On Uncommon Descent, poster gpuccio has been discussing “functional information”. Most of gpuccio’s argument is a conventional “islands of function” argument. Not being very knowledgeable about biochemistry, I’ll happily leave that argument to others.
But I have been intrigued by gpuccio’s use of Functional Information, in particular gpuccio’s assertion that if we observe 500 bits of it, that this is a reliable indicator of Design, as here, about at the 11th sentence of point (a):
… the idea is that if we observe any object that exhibits complex functional information (for example, more than 500 bits of functional information ) for an explicitly defined function (whatever it is) we can safely infer design.
I wonder how this general method works. As far as I can see, it doesn’t work. There would be seem to be three possible ways of arguing for it, and in the end; two don’t work and one is just plain silly. Which of these is the basis for gpuccio’s statement? Let’s investigate …
A quick summary
Let me list the three ways, briefly.
(1) The first is the argument using William Dembski’s (2002) Law of Conservation of Complex Specified Information. I have argued (2007) that this is formulated in such a way as to compare apples to oranges, and thus is not able to reject normal evolutionary processes as explanations for the “complex” functional information. In any case, I see little sign that gpuccio is using the LCCSI.
(2) The second is the argument that the functional information indicates that only an extremely small fraction of genotypes have the desired function, and the rest are all alike in totally lacking any of this function. This would prevent natural selection from following any path of increasing fitness to the function, and the rareness of the genotypes that have nonzero function would prevent mutational processes from finding them. This is, as far as I can tell, gpuccio’s islands-of-function argument. If such cases can be found, then explaining them by natural evolutionary processes would indeed be difficult. That is gpuccio’s main argument, and I leave it to others to argue with its application in the cases where gpuccio uses it. I am concerned here, not with the islands-of-function argument itself, but with whether the design inference from 500 bits of functional information is generally valid.
We are asking here whether, in general, observation of more than 500 bits of functional information is “a reliable indicator of design”. And gpuccio’s definition of functional information is not confined to cases of islands of function, but also includes cases where there would be a path to along which function increases. In such cases, seeing 500 bits of functional information, we cannot conclude from this that it is extremely unlikely to have arisen by normal evolutionary processes. So the general rule that gpuccio gives fails, as it is not reliable.
(3) The third possibility is an additional condition that is added to the design inference. It simply declares that unless the set of genotypes is effectively unreachable by normal evolutionary processes, we don’t call the pattern “complex functional information”. It does not simply define “complex functional information” as a case where we can define a level of function that makes probability of the set less than 
. That additional condition allows us to safely conclude that normal evolutionary forces can be dismissed — by definition. But it leaves the reader to do the heavy lifting, as the reader has to determine that the set of genotypes has an extremely low probability of being reached. And once they have done that, they will find that the additional step of concluding that the genotypes have “complex functional information” adds nothing to our knowledge. CFI becomes a useless add-on that sounds deep and mysterious but actually tells you nothing except what you already know. So CFI becomes useless. And there seems to be some indication that gpuccio does use this additional condition.
Let us go over these three possibilities in some detail. First, what is the connection of gpuccio’s “functional information” to Jack Szostak’s quantity of the same name?
Is gpuccio’s Functional Information the same as Szostak’s Functional Information?
gpuccio acknowledges that gpuccio’s definition of Functional Information is closely connected to Jack Szostak’s definition of it. gpuccio notes here:
Please, not[e] the definition of functional information as:
“the fraction of all possible configurations of the system that possess a degree of function >=
Ex.”which is identical to my definition, in particular my definition of functional information as the
upper tail of the observed function, that was so much criticized by DNA_Jock.
(I have corrected gpuccio’s typo of “not” to “note”, JF)
We shall see later that there may be some ways in which gpuccio’s definition
is modified from Szostak’s. Jack Szostak and his co-authors never attempted any use of his definition to infer Design. Nor did Leslie Orgel, whose Specified Information (in his 1973 book The Origins of Life) preceded Szostak’s. So the part about design inference must come from somewhere else.
gpuccio seems to be making one of three possible arguments;
Possibility #1 That there is some mathematical theorem that proves that ordinary evolutionary processes cannot result in an adaptation that has 500 bits of Functional Information.
Use of such a theorem was attempted by William Dembski, his Law of Conservation of Complex Specified Information, explained in Dembski’s book No Free Lunch: Why Specified Complexity Cannot Be Purchased without Intelligence (2001). But Dembski’s LCCSI theorem did not do what Dembski needed it to do. I have explained why in my own article on Dembski’s arguments (here). Dembski’s LCCSI changed the specification before and after evolutionary processes, and so he was comparing apples to oranges.
In any case, as far as I can see gpuccio has not attempted to derive gpuccio’s argument from Dembski’s, and gpuccio has not directly invoked the LCCSI, or provided a theorem to replace it. gpuccio said in a response to a comment of mine at TSZ,
Look, I will not enter the specifics of your criticism to Dembski. I agre with Dembski in most things, but not in all, and my arguments are however more focused on empirical science and in particular biology.
While thus disclaiming that the argument is Dembski’s, on the other hand gpuccio does associate the argument with Dembski here by saying that
Of course, Dembski, Abel, Durston and many others are the absolute references for any discussion about functional information. I think and hope that my ideas are absolutely derived from theirs. My only purpose is to detail some aspects of the problem.
and by saying elsewhere that
No generation of more than 500 bits has ever been observed to arise in a non design system (as you know, this is the fundamental idea in ID).
That figure being Dembski’s, this leaves it unclear whether gpuccio is or is not basing the argument on Dembski’s. But gpuccio does not directly invoke the LCCSI, or try to come up with some mathematical theorem that replaces it.
So possibility #1 can be safely ruled out.
Possibility #2. That the target region in the computation of Functional Information consists of all of the sequences that have nonzero function, while all other sequences have zero function. As there is no function elsewhere, natural selection for this function then cannot favor sequences closer and closer to the target region.
Such cases are possible, and usually gpuccio is talking about cases like this. But gpuccio does not require them in order to have Functional Information. gpuccio does not rule out that the region could be defined by a high level of function, with lower levels of function in sequences outside of the region, so that there could be paths allowing evolution to reach the target region of sequences.
An example in which gpuccio recognizes that lower levels of function can exist outside the target region is found here, where gpuccio is discussing natural and artificial selection:
Then you can ask: why have I spent a lot of time discussing how NS (and AS) can in some cases add some functional information to a sequence (see my posts #284, #285 and #287)
There is a very good reason for that, IMO.
I am arguing that:
1) It is possible for NS to add some functional information to a sequence, in a few very specific cases, but:
2) Those cases are extremely rare exceptions, with very specific features, and:
3) If we understand well what are the feature that allow, in those exceptional cases, those limited “successes” of NS, we can easily demonstrate that:
4) Because of those same features that allow the intervention of NS, those scenarios can never, never be steps to complex functional information.
Jack Szostak defined functional information by having us define a cutoff level of function to define a set of sequences that had function greater than that, without any condition that the other sequences had zero function. Neither did Durston. And as we’ve seen gpuccio associates his argument with theirs.
So this second possibility could not be the source of gpuccio’s general assertion about 500 bits of functional information being a reliable indicator of design, however much gpuccio concentrates on such cases.
Possibility #3. That there is an additional condition in gpuccio’s Functional Information, one that does not allow us to declare it to be present if there is a way for evolutionary processes to achieve that high a level of function. In short, if we see 500 bits of Szostak’s functional information, and if it can be put into the genome by natural evolutionary processes such as natural selection then for that reason we declare that it is not really Functional Information. If gpuccio is doing this, then gpuccio’s Functional Information is really a very different animal than Szostak’s functional information.
Is gpuccio doing that? gpuccio does associate his argument with William Dembski’s, at least in some of his statements. And William Dembski has defined his Complex Specified Information in this way, adding the condition that it is not really CSI unless it is sufficiently improbable that it be achieved by natural evolutionary forces (see my discussion of this here in the section on “Dembski’s revised CSI argument” that refer to Dembski’s statements here). And Dembski’s added condition renders use of his CSI a useless afterthought to the design inference.
gpuccio does seem to be making a similar condition. Dembski’s added condition comes in via the calculation of the “probability” of each genotype. In Szostak’s definition, the probabilities of sequences are simply their frequencies among all possible sequences, with each being counted equally. In Dembski’s CSI calculation, we are instead supposed to compute the probability of the sequence given all evolutionary processes, including natural selection.
