Several people have pointed me to Stephen Hawking’s warning about ‘First Contact’ with aliens. Specifically that we’d be on the short end of the stick. His worry reminded me of something I read as a child which shocked me somewhat when I encountered it, as I was conditioned by a post-Cosmos optimism. Here’s the author:

…I find it mind-boggling that the astronomers now eager to spend a hundred million dollars on the search for extraterrestrial life never thought seriously about the most obvious question: what would happen if we found it, or if it found us. The astronomers tacitly assume that we and the little green monsters would welcome each other and settle down to fascinating conversations. Here again, our own experience on Earth offers useful guidance. We’ve already discovered two species that are very itnelligent but less technically advanced than we are-the common chimpanzee and pygmy chimpanzee. Has our response been to sit down and try to communicate with them? Of course not. Instead we shoot them, dissect them, cut off their hands for trophies, put them on exhibit in cages, inject them with AIDS virus as a medical experiment, and estroy or take over their habitats. That response was predictable, because human explorers who discvered technically less advanced humans also regularly responded by shooting them, decimating their popualtiosn with new diseases, and destroything or taking over their habitats.

Any advanced extraterrestrials who discovered us would surely treat us in the same way….

That was Jared Diamond in The Third Chimpanzee. In terms of this particular concern I have to admit that my attitude is encapsulated by Arthur C. Clarke’s third law of prediction. An advanced alien race is basically going to have magical powers in relation to humanity, and I doubt anything we do will matter either way (i.e., I don’t think we could hide, or, get their attention). But my main question is why haven’t the von Neumann machines already co-opted all the matter and energy in the universe? The Fermi paradox is a real issue. There are still big questions that we have no idea or clue about.

Michael Arrington of TechCrunch has a post up, The Age Of Facebook. Facebook having superseded Google having superseded Microsoft. Unstated that Microsoft superseded IBM as a firm which defines an age through reach, power and influence. Two thoughts that come to mind:

1) It seems that each “age” has been shorter than the previous. IBM was computing for decades. Microsoft probably ten years or so depending on how you define it (I put the second derivate maximum at 1995). Google’s real ascent seems to date to around 2000, but its monopolistic plateau of the mindshare didn’t seem to last for very long as Facebook was already generating a lot of buzz by 2007 (the same principle operates across human history, the civilization of Pharaonic Egypt spanned 2,000 years, the same length as from Augustus to our own time!)

2) It also seems that the extent of a definite age of ascendancy for a particular firm is more muddled now, as creative destruction and innovation allow for many domains of excellence and supremacy, as well as the resurrection of bygone brands. Consider the revival of Apple’s fortunes. And if we are on the verge of the Age of Facebook does anyone believe that Google’s brand will collapse? Arrington notes that Microsoft is perceived to be passed its peak, but it has many years left of its cash cow products, perhaps at least another decade. IBM has reemerged as a software services company. And so on. On a relative scale Arrington’s argument seems to have some merit, but secure domination doesn’t seem to be what it used to be (also, one might need to distinguish between buzz and influence, and concrete metrics).

Alan Templeton, whose text Population Genetics and Microevolutionary Theory is right below Hartl & Clark in my book, recently published a strongly worded paper, Coherent and incoherent inference in phylogeography and human evolution. The possibility of statistical errors in published work is not shocking, I have heard that when statisticians are asked to sort through papers in medical genetics journals there are elementary errors in ~3/4 of those which have made it beyond peer review. That being said Templeton seems to be making a stronger case than simple refutation of basic errors, in particular he is suggesting that the “ABC” method which lay at the heart of the paper I reviewed last week is incoherent at the root. Here’s Templeton’s abstract:

A hypothesis is nested within a more general hypothesis when it is a special case of the more general hypothesis. Composite hypotheses consist of more than one component, and in many cases different composite hypotheses can share some but not all of these components and hence are overlapping. In statistics, coherent measures of fit of nested and overlapping composite hypotheses are technically those measures that are consistent with the constraints of formal logic. For example, the probability of the nested special case must be less than or equal to the probability of the general model within which the special case is nested. Any statistic that assigns greater probability to the special case is said to be incoherent. An example of incoherence is shown in human evolution, for which the approximate Bayesian computation (ABC) method assigned a probability to a model of human evolution that was a thousand-fold larger than a more general model within which the first model was fully nested. Possible causes of this incoherence are identified, and corrections and restrictions are suggested to make ABC and similar methods coherent. Another coalescent-based method, nested clade phylogeographic analysis, is coherent and also allows the testing of individual components of composite hypotheses, another attribute lacking in ABC and other coalescent-simulation approaches. Incoherence is a highly undesirable property because it means that the inference is mathematically incorrect and formally illogical, and the published incoherent inferences on human evolution that favor the out-of-Africa replacement hypothesis have no statistical or logical validity.

