I took another peek into the nonsense the Discovery Institute is currently peddling. It’s depressingly shallow, a lot of motivated reasoning and twisted use of the evidence. For instance, Kirk Durston has an article titled Could Atheism Survive the Discovery of Extraterrestrial Life?, which, as an atheist who would be thrilled to pieces if we discovered alien life of a completely independent origin, seems peculiar.

Here’s his argument, though. The origin of life on Earth is a hard problem (agreed). Current models, as he understands them, suggest that it was an event of exceedingly low probability, so low that it was extremely lucky that it happened here, but it would be extremely unlikely that it would also happen in multiple places in our universe. Therefore, logic dictates the existence of a supernatural creator. It’s simply, I don’t understand this, therefore god. It also flops inelegantly into a common creationist theme that there are only two possible models, and if I find a weakness in yours, my model is automatically correct, even if my model has even more flaws, which I conveniently ignore.

The centerpiece of these kinds of articles is usually some juicy admission from real scientists that we don’t understand every detail of the origin of life, therefore, ha ha, god exists! It’s annoying, because this is how science works, by identifying problems and working to solve them, and creationists love to pervert that methodology into some kind of admission that science is failing and wrong. They never seem to notice, either, that the only way they can steal some credibility is by quoting the scientific literature, or rather, misquoting it.

Durston provides us with a prime example of this tactic.

A 2011 article in Scientific American, “Pssst! Don’t tell the creationists, but scientists don’t have a clue how life began,” summarized our lack of progress in the lab. Of course, there are plenty of scenarios, but creative story-telling should not be confused with doing science, or making scientific discoveries. With regard to “thousands of papers” published each year in the field of evolution, as Austin Hughes wrote, “This vast outpouring of pseudo-Darwinian hype has been genuinely harmful to the credibility of evolutionary biology as a science.”

Evolutionary biologist Eugene Koonin, meanwhile, calculates the probability of a simple replication-translation system, just one key component, to be less than 1 chance in 10^1,018 making it unlikely that life will ever spontaneously self-assemble anywhere in the universe. His proposed solution is a near-infinite number of universes, something we might call a “multiverse of the gaps.”

So three sources: Horgan, Hughes, and Koonin. Is he reporting their work accurately?

He comes closest with his interpretation of Horgan’s article. It is very pessimistic, and is describing the failings of the RNA world hypothesis.

But the “RNA-world” hypothesis remains problematic. RNA and its components are difficult to synthesize under the best of circumstances, in a laboratory, let alone under plausible prebiotic conditions. Once RNA is synthesized, it can make new copies of itself only with a great deal of chemical coaxing from the scientist. Overbye notes that “even if RNA did appear naturally, the odds that it would happen in the right sequence to drive Darwinian evolution seem small.”

This is true. Does anyone believe in a pure, straight RNA world anymore? Not that I know of. The evidence is clear that RNA played a bigger catalytic role in the distant past — we can find vestiges of that role in our cells even now — but the answer is going to be more complicated than just “RNA did it”. And of course, “RNA didn’t do it” doesn’t imply that God did it.

Unfortunately, Horgan’s alternative is panspermia, which even he doesn’t believe.

Of course, panspermia theories merely push the problem of life’s origin into outer space. If life didn’t begin here, how did it begin out there? Creationists are no doubt thrilled that origin-of-life research has reached such an impasse (see for example the screed “Darwinism Refuted,” which cites my 1991 article), but they shouldn’t be. Their explanations suffer from the same flaw: What created the divine Creator? And at least scientists are making an honest effort to solve life’s mystery instead of blaming it all on God.

I also think he is too pessimistic and doesn’t seem to be aware of the breadth of origin of life research. The recent ideas from Martin and Lane about chemistry and proton gradients have been a breath of fresh air, and reveals the flaw in creationist dismissals of our current understanding — we are constantly learning new things, and what seems like an unsolvable problem now may become a trivial obstacle with further discoveries. It’s one of the virtues of not constraining your search space to the pages of a single old book.

The Hughes article gets a prize for being the most egregiously distorted of the three. For one, it’s not about problems in origin of life studies at all — it’s about poor statistical analyses and over-reliance on adaptive hypotheses. Read the abstract; does this sound like a guy who is questioning evolution?

