that possess both complexity and utility: artificial, man-made objects and the biological mechanisms of living organisms. Objects in the first category are produced by the ostensibly intelligent homo sapiens, but it is not immediately apparent that objects of the second category were built by an intelligent artificer.
But how would complex, useful things arise without the input of intelligence? At this point it would be worthwhile to take a step back and ask a more general question: What is intelligence?
A very minimalistic way to define intelligence would be the way that many people in the field of artificial intelligence (AI) implicitly use the term: intelligence is the ability to utilize a strategy [or set of strategies] to achieve a particular goal. Consciousness, self-awareness, or free will are neither necessary nor sufficient conditions for intelligence. Under this definition, machines can possess intelligence to the same or greater degree as humans. An AI which possesses the ability to play chess can be more intelligent than a human when it comes to chess-playing.
A very minimalistic way to define intelligence would be the way that many people in the field of artificial intelligence (AI) implicitly use the term: intelligence is the ability to utilize a strategy [or set of strategies] to achieve a particular goal. Consciousness, self-awareness, or free will are neither necessary nor sufficient conditions for intelligence. Under this definition, machines can possess intelligence to the same or greater degree as humans. An AI which possesses the ability to play chess can be more intelligent than a human when it comes to chess-playing.
In AI, many (if not all) tasks can be framed as a “state-space search.” In other words, the problem of achieving a particular result boils down to choosing a correct strategy, or solution, out of a very large (and often infinite) set of possible incorrect solutions. For example, solving a maze can be reduced to the problem of searching through all the possible paths that one can draw for the one path that will take you from the start to the end without crossing any walls. A naive way to solve a maze would be to attempt every possible sequence of movements from the starting position until the end of the maze is reached. The is known as a “brute-force” technique, and is, of course, quite inefficient. At the end of the day, however, a brute force algorithm is guaranteed to find a solution given enough time. So is a brute-force algorithm “intelligent?” According to our definition of intelligence above, the answer is decidedly affirmative. Any system with the ability to randomly produce answers for an infinite amount of time -- such as a monkey randomly pressing buttons on a typewriter - can be considered intelligent. [Empirically, however, it turns out that if you stick a monkey in front of a typewriter it will just push down the ‘S’ button and pee all over the keyboard.]
Somehow, though, it doesn’t seem right that a strategy of guessing all possible answers until you arrive at the correct one should be considered “intelligent.” In common usage, intelligence isn’t just about “finding the answer”; intelligence also implies something about the efficiency of the strategy employed. While brute force may find the end of a maze eventually, it will also have to try every wrong path first (or half of them, on average.) So it might be better to update our definition of intelligence to “the ability to utilize a strategy to achieve a particular goal *efficiently*.
One can easily see how the two definitions of intelligence proposed above relate to the topic of Intelligent Design. If one assumes that nature has the ability to combine matter with “infinite diversity in infinite combinations”, as the Vulcans say, that means that nature can -- by brute-force -- come up with sophisticated objects that have utility, such as the frog’s eye. In practice, however, the odds of achieving this result -- even over the time course of several billion years -- is astronomically small.
This is where evolution comes in. To the average person, evolution is an abstract, pie-in-the sky description of a basically random process. Even for the biologist, it can sometimes be difficult to comprehend how the process of natural selection can result in something as sophisticated, as, say, the human brain. Computer scientists, on the other hand, especially those of us who do AI, routinely use the principles of evolution to solve difficult problems, usually completely unrelated to biology. A class of algorithms known as genetic or evolutionary algorithms take the most fundamental aspects of evolution -- survival of “fit” solutions, combinations and mutations of solutions, and destruction of unfit solutions -- to drastically simplify state-space search problems. A problem that could take years to solve by brute force can be solved in a matter of minutes by a genetic algorithm. A programmer can write a genetic algorithm in under an hour; the only tricky part is specifying a “fitness function” -- that is, a sliding scale criterion that evaluates how good a particular solution is. A genetic algorithm will often be able to find a very good solution (or at least a better solution that brute force) after a small number of iterations. The outcome of evolution -- biological or algorithmic -- can be quite complex, and the results are optimized to maximize fitness (or utility, to use the term mentioned earlier). From personal experience, it can be much easier to appreciate the immense problem-solving capacity of evolution once you write an evolutionary algorithm to help you solve a real-world task.
