Phinehas and Kairosfocus share second prize for my CSI challenge: yes, it is indeed “Ash on Ice” – it’s a Google Earth image of Skeiðarárjökull Glacier.

But of course the challenge was not to identify the picture, but to calculate its CSI. Vjtorley deserves, I think, first prize, not for calculating it, but for making so clear why we cannot calculate CSI for a pattern unless we can calculate “p(T|H)” for all possible “chance” (where “chance” means “non-design”) hypotheses.

In other words, unless we know, in advance, how likely we are to observe the candidate pattern, given non-chance, we cannot infer Design using CSI. Which is, by the Rules of Right Reason, the same as saying that in order to infer Design using CSI, we must first calculate how likely our candidate pattern is under all possible non-Design hypotheses.

As Dr Torley rightly says:

Professor Felsenstein is quite correct in claiming that “CSI is not … something you could assess independently of knowing the processes that produced the pattern.”

And also, of course, in observing that Dembski acknowledges this in his paper, , Specification: The Pattern That Signifies Intelligence, as many of us have pointed out. Which is why we keep saying that it can’t be calculated – you have to be able to quantify p(T|H), where H is the actual non-design hypothesis, not some random-independent-draw hypothesis.

I’d say (and interestingly Joe G seems to agree) that this makes CSI useless. I don’t think it means that we can’t detect design (I think there are loads of ways of detecting design) but it’s worth considering why vjtorley things CSI still has some use. He says:

But how can we rule out

all possible“chance hypotheses” for generating a pattern, when we haven’t had time to test them all? The answer is that if some “chance hypotheses” aremuch more probablethan others, so that a few tower above all the rest, and the probabilities of the remaining chance hypotheses tend towards zero, then we may be able to estimate the probability of theentire ensembleof chance processes generating that pattern. And ifthisprobability is so low that we would not expect to see the event realized evenoncein the entire history of the observable universe, then we could legitimately infer that the pattern was the product of Intelligent Design.

I think that’s entirely legitimate, but I don’t think it merits the description CSI if we take CSI to be the item in Dembski’s formula. For example, if something isn’t obviously the result of some other iterative process like crystallisation or wave action (which my glacier is), or self-replication, then it might be perfectly reasonable to infer design as at least a possible, even likely, candidate (black monoliths on the moon would come into this category). And in such circumstances, the next obvious question would be: well, what can we now infer about the designer? In the case of a black monolith, we could probably infer quite a lot, and we could start testing hypotheses about when the designers might have fabricated the object, and what tools they might have used, and what purpose it might have been intended to serve, etcetera. Perhaps one day the Voyager capsule may be subjected to just those investigations by future alien scientists.

But ID proponents rule out such speculation. The claim Dembski makes is that ID is the *the study of patterns in nature* *that are best explained as the products of intelligence, *not the nature of the putative intelligent agent itself (which he, refreshingly, happily hands over to theology). And if CSI requires that we know the probability that the pattern can be explained by non-design before we can conclude that it is best explained by intelligence, then the entire question is begged if the pattern in question is something that could be produced by an iterative process, such as a glacier, or a crystal, *or a self-replicating molecule*. Such things *could* be designed, of course, and are, and, indeed, design itself is, I would argue, an iterative process. But in order to infer that design is the *best* explanation using CSI, we’d have to calculate the probability of seeing such a pattern under all possible non-design iterative hypotheses.

And if any ID proponent can suggest how we might make such a calculation, I would like to hear it. Until then I shall continue to consider that we have no method for calculating CSI 🙂

Yes. If you have a good theory, you should be able to derive a hypothesis that makes an experimental prediction: if X is true, when we do Y we should see Z. If we do see Z, we have support for X being true.

OK.

Lizzie,And you can test that every time that we did or will do Y we are going to see Z.

Well, science is always probabilistic. At the very minimum, there is measurement error. That’s why we do statistics on our result, and give our results with an accompanying p value or confidence interval. Essentially a p value (in traditional frequentist hypothesis testing) means: if our hypothesis is false, we will see this result only p proportion of the time.

You will see p proportion of time in the condition of your testing. Extrapolation in past time or future time are not testable.

Then you moved from an only immagination realm to a probabilistic limited realm.

In what sense not? Do you think that chemical properties have changed over the past few million or billion years? That itself is a testable hypothesis.

All science is probabilistic and all conclusions are provisional. The beef I have with ID is not that it is wrong (it may well be right) but that it is an unsound inference given our data.

How?

LizzieAll science is probabilistic and all conclusions are provisional.The beef I have with ID is not that it is wrong (it may well be right) but that it is an unsound inference given our data.

Also ToE accomodates the data to a narrative based on the assumption that life is a “natural” phenomenon.