gpuccio has a similar condition in the requirements for concluding that complex
functional information is present: We can see it at step (6) here:
If our conclusion is yes, we must still do one thing. We observe carefully the object and what we know of the system, and we ask if there is any known and credible algorithmic explanation of the sequence in that system. Usually, that is easily done by excluding regularity, which is easily done for functional specification. However, as in the particular case of functional proteins a special algorithm has been proposed, neo darwininism, which is intended to explain non regular functional sequences by a mix of chance and regularity, for this special case we must show that such an explanation is not credible, and that it is not supported by facts. That is a part which I have not yet discussed in detail here. The necessity part of the algorithm (NS) is not analyzed by dFSCI alone, but by other approaches and considerations. dFSCI is essential to evaluate the random part of the algorithm (RV). However, the short conclusion is that neo darwinism is not a known and credible algorithm which can explain the origin of even one protein superfamily. It is neither known nor credible. And I am not aware of any other algorithm ever proposed to explain (without design) the origin of functional, non regular sequences.
In other words, you, the user of the concept, are on your own. You have to rule out that natural selection (and other evolutionary processes) could reach the target sequences. And once you have ruled it out, you have no real need for the declaration that complex functional information is present.
I have gone on long enough. I conclude that the rule that observation of 500 bits of functional information is present allows us to conclude in favor of Design (or at any rate, to rule out normal evolutionary processes as the source of the adaptation) is simply nonexistent. Or if it does exist, it is as a useless add-on to an argument that draws that conclusion for some other reason, leaving the really hard work to the user.
Let’s end by asking gpuccio some questions:
1. Is your “functional information” the same as Szostak’s?
2. Or does it add the requirement that there be no function in sequences that
are outside of the target set?
3. Does it also require us to compute the probability that the sequence arises as a result of normal evolutionary processes?
How does purifying selection preserve the function “producing ATP for cellular energy” other than through its effect on survival and reproduction?
No, it’s fitness. And you are (implicitly) assuming there is a one-to-one relationship between the molecular function and fitness. Now, try again. Indulge this indoctrinated biologist and reproduce the “dancing around an optimum” argument in your own words.
Corneel,
We are seeing a separation. We are also seeing greater variation among bacteria as the closest distance 73% is less then the 90% among vertebrates. At this point our data is limited as we have not purged through 40000 vertebrates and 10000 bacteria species but bacteria appear to tolerate more variation then vertebrates so far.
It is also possible that there are different functional requirements among different bacteria.
A point of agreement 🙂 Different functional requirements is just an untested hypothesis at this point.
Corneel,
It is not preserving the function, it is preserving the sequence. If the sequence varies beyond a tolerable point there are several possibilities. It could prevent an egg from being fertilized, it could stop the reproductive process or it could purge the variation from the process through poor reproduction of the animal with the additional mutation. Lots of potential filters but with 400 million years of preservation these filters are obviously strong.
Corneel,
My favorite indoctrinated biologist 🙂 as rumor has it, he is an Ale drinker.
Let me think about this as the beta chain is just a piece of an overall protein function.
The bigger issue is how do you make the case that all the islands of function have a larger ratio to overall sequence space then the ratio of a grain of sand to the quantity of water in the Atlantic ocean.
I don’t have to.
Alan Fox,
or I don’t want to
or I can’t 🙂
It’s gpuccio’s claim. Let him support it. Or you!
Buehler?
Anyone?
Alan Fox,
This is Jocks claim which is not relevant if the isles of function are not larger then the grain of sand in the ocean.
He claimed isles of function counters gpuccio’s claim yet he has not shown the relevance.
Gpuccio has made an outstanding argument why the islands are too tiny to be relevant yet there is no counter so far from the evolutionist camp.
You are going to have to show your working for your “grain of sand” claim.
The only people I know of who have put a number on the proportion of functional sequences are Keefe and Szostak. N.B. : even you and gpuccio have agreed that gpuccio’s preserved sequence calculations do NOT measure the size of ‘islands’.
So, using Keefe’s data, I get a “grain of sand” that is 3 million cubic metres in size.
That’s a really big ‘grain’! 🙂
DNA_Jock,
How about Hayashi needing a library of 10^70 sequences to find the wild type or Axe 10^77 to bind another protein sub unit and break down a molecule.
Although the Szostak argument shows a bowling ball in the ocean these other papers show a sub atomic particle.
Do you think that Szostak’s example was really showing a functional protein?
