The paradox of almost definite knowledge in the face of maximum uncertainty — the basis of ID
|December 18, 2013||Posted by scordova under Complex Specified Information, Intelligent Design, Mathematics, Physics|
When facing maximum uncertainty, it seems paradoxical that one can have great assurance about certain things. This has enormous relevance to ID because Darwinists will argue, “how can you be so certain of something when it is apparent there is great uncertainty in the system.” I will respond by saying, “when we have maximum uncertainty about what specific configuration 500 fair coins is in (by randomizing the coins in some vigorous fashion), we simultaneously have almost near certainty about which configurations it cannot be in — such as all-coins heads or a pre-specified sequence….”
When a process like a biotic soup maximizes uncertainty about possible polymer sequences that can evolve, it gives us near certainty life will not evolve by chance. When a process like random mutation and real selection (as opposed to DFFM) maximizes uncertainty for the direction of evolution, we know then that complex functions will not evolve via RM + RS (where RS stats for real selection in the wild, not Darwin’s Falsified Fantasy Mechanism (DFFM)).
If I apply a stochastic process that maximizes the uncertainty in a system (aka chance process), depending on the situation, we can often land high certainty about what configuration the system cannot be in, even in principle. Thus at least in principle, given a distribution, we can reject chance as hypothesis for a particular configuration, and thus we can in principle identify design.
Darwinists will complain, we know so little about how the system will evolve via chance, especially since stochastic mechanisms are in play. An ID proponent should then respond by saying, “Great! And even better, suppose we have chance maximize the uncertainty of a system’s configuration even more as it evolves over time. In that scenario, we can be quite sure chance won’t make a living organism nor complex integrated functions almost as surely as when we randomize a large set of fair coins laid out on table, they will not be 100% heads but instead approach the expectation value of 50% heads.”
This paradox is related to the Law of Large Numbers, a law which I regard as The Fundamental Law of Intelligent Design. Some have expressed concern the Law of Large Numbers can’t be applied to specific sequences. It can be, you just have to be a little creative. For examples, see: Coordinated Complexity, the key to refuting single target and postdiction objections.
1. I’ve tried to define “chance” as a stochastic process that maximizes the uncertainty in a system relative to the degrees of freedom of the relevant symbols. Sorry for being so anally meticulous about what “chance” means, but given how there were 111 some comments in Statistics Question for Nick Matzke going off on all sorts of tangents about the meaning of chance, I provide a tentative definition to immunize this discussion from such clutter.
2. A designed system is defined as a system not the result of law and chance. Whether in the ultimate sense such a system is created by a conscious intelligence is a separate question. But the reason defining design in this way is important is that it takes away the complaints like “the structure of such systems as being special is merely a figment of our postdictive imagination like seeing faces in clouds.” As far as not defining design with respect to intelligence see: It is useful to separate design from theories of intelligence and intelligent agency.
3. We have an illustration of this principle in thermodynamics. As a system approaches thermal equilibrium and uniform temperature, the uncertainty of the specific energy configuration is maximized, but in the process of maximizing uncertainty about the specific energy configuration (and uncertainty is also entropy, S = k log w) we have high certainty about the uniformity of temperature. All I’m doing is importing the illustrations of thermodynamics into the realm of ID — as an evolutionary process maximizes the uncertainty of a particular configuration it also precludes the evolution of highly specific outcomes as a matter of principle to a high level of certainty.
4. This is not an argument from ignorance against evolutionism, it is Proof by Contradiction.
5. There is an distinction between uncertainty because we were unable to observe data, and uncertainty because a process (like randomizing a set of fair coins) induces uncertainty. This essay deals with the latter sense of the notion of uncertainty.