The Sinmantyx Statistic Posts

Some of my fondest childhood memories were of reading Discover Magazine and National Geographic in my grandfather’s basement. He more than anyone cultivated my interest in science, and having an encyclopedia for a dad didn’t hurt either. This led to a casual interest in statistics, which popped up time and again as the bedrock of science.

Jumping ahead a few years, writing Proof of God led me towards the field of epistemology, or how we know what we know. This fit neatly next to my love of algorithms and computers, and I spent many a fun afternoon trying to assess and break down knowledge systems. