Reasons to Believe, an old earth creationist group headed by astronomer Hugh Ross, is trying hard to sell their new book, Creation As Science: A Testable Approach to End the Evolution/Creation Wars. They issued a press release yesterday about the book, which included some false claims, some good analysis of why ID isn’t taken seriously by scientists, and little detail on this new model they’ve been talking about for years. First, the false claims:
“The 1981 Supreme Court ruling guarantees the place of any scientifically viable model in public education regardless of its theological implications,” contends Ross.
There is no 1981 Supreme Court ruling on this question. The 1981 case was McLean v Arkansas, which was a district court case. He obviously intends to refer to Edwards v Aguillard, a 1987 Supreme Court case. What he is apparently referring to in the ruling is the following statement, which has been taken by creationists of all stripes to mean that if they can just find a way to claim their ideas are scientific, they can be taught:
We do not imply that a legislature could never require that scientific critiques of prevailing scientific theories be taught.
But of course, the young earth creationists say the same thing that Ross says, that their ideas really are scientific and therefore can’t be prohibited. The ID movement says the same thing. And now Ross says he’s got a truly testable model that can pass the test. He doesn’t lay out that model in the press release, but judging by many of the claims RTB has made in the past, they’ve got a rather odd definition of “testable model”.
A good example is this article, where they claim that the “creation model” passed a “big test”. But in fact, the prediction is inconsequential and irrelevant, and the inference drawn from it based upon a caricature of the mainstream scientific view. Their vaunted “prediction” is that life will appear early in the earth’s history:
Reasons To Believe’s creation model makes several predictions that can be used to evaluate its validity. For example, the model predicts that life should appear early in Earth’s history and that the first life forms should be inherently complex.
Evolutionary origin of life models, on the other hand, require a long “percolation” time, perhaps up to 1 billion years, before life can emerge from a primordial soup. These naturalistic scenarios also predict that the first life forms should be relatively simple.
But this is simply nonsense. We have known for a very long time that microbial life first appeared on earth some 3.8 billion years ago, or around 750 million years after the formation of the earth. This “prediction” is of old data accepted by everyone except – ironically – many creationists. And of course, abiogenesis theories predict what the first self-replicating life forms would have been like and how they might have came about, but not that they will be found, so it makes no sense to claim that since the first life forms on earth that we find evidence of were bacteria, those must have been the first life forms actually here.
It is highly implausible that we will ever find fossilized remains of pre-cellular organisms; we are extraordinarily fortunate to have found even the trace evidence of early microbial life, and even then all of the evidence we have of early non-metazoan life consists of stromatolites (colonies of bacteria) that constituted the whole of the earth’s biosphere for some 2 billion years. So what RTB calls a “big test” of a major prediction is in fact nothing more than a mundane retrodiction of what everyone already knew to be true long before they ever developed their “testable model”, combined with a straw man version of evolution to show some ostensible contrast between the two “models”.
But I do agree with this statement:
“The problem scientists have with the current Intelligent Design movement is that ID proponents offer no model by which to test their claims. Testability and predictive power are crucial to credibility,” says Ross. “It is right for the scientific community to ask, ‘Where is your model?’”
But of course, we require a real model that makes real predictions, not the sort of pointless and empty predictions attempted above.