Well, though I think analogies get more misleading the further you take them, let’s try this one. Dr Liddle is fond of using Chesil Beach as an analogy for non-random sorting, so let’s start there. Chesil Beach is a long pebble beach on the South of England’s Dorset Jurassic Coast.
Imagine you are an organism that needs pebbles instead of proteins (analogies aren’t perfect) and you need a particular one. How long will it take you to search the one you need. Aeons, if, as you claim, only just the right pebble will do.
But what if, as I claim, the beach is full of pebbles that are good enough? And you can then function adequately while strolling around looking for samples closer to your requirements. Indeed, you don’t have to target your search, just pick up and check the odd ones you come across.
ETA if
colewd,
Yes. Affinity for ATP is a very useful function.
I am not responsible for your comprehension failures, Bill. Hayashi actually reckoned that “most random or primordial sequences” had minimally selectable function: that’s MORE ISLAND THAN OCEAN, kiddo. Not sure what you are claiming re Axe, but he hasn’t written a paper yet that couldn’t be eviscerated by a moderately competent biology undergrad, and I know for a fact that he hasn’t created a library of 10^77 anything.
DNA_Jock,
Sure. But the search to what was being observed was a library of 10^70 sequences. The other functions obviously did not lead to what was observed. So if the sequence was created by a random search I would not expect the wild type kiddo 🙂 Your spin is not my poor comprehension.
So you are claiming that the AXE paper is not valid. I think you need to reproduce his experiment unless you think you need to stick to your ad populum fallacy. Your other option is to site a paper that tries to invalidate it. I don’t think the current one does the job.
https://pandasthumb.org/archives/2007/01/92-second-st-fa.html
Alan Fox,
A good analogy if living organisms can exist without optimized sequences and they have proteins of 7 AA’s or less.
Oh Bill, your comprehension is exactly as I reckoned. You are claiming that Hayashi made a library of 10^70 sequences. They didn’t.
And the panda’s thumb article that you linked to destroys Axe’s paper, and (along the way) explains the difference between the forward and the reverse approaches.
The fact that you don’t think that it ‘does the job’ is your uninformed opinion. Until you are willing to support your opinion(s) with evidence and argument (and you have not even tried to date), your opinions are worthless.
A library of
sequences would be how big? Well, let’s suppose one sequence weighs as much as one hydrogen atom. That’s minimal figure, right?
Using Avogadro’s Number and the Wikipedia figure for the weight of the earth, I find that the library would weigh as much as
earths.
That’s a bit too large.
Organisms do have functional proteins (peptides is the arbitrarily preferred name for polymers of less than 50 aas) as small as dimers (dipeptides).
Sorry, the library was only
sequences, so actually only about 
earths, a much smaller figure. Therefore a lot easier for experimenters to create in the lab.
If you have the niche to yourself, you don’t need to be optimal. The first organisms had an empty niche. They could bumble along without a care.
Pow pow.
Alan Fox,
Not without processing oxygen and glucose 🙂
Elemental sulphur and iron can (and do today) act as electron donors. Energy obtained can drive endothermic reactions. In the simplest organisms, glucose is manufactured.
Joe Felsenstein,
I can’t explore the entire sequence space but I know most of it is selectable function 🙂
If Szostak estimated 10^11 for binding ATP what would be the probability of binding ATP and an additional molecule?
Alan Fox,
How simple are the simplest organisms?
I’ve remarked previously that designing functional proteins from scratch is an impossible task but science is a work in progress. Bill might be interested in this recent review paper (PDF) if only for ammunition. 😉
We’re doing reductio ad absurdam are we, Bill? I admit there are no sure answers. Have a look at Nick Lane’s The Vital Question for some ideas.
DNA_Jock,
Not my claim Jock.
Destroys Axe’s paper. Texas sharp shooter fallacy. I love these. Superb political arguments.
Why don’t you explain why it destroys Axe’s paper. Did you look at the range of scientific papers in Hunts analysis. 10^10 to 10^60 for probabilities among the scientific papers. The range is from a very small island in the ocean to an atom.
Sort of DESTROYS your argument against gpuccio 🙂
Since were talking about individual proteins and not multi protein complexes where more then one binding event occurs where do you think the beta chain of ATP would fall?
Alan Fox,
So you’re admitting a naturalism of the gaps argument?
How does that work? I’m saying, so far, there is no satisfactory natural explanation for the origin of life that I know of. There are many ideas and suggestions.