The method which Templeton favors is naturally one which he has pushed in the past. In any case, I don’t know the statistical details well enough to comment with much knowledge, but I see that a statistician has responded to Templeton already, so I would recommend checking that out. I immediately went looking for responses because the paper uses really strong and dismissive language, and I am somewhat wary of that sort of thing when attempting to tear down the fundamentals of a whole field of research (I want to emphasize that overall I enjoy Templeton’s work, but the paper reminded me a bit too much of Jerry Fodor). His citation of Popper in particular seems an appeal to authority that aims to convince the non-statisticians in the audience, and I don’t see the point of that besides rhetorical utility. I do tend to accept somewhat Templeton’s critique of models which assume very little gene flow between hominin populations before the Out-of-Africa migration, though from what I can tell it does seem that Africa has had relatively little back-migration south of the Sahara over the past 50,000 years, so perhaps this is an older dynamic as well. I am cautiously optimistic that DNA extraction from fossils themselves may put to bed some of these arguments over the dance of parameters, though naturally interpretation is always an issue outside of pure mathematics.

For what it’s worth, here’s the model which Templeton’s method favors:
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I think it is probably (or should be) an uncontroversial statement to say that recent genome-wide association studies have revolutionized our understanding of the molecular basis of variation in disease risk in humans. From a handful of polymorphisms reliably associated with a few diseases, there are now hundreds of such associations for a wide spectrum of disease and non-disease traits. That said, these studies have been disappointing to some–even now, the genetic loci identified are generally a poor predictor of whether a person will get a disease or not. This has led to something of a backlash against these sorts of studies. Some of this backlash is fair enough, but some of the arguments presented are problematic. One bizarre argument that seems to be gaining some traction is that, since genome-wide association studies are finding many non-genic regions associated with disease risk, they’re not identifying anything functionally relevant. See, for example, this article in the New York Times, and a recent commentary by McClellan and King. Here are McClellan and King:

A major limitation of genome-wide association studies is the lack of any functional link between the vast majority of risk variants and the disorders they putatively influence…Very few published risk variants lie in coding regions, in UTRs, in promoters, or even in predicted intronic or intergenic regulatory regions. Far fewer have been shown to alter the function of any of these sequences. How did genome-wide association studies come to be populated by risk variants with no known function?

Their answer to this rhetorical question is that common SNPs (used on current genotyping platforms) are generally nonfunctional. The alternative, the evidence for which I’ll present here, is that our ability to predict functional SNPs is poor. In the phrase “no known function”, the emphasis should be on the word “known”.
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What is the impact of strict population control? Unintended consequences. Note the convergence in fertility between South Korea and the People’s Republic of China. Coercion or no, some things are inevitable.

Beating Obesity. Marc Ambinder went from 235 to 150 in a year after surgery.

For ancient hominids, thumbs up on precision grip. Many things which we perceive to be derived may be more ancestral than we’d thought.

New Genetic Framework Could Help Explain Drug Side Effects. Medicine is a crap shoot, so you want to load the die in your favor as much as you can.

Chimpanzees Prefer Fair Play To Reaping An Unjust Reward. Not too surprising, but there’s a lot of “complex behavior” whose building blocks are probably pretty ancient. The fact that humans can “socialize” with dogs and cats are somewhat suggestive to me of common mammalian cognitive furniture.

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Mirrored from Wiring the Brain (http://wiringthebrain.blogspot.com/)

Faces are special. Humans are innately interested in faces and so good at detecting them that we see them in clouds, shrouds, pieces of toast, tree-stumps, and even simple yellow circles with a couple of dots in them. Even newborn infants (really, really newborn) are more interested in looking at faces than non-faces. Not too surprisingly, this preference and ability extends to other species too. Monkeys reared from birth with absolutely no visual exposure to either monkey or human faces for two years still showed a strong preferential interest in faces (both monkey and human) when they were shown them. Given the importance within social groups of recognising particular individuals and of reading emotional and social cues from people’s faces, it is perhaps not too surprising that face recognition is a built-in part of our cognitive toolkit.

