For a free copy of Stephen Meyer’s Signature in the Cell (Harper One, 2009), help me understand the following:
Accidental origin of life is the basic thesis of origin of life researchers. Life all just somehow sort of happened one day, billions of years ago, under the right conditions – which we may be able to recreate. But there is a constant, ongoing dispute about just what those conditions were.
Here is the problem I have always had with accidental origin of life: It amounts to spontaneous generation. However, banishing the doctrine of spontaneous generation played a key role in modern medicine’s success. If we assume that life forms (for medical purposes, we focus on pathogens) cannot start spontaneously, then they must have been introduced. Hence, we can develop procedures for a sterile operating room or lab.
If life can be spontaneously generated, why isn’t it happening now? Conditions for life today are probably as good as they have ever been, and maybe better. For over 500 million years they have obviously been good for complex life forms, and for billions of years they have been good for simple ones.
If you wish to contribute to this question, you may advisedly wish to read this recent article in the math and engineering literature by Dembski and Marks:
Abstract—Conservation of information theorems indicate that any search algorithm performs, on average, as well as random search without replacement unless it takes advantage of
problem-specific information about the search target or the search-space structure. Combinatorics shows that even a moderately sized search requires problem-specific information to be successful. Computers, despite their speed in performing queries, are completely inadequate for resolving even moderately sized search problems without accurate information to guide them. We propose three measures to characterize the information required for successful search: 1) endogenous information, which measures the difficulty of finding a target using random search; 2) exogenous information, which measures the difficulty that remains in finding a target once a search takes advantage of problemspecific information; and 3) active information, which, as the difference between endogenous and exogenous information, measures the contribution of problem-specific information for successfully finding a target. This paper develops a methodology based on these information measures to gauge the effectiveness with which problem-specific information facilitates successful search. It then applies this methodology to various search tools widely used in evolutionary search.Index Terms—Active information, asymptotic equipartition property, Brillouin active information, conservation of information (COI), endogenous information, evolutionary search, genetic algorithms, Kullback–Leibler distance, no free lunch theorem (NFLT), partitioned search.