Sequences of DNA provide documentary evidence of the evolutionary past undreamed of by pioneers such as Darwin and Wallace, but their potential as sources of evolutionary information is still far from being realized. A major hindrance to progress has been confusion regarding the role of positive (Darwinian) selection, i.e., natural selection favoring adaptive mutations. In particular, problems have arisen from the widespread use of certain poorly conceived statistical methods to test for positive selection (1, 2). Thousands of papers are published every year claiming evidence of adaptive evolution on the basis of computational analyses alone, with no evidence whatsoever regarding the phenotypic effects of allegedly adaptive mutations. But it would be a mistake to dismiss Yokoyama et al.’s (3) study, in this issue of PNAS, of the evolution of visual pigments in vertebrates as more of the same. For, unlike all too many recent papers in the field, this study is solidly grounded in biology.

Hughes also does not propose god as an alternative. We’ve got a better option, one that’s actually supported by the evidence.

As well as natural selection, nonselective (or “non-Darwinian”) mechanisms may play a role in the origin of adaptive phenotypes. The most important non-Darwinian process is chance fluctuation in gene frequency or genetic drift, which can lead to the fixation of selectively neutral mutations (those with no effect on fitness) or sometimes even of slightly deleterious mutations. Kimura coined the term “Dykhuizen-Hartl effect” to describe an originally neutral mutation that later becomes adaptive in a changed environment, including a changed biochemical environment resulting from other amino acid replacements in the same protein.

You know how every time I criticize evolutionary psychology for failing to understand that there’s more to evolutionary biology than just selection, I get a swarm of indignant responses that I must be a creationist? This is the same thing. Hughes is properly pointing out that other forces can drive evolutionary change and criticizing the scientists who seem unaware of that, and for that, Durston thinks he’s a creationist ally…or at least, someone whose words can be twisted to pretend he’s an ally.

What about Koonin? This one is interesting, because Koonin is a brilliant thinker and theorist, and always seems willing to take on sacred cows. His book, The Logic of Chance: The Nature and Origin of Biological Evolution, actually does have a chapter on the mathematical probability of the origin of life, and he does use that 10^-1,018 number (but not for the origin of a single component: his point is the coevolution of the multiple components of the transcription and translation apparatus is a difficult problem). It is! In the book, Koonin does suggest that a Multiple Worlds hypothesis might offer an out, but I found that as unconvincing as panspermia or worse, the god did it hypothesis.

The heart of his argument, though, is the power of the Darwin-Eigen cycle. That is, in a replicating system, there is selection for better fidelity of replication, which allows increases in size and complexity by drift, which is then refined further by selection. The existence of this effect means you can get this constant escalation of complexity and information in cells by the interaction of 3 components, fitness, genome size, and replication fidelity. He’s actually making a powerful argument against another key component of creationist ideology, that you can’t get increases in information without a designer. It’s inherent in the system!

However, he also points out that before the Darwin-Eigen cycle can start chugging along, it needs to cross a threshold. You need some minimal genome size, which you could imagine coming together by chance, but you also need some minimal fidelity — if every generation is randomized, the cycle is not going to be able to get a grip — and that requires functionality that is not likely to arise by pure chance processes. Koonin has no problem as a scientist pointing out that you need a certain threshold of complexity to get the engine of selection and drift going, and recognizes that the emergence of a translation system to convert RNA sequences to protein is a crucial, and difficult breakthrough. That chapter in his book is explaining that this really is a hard problem.

But note that Koonin does not argue that the only alternative is a god — gods make no appearances in the book. Nor does he advocate giving up. Maybe there is a solution, he just hadn’t thought of one in 2011.

So, here’s a paper from 2007, “On the origin of the translation system and the genetic code in the RNA world by means of natural selection, exaptation, and subfunctionalization” which Durston does not cite, which proposes pathways by which the breakthrough could have been made.

The origin of the translation system is, arguably, the central and the hardest problem in the study of the origin of life, and one of the hardest in all evolutionary biology. The problem has a clear catch-22 aspect: high translation fidelity hardly can be achieved without a complex, highly evolved set of RNAs and proteins but an elaborate protein machinery could not evolve without an accurate translation system. The origin of the genetic code and whether it evolved on the basis of a stereochemical correspondence between amino acids and their cognate codons (or anticodons), through selectional optimization of the code vocabulary, as a “frozen accident” or via a combination of all these routes is another wide open problem despite extensive theoretical and experimental studies. Here we combine the results of comparative genomics of translation system components, data on interaction of amino acids with their cognate codons and anticodons, and data on catalytic activities of ribozymes to develop conceptual models for the origins of the translation system and the genetic code.