Despite its relative computational simplicity, I think that evolution thus fulfills our second definition of intelligence. Not only can evolution find good, sophisticated solutions to problems, it can also find them far more quickly and efficiently than monkeys on typewriters. So even with our more restrictive definition, biological organisms are indeed the result of an “intelligent” process. Once again, however, it seems like our definition of intelligence falls short of what we want it to mean. Evolution is effective, but does it know what it’s doing? Maybe when we talk about intelligence, what we really mean is *decision-making* based on *reasoning*: explicit derivation of consequences deductively from axioms or inductively from examples.
Still, neither free will nor consciousness are necessary for reason-based intelligence. Wolfram Alpha, an online software that solves math problems, uses a rule-based mathematics and logic system. If you give Wolfram Alpha a calculus problem, it will analyze the structure of the problem, decide on a sequence of mathematical rules to apply, and then spit back an answer, which you can then proceed to write on your homework assignment for an easy A. Here, though, we seem to have reached a kind of intelligence that is uniquely human--or at least man-made. No known natural system can engage in inductive or deductive reasoning to make decisions for the explicit purpose of accomplishing a particular task.
Except...what’s that? The brain? Yes, the brain.
It turns out that the brain, which is apparently the first object in the universe with the generalized ability to make decisions based on syllogistic reasoning, was designed by evolution. And it also turns out that (most of) our brains aren’t even that good at rote tasks of logical inference, so we designed computers and software like Wolfram Alpha to do that kind of thing in far more efficiently than we could ourselves.
In the end, we have this funny situation where the random behavior of matter -- which is the most general form of computation, brute force -- gave rise to the building blocks of biology, which allowed for the more refined and efficient computation of organisms optimized for their environment via an “evolutionary algorithm”. After a few billion years, evolution produced a new kind of intelligence -- the animal brain, which is capable of directly solving problems by sequentially applying rules. And then, after a few hundred million years, we designed computers which can store a lot of information and do a lot of rule-based calculations much faster than we can.
Each successive “intelligence” or computational system is more heavily optimized for the particular task is was designed for. Evolution is better than random particle interactions at designing an eye, and Wolfram Alpha is better than me at solving boring algebra problems. But in each iteration, it seems that we also lose something, namely the generality of computational ability. Biological evolution can’t design a solar system (or anything non-organic) and I can’t design an ecosystem of organisms from raw materials. And at the moment, a computer doesn’t seem to be able to write a coherent essay.
None of these limitations, however, are theoretical boundaries on computational ability, only physical ones. The Church-Turing thesis states that any calculable function can be computed by a Turing machine with an infinitely long tape. So a computer with infinite memory could simulate the entire universe, and maybe a brain with an infinite number of neurons (or dendrites, if you’re a single neuron computation guy) could too. Physically, though, neither my laptop nor my brain will have access to all of the matter, energy, or time in the universe. Our computational scope will always be inferior to that of the universe, even though the universe’s “computation” basically involves randomly smashing particles into each other. Instead, we optimize the resources that we do have to efficiently solve the very small subset of problems which are relevant to us.
So which of the systems outlined above possesses the most intelligence? Again, it’s all a question of definition. If you care about the ability to generate different combinations of matter, it’s the universe. If building brains is what’s most important to you, evolution is a more appropriate algorithm. If you want to solve problems that are relevant to surviving, thriving, and reproducing as an individual organism on planet Earth, well, the brain is pretty good at that. And if you need to add together some big numbers on your math test, the pocket calculator is your winner.