This is not to say that experience plays no part in the skill of face recognition – we clearly improve with practice and exposure in the ability to distinguish large numbers of faces. This can clearly be seen in the effect of cultural exposure to people of different races on the ability to distinguish such faces. (Most people are significantly worse at distinguishing between faces in races other than their own). We are thus pre-wired to be interested in faces and to process them differently from other visual stimuli, but we still need experience to be good at it.
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Remember when there was talk about how SARS might disproportionately hit Chinese in comparison to other populations? Here’s a new paper on how Swine Flu may progress in different populations, Clinical Findings and Demographic Factors Associated With ICU Admission in Utah Due to Novel 2009 Influenza A(H1N1) Infection:

The ICU cohort of 47 influenza patients had a median age of 34 years, Acute Physiology and Chronic Health Evaluation II score of 21, and BMI of 35 kg/m². Mortality was 17% (8/47). All eight deaths occurred among the 64% of patients (n = 30) with ARDS, 26 (87%) of whom also developed multiorgan failure. Compared with the Salt Lake County population, patients with novel A(H1N1) were more likely to be obese (22% vs 74%; P < .001), medically uninsured (14% vs 45%; P < .001), and Hispanic (13% vs 23%; P < .01) or Pacific Islander (1% vs 26%; P < .001). Observed ICU admissions were 15-fold greater than expected for those with BMI ≥ 40 kg/m² (standardized morbidity ratio 15.8, 95% CI, 8.3-23.4) and 1.5-fold greater than expected among those with BMI of 30 to 39 kg/m² for age-adjusted and sex-adjusted rates for Salt Lake County.

Remember that these are 47 intensive care patients, the most extreme cases. Here’s a table with N’s & odds ratios:
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Since I’ve been talking about the possibility of admixture with “archaics” (I’m starting to think the term is a bit too H. sapiens sapiens-centric, is the Neandertal genome turning out to have more ancestral alleles?) I thought I’d point to a paper out in PLoS ONE which reiterates the basic fact that the overwhelming genetic evidence today suggests a massive demographic expansion from an African population within the last 100,000 years. Study after study has supported this contention since the mid-1980s. The question is whether this is the exclusive component of modern human genetic ancestry, which is a somewhat more extreme scenario. In any case, the paper is Formulating a Historical and Demographic Model of Recent Human Evolution Based on Resequencing Data from Noncoding Regions:

Our results support a model in which modern humans left Africa through a single major dispersal event occurring ~60,000 years ago, corresponding to a drastic reduction of ~5 times the effective population size of the ancestral African population of ~13,800 individuals. Subsequently, the ancestors of modern Europeans and East Asians diverged much later, ~22,500 years ago, from the population of ancestral migrants. This late diversification of Eurasians after the African exodus points to the occurrence of a long maturation phase in which the ancestral Eurasian population was not yet diversified.

They took 213 individuals, a little over half from diverse African groups, and the other half split evenly between Europeans and East Asians, and sequenced 20 distinct noncoding autosomal regions of the genome. ~27 kilobases per person. The noncoding part is important because they are trying to look at neutral regions of the genome, not subject to natural selection (this is obviously an approximation, as there is some evidence that even noncoding regions may have some selective value). The variation is what you’d expect, Africans more varied than non-Africans, and the two Eurasian populations are distinct from each other, but less so than either is from the Africans. Lots of statistics ensue, and an “Approximate Bayesian Computation (ABC) analysis.” I’ll cut to the chase, the highest probability model is illustrated in panel A of figure 4. Expansion out of Africa ~60,000 years ago, major bottleneck, a ~40,000 year interregnum where there was a relatively unified Eurasian population genetically, and then a separation between East and West Eurasians ~20,000 years ago.
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Perhaps. Matt Stone & Trey Parker have put out a statement. I watched it online yesterday and I thought the bleeps were part of the “in joke.” I’ll spoil the episode for you by noting that it wasn’t even Muhammad in the bear a suit. Additionally I don’t get why people are that that scared, the threats were made by a group that’s very close to literally being in a basement. On the other hand, remember during the Salman Rushdie affair that translators were killed, so perhaps there’s reason that a corporation would want to stay on the safe side (one could imagine civil lawsuits if someone did get hurt against the corporation).

On final thing, the South Park episode in question depicted Moses as a dull artificial intelligence, Buddha as a cocaine junkie and Jesus as a habitual viewer of internet pornography (at least that’s Buddha’s accusation, which Jesus does not deny, rather, he minimizes its equivalence with a drug habit. I think Jesus’ logic is spot on, and am leaning toward Brit Hume’s dismissal of Buddhism on account of this interaction). There are of course Jewish,* Christian and Buddhist extremists in world. But most people judge that Jews, Christians and Buddhist are less liable to take violent action to defend the dignity of their faith than extremist Muslims. I think that’s probably a valid assessment, and I think that points to the fact that not all religions can be made equivalent in the nature and numbers of violent radicals. Why that is is a different question.

* Because Judaism is operationally coterminous with an ethnicity, at least by self-conception, I have seen some attempts to accuse those who have anti-Jewish religious views as anti-Semites. In general anti-Semites have anti-Jewish attitudes in regards to the religion, but the inverse is not always so. Some Muslims have started imitating that strategy, accusing plain anti-religious folk like Richard Dawkins of being an Islamophobe as if he is racist.