We describe a stepwise model for the origin of the translation system in the ancient RNA world such that each step confers a distinct advantage onto an ensemble of co-evolving genetic elements. Under this scenario, the primary cause for the emergence of translation was the ability of amino acids and peptides to stimulate reactions catalyzed by ribozymes. Thus, the translation system might have evolved as the result of selection for ribozymes capable of, initially, efficient amino acid binding, and subsequently, synthesis of increasingly versatile peptides. Several aspects of this scenario are amenable to experimental testing.

The authors are Yuri Wolf and Eugene Koonin.

So Durston is incorrect to assume that Koonin gave up with a feeble multiverse of the gaps hypothesis. That a scientist acknowledges the difficulty of an interesting and complex problem is not a prelude to surrendering and going to church; that’s the creationist solution.

It also produced a very interesting paper.

Great moments in labor history I was unaware of: did you know the Skylab astronauts went on strike?

Then it turns out that NASA is a bad boss.

More details here; the eventual outcome was that NASA never let any member of that mutinous crew fly into space again. (NASA isn’t alone, since Arianespace also has a messy labor history.)

The Discovery Institute is still singing the same tune. It’s revealingly tone-deaf, too. David Klinghoffer champions falsification as a key strategy, and he doesn’t even understand it.

Want to falsify the theory of intelligent design? Here’s one way.

Show with a convincing computer simulation – no cheating allowed — that the infusion of biological information in the Cambrian explosion could occur absent the intervention of a guiding intelligence: artificial life in a variety as we see in the Cambrian event, but without design.

He starts out with an interesting proposal: falsify his favored theory. That’s how science works. We propose a hypothesis, and then we batter it about trying to find the flaws and identify tests that would evaluate whether our proposal actually works. I read that and thought that finally we were going to see a testable claim about Intelligent Design creationism.

No such luck. Read the next sentence, and he isn’t taking a critical look at ID creationism: he announces that we have to come up with a test to prove our theory is possible. That isn’t a falsification test! It’s the opposite of falsification — we have to prove every detail of evolutionary theory is true, or he gets to claim his bullshit idea is true.

Wesley Elsberry takes on the bizarre infatuation of creationists with binary models. This is good stuff.

There is nothing in falsification about how validating some other concept makes a concept false. This is a popular misconception in antievolution circles, though, as one finds this particular mistake in the output of various high-profile “intelligent design” creationists. It is a long-running misconception, a zombie pseudoscience if you will, as I was pointing this out directly to William Dembski and Michael Behe at a conference in 2001, and it continued to put in appearances from them later.

One might wonder why IDC advocates have such trouble with this. I think that it follows from confusing and conflating their “two-model” worldview with an actual concept in philosophy. The “two-model” view was a component of “scientific creationism” that has propagated through the various renamings that have followed it. The “two-model” view states that there are only two possible models, creationism or evolution, and evidence against one is evidence for the other. In other words, that one’s likelihood of belief in one can be bolstered by reducing one’s likelihood of belief in the other. Or, putting it in the terms that likely led to the confusion, the falsity of one model attests to the truth of the other. This whole notion is rank nonsense, and has been exposed as rank nonsense for decades. For example, Francisco Ayala, as a witness in the McLean v. Arkansas case in 1981 was questioned about the soundness of the “two-model” view by an unfortunate lawyer named Williams. Ayala said, “Surely you realize that not being Mr. Williams in no way entails being Mr. Ayala!” Judge Overton in his decision also noted the inherent problems with what he termed “a contrived dualism”. This was referenced in the Kitzmiller v. Dover decision as well, where it was noted that the same erroneous argumentation had been carried forward to that case.

I also take exception to creationist’s constant focus on “computer models”. Computer models are useful tools for assessing some ideas, but they’re no substitute for real data…especially when the events you’re pursuing are not simple, and have a million different equally valid ways of producing a result. Again with the binary thinking: Cambrian evolution will not be described with a “yes” or a “no”.

