My latest paper, “Measuring Active Information in Biological Systems” was released today at BIO-Complexity. The paper itself is somewhat math-heavy, so I thought I would give UD readers a short overview of the basic ideas.
This paper is focused around the question of “random mutations” vs. “directed mutations”. Most people aren’t aware of this, but, more and more, biologists are finding mutations which are decidedly not random, but directed by a cell’s internal machinery. For those interested in more background information, see this video.
However, skeptics often simply dismiss the arguments for directed mutation. In Larry Moran’s case (and I find this response to be typical), he agreed with the basic facts, but refused to concede that it was directed. Despite the fact that the mutation spectrum aligned directly with the near-term needs of the organism, Moran couldn’t allow himself to say that the mutation was directed.
To the rescue comes Robert Marks and William Dembski, with Active Information. Active Information has been used to analyze non-biological “evolutionary” systems for the existence of information repositories guiding their evolution. I decided to apply that same technique to biology.
The core of the technique is this. The No Free Lunch theorem states that, loosely, that there is no general search mechanism that is optimal for all possible search spaces. More specifically for our purposes, it says that a “random search” is actually equivalent to the time of the expected outcome of any particular search process, as long as the search process is not *designed* to match the search space.
Therefore, whether or not an organism’s mutations are random, the expected speed of success of the organism’s mutation system should be equivalent to a random search, unless the search system is specifically designed to match the selective pressures it will face. Therefore, whether or not mutations are random, the effects of truly random mutations will give us an expected value for the success of any given non-designed search.
We can experimentally model random mutations in a number of ways. There is a bit of a problem, though, in that it is near-impossible to turn off an organism’s internal mutation system without causing other problems. Therefore, the paper presents a way, mathematically, to separate out the effects of the random mutations vs. the internally-generated mutations.
So, once we have determined the efficacy of random mutations, this gives us an expected value for the efficacy of the organism’s internally-generated mutations, if the mutational system is not designed. If the mutational system is significantly more directed towards beneficial outcomes than the expectation, then we have justification to believe that there is some sort of orienting mechanism at play which is causing mutations to be aligned with the needs of the organism (i.e., there is design in the mutational mechanisms).
Note that the product of such a study is not purely for speculative purposes. There are real, practical reasons to want to know this. First of all, it takes a lot of resources (time and material) to analyze mutational mechanisms in organisms. This represents a large risk of resources if we don’t know that there is a mechanism to find. Using Active Information, we can measure how much information the cell is contributing to its evolution, and, if it is significant, this justifies the expenditure of resources to determine the mechanism.
Additionally, we can start to treat evolutionary potential as a phenotype. That is, different organisms may have different evolutionary capabilities. Knowing what these capabilities are require the ability to measure them, which is what Active Information provides. Additionally, once they are known, these can be used for bio-engineering when evolutionary potential is a necessary component. For instance, for cleaning up waste, it would be important to know which organisms are more likely to evolve the ability to eat that particular kind of waste.
Anyway, I hope you all take the time to read the paper, and I am curious as to your comments!