Where does this leave us humans? Well, if you still want to feel special, intelligence -- in the computational sense -- is probably not the direction to go in. Human intelligence does not seem to be particularly unique other than in the sense that it sits somewhere in between the naive, generalized brute-force intelligence of the cosmos and the highly efficient, narrowly-oriented intelligence of a computerized expert system. Consciousness and free will, broadly defined, are likely more promising avenues for understanding if and how the animal mind -- and the human mind in particular -- are unique. Science still has a long way to go before being able address those subjects, but, as with everything, we will try and fail until we succeed.
I just want to see if I understood the conceptual progression of this post. So an inference to intelligent design (ID) is ostensibly justified if whatever we're observing fits the following criteria: It is (1) complex (2) has a utility and is (3) efficient. You add criterion (3) in order to circumvent brute-force as a property that by itself can satisfy the first two criteria. But you conclude that (3) is trivial because a hierarchy of efficiency (illustrated as creatures or inanimate matter using heuristics or rules of reasoning to solve problems) can be developed from a foundation of brute-force (illustrated as creatures or inanimate matter going through an algorithmic process to either solve problems or by chance produce more efficient systems respectively). All you need is enough time and random interactions for brute-force to be a foundation for the hierarchy.
ReplyDeleteSomething like that, yes. That's a good restatement, thank you.
DeleteIf there is a "God of the Gaps" analogue fallacy for critics of ID, it might be termed brute-force of the gaps. Even allowing for a sufficient span of time (deep time) and random interactions of particles to generate different kinds of hierarchies exhibiting complexity, purposefulness, and efficiency, it is a mistake to conclude that ID is undermined as a useful and robust theory. It is also disingenuous to assume that "proponents of ID tend to focus on biology, rather than chemistry or physics."
DeleteIntelligent Design theory is of interest to a wide variety of fields, for example, archeology, cryptography, CSI, SETI etc. We make causal and meaningful design inferences on a daily basis, moreover. ID theorists have offered a number of sophisticated accounts of what justifies a design inference. One of which, by William Dembski in Cambridge University Press’s series on Probability, Induction, and Decision Theory, argues that a design inference is justified when two conditions are met: (1) the observed is extraordinarily improbable and (2) it corresponds to an independently given pattern.
While disagreement may exist over which theory of design inference is correct, this is hardly the point at which Intelligent Design encounters heated opposition. Its application to the field of biology is what tends to bring about controversy, not that ID theorists are desperately focused on biology. Some typical objectors, like Richard Dawkins, reject Intelligent Design out of anti-metaphysical or, rather, anti-religious motives. It appears the analysis here rejects ID, as applied to biology, based on ad hominem: “we still want to feel special" yet we somehow ought to be disillusioned once we realize that intelligence is a conspicuous term. The conjoined observations entail nothing interesting.
It could be that the underlying objection is the belief that ID is just religion masquerading as science. But ID theorists have repeatedly insisted that the design inference is not an inference to theism but merely to some sort of intelligent agency. This disclaimer is not, I think, disingenuous, since they do not claim to be able to infer such qualities that traditional theism ascribes to God, which leaves the door open for other intelligent agents as responsible for biological design.
Ironically, Dawkins actually agrees with the most fundamental tenets of Intelligent Design theory: (i) that Intelligent Design is a scientific hypothesis which should be assessed as such, (ii) that it is illegitimate to exclude a priori from the pool of explanatory options hypotheses which appeal to final causes or even supernatural beings, and (iii) that the design inference is not to be equated with an inference to theism. What follows is that ID is not religious creationism masquerading as science.
So if we want to dispute ID in general, or more specifically, undermine its application to the field of biology, it cannot be done by simply reasserting naturalistic tenets. Randomness and time, the brute force that may or may not underlie all systems of complexity, purposefulness, and efficiency is not then antithetical to ID, nor is it a better alternative, but just irrelevant. God of the Gaps, meet your counterpart.