I’m also going to call shenanigans on his assumptions. The Cambrian was not an “event”. It was a long, multi-million year series of events, and it was driven by multiple phenomena. There was the pre-Cambrian bioturbation revolution, in which the evolution of worms with hydraulic skeletons drove massive turnover of nutrients in sediments; there was the gradual increase in atmospheric oxygen, which made more energetic organisms possible; there was a long history of evolution of animal lineages before the Cambrian that set the stage with breadth and depth of diversity. How do you “simulate” all that on a computer? And why bother, because you know creationists like Klinghoffer will simply reject any result that shows an increase in complexity without an infusion of biological information (whatever that means) as cheating?

Most importantly, no one with any sense or competence would carry out such a simulation to falsify creationism, an endeavor with no reward, since they’ll just move the goalposts as they always have.

David Attenborough is going to need a replacement someday (no hurry!), and I think I’ve found him: it’s Aiden the Zoologist.

He seems to know what he’s talking about, and he’s certainly enthusiastic. All we need to do now is get him through college.

Trapped in a cunning prison!

Oh, no, what are you doing now?

[Read more…]

You can lie with numbers as effectively as you can with words, so this collection of rules for critically evaluating Big Data claims is timely. I think they missed at least one, though. It was caricatured in a recent xkcd:

I’m seeing a lot of these lately. For example, here are the most popular porn searches by state. I’m sorry to say that this is mostly garbage data, useless to everyone.

These data are produced by basically subtracting (or dividing) away the mean and amplifying the differences. I suspect that there is a great sea of banal commonality to porn searches, and they’re more or less the same everywhere…but all the similarities are erased to accentuate slight variations that might be minuscule. If everyone in America were searching for “insect porn”, which would be an interesting and weird piece of data, and one guy in New Hampshire slipped and typed in “incest porn” instead, New Hampshire would be lit up in these maps as the freaky state that wasn’t watching mantis copulation videos.

You might be saying to yourself that this is a trivial example — OK, let’s be cautious in interpreting data techniques that rely on amplifying minor differences, since they can mislead you about the overall state of the system. However, there is a technique that gets published all over the place in the scientific literature that is doing exactly the same thing: it’s called fMRI. This is not to imply that MRI data is bogus, because it’s very good at detecting consistent differences in pattern, but it’s also very good at highlighting chance variation, and it takes a lot of processing to smooth out the roughness in the raw data, and the whole point of the technique is to erase background activity.

I used to do ratiometric imaging, which has similar potential pitfalls. We used a fluorescent dye that would exhibit subtle wavelength shifts in the presence of calcium, so you would visualize activity in the brain by taking a photo at one wavelength, and then a second photo at a slightly different peak wavelength a fraction of a second later, and then taking the ratio of the two. If there was no shift at all, the images would be identical, so every pixel would have a ratio of 1 — which we’d scale to a displayed color of black. If a pixel was fluorescing a little more at the second wavelength, you’d have a ratio slightly greater than 1, and we’d pseudocolor that to something a little brighter.

Again, this is a perfectly legitimate processing technique and the fluctuations we observed were valid and consistent, and you could even calibrate the ratios against known concentrations of calcium and get good estimates of the actual amount of free calcium at each time point in a recording. However, here’s the thing: if you looked at the raw data, or if you looked through the eyepieces at the tissue, you’d see that everything was gently glowing, and that there was actually artifactual fluorescence all over the place, and there was also continuous, low-level calcium flux everywhere, all the time. That information was discarded. Also, when you see the pseudocolored images rendered by these sort of techniques, there’s an awful lot of point variation that is smoothed away, because we tend not to like our pretty pictures spattered with lots of salt-and-pepper noise. We blur it all out.

This is a special problem for methods like MRI, which tend to be at a painfully low resolution (each pixel represents thousands upon thousands of cells), and is also grossly indirect — it’s measuring oxygen and blood flow, not actual electrical activity.

To that list of Big Data cautions, I’d also add that you have to be conscious of what is actually being measured, limitations of the technique, and how you can be misled by assumptions about the resolution. Data can be massaged into all kinds of ridiculous conclusions if you’re not aware of every step of its manipulation.

None of the above: it’s a unique canid, the long-legged South American maned wolf. But it’s not a wolf.

As you might guess, this collection of photos is not safe for work, even though there is nothing particularly prurient about it. One hundred men stood in nearly identical poses, and were then photographed between waist and thighs, and there they are, a hundred weird-looking dinguses in an array.

What’s striking is how much variability there is. It looks to me like evolution has not been paying much attention to this feature: they all work well enough so the differences really don’t matter much. “Normal” is a word that covers a surprisingly wide range here.