That we don’t have a scientific explanation yet means just that. We don’t know.
I suspect you may want to insert a god into that gap.
He doesn’t need to. Arthur Hunt has done that quite adequately. Why reinvent the wheel?
Alan Fox,
Thanks for the paper. Just skimmed it but love this.
As the famous TSZ quote says: think it possible you may be mistaken 🙂
*chuckles*
At least you looked!
Alan Fox,
If all you guys want to do is argue by assertion thats fine.
So Art actually supports Axe’s results being in the range of the scientific literature.
BTW, Bill,
What’s the problem with the bit you quote? Seems reasonable to me.
Oh, the irony!
My google skills are found wanting. Anyone got a link to a free version of Axe’s paper?
Alan Fox,
It’s a classic begging the question fallacy.
Isn’t it remarkable evolution did this.
Is it possible that this problem shows that evolution may not have given the probabilistic resource limitations are order of magnitude smaller then the sequence space?
Anything done by something as huge as nature would look remarkable to beings as small and ephemeral as ourselves. But, once some basic processes are understood, I’m not too surprised.
Probabilistic resources? Nature doesn’t work with that. It works with energy flows, and those are much more than enough. Orders of magnitude more. But, truly orders of magnitude more.
You said before that “islands of function” had to be proven. If you talk about “sequence space,” you’re assuming that there’s such things as islands of function. So, which is it? Are there islands of funtion or not?
Entropy,
The question should be, is the island of function limited across certain protein types or ubiquitous across all proteins. The Hayashi paper identifies it for a sequence segment of a specific protein type. Does that same conceptual landscape exist for a protein that makes up part of a protein complex like the beta chain of ATP synthase? I don’t know.
The conceptual framework is a shortcut to talk about a more complicated thing. Namely, that changes in amino-acids have from no, to little, to large consequences. The conceptual framework can be used at different levels, from one including the whole thing (all possible sequences), as you did in your post, to single families, as in the Hayashi paper. I see no reason to imagine that something you’re applying to every protein (the whole of all possible sequences), would not apply to one sequence, but apply to another. Sounds contradictory. At most you could propose that there might be “functions” that only one single sequence can “perform,” and call that quite a narrow island of function. I see no reason why this could be the case though. From all I have read and understood, there’s no reason to think that could be the case for any protein.
Under a very particular condition, and under a very limited experimental framework.
Conceptual landscapes don’t actually exist Bill. They’re conceptual. We use them as shortcuts to talk about more complicated things. Since there’s tons of sequences in the beta chain ATP synthase family, the conceptual framework is useful to talk about it as well.
Entropy,
This doesn’t made sense to me. Not until you have established more then one island exists. Hayashi established islands with very different sequences then the wild type. Again, for a sequence that was only 30% of the overall protein.
Oh! I see. I thought you were talking about islands in general, but what you seem to be saying is that there’s no more than one “island of function” for anything and everything? For most sequences? If either of those, do you know how many different protein families produce ATP? There’s loads of them. But really loads of them. For example, a frequent question in biochemistry tests is to point, in some biochemical pathway, to all the points where ATP is produced.
Entropy,
This is not what I am saying. Lets table this for now.
You seem to be using a different definition of “separation” and, more worrisome, of “multicellular”. Are you aware that multicellular organisms exist that are not vertebrates? If so, could you try to temper the anthropocentrism a wee bit, please?
That’s a nice euphemism. Rumraket phrased that a bit differently 🙂
It is not preserving the sequence, it is preserving the function. If you replace the sequence by a different one that is capable of fulfilling exactly the same function, then purifying selection does not occur. Selection operates on the phenotype.
All of which negatively impact fitness. Thank you for acknowledging my point.
Any type of beer, really. I live pretty close to Belgium, you know.
PS: don’t forget to give us your version of the “dancing around the optimum” argument. I am curious why you keep using the conservation argument while being reluctant to admit that the function in your FI must have some relation to fitness.
Good Grief!!!
How did I not see this before???
Axe, EN&W and protein sequence space (again, again, again)
Excellent article by Rumraket eviscerating Axe’s paper
And look who I see posting in the comments!
Why it’s Bill!
I am pretty sure there is some safety regulation prohibiting that.
Alan Fox,
link is broken, Alan.
Corneel,
Oops! Thanks – fixed.
Alan Fox,
I think you clearly beat Jock here for the most creative and descriptive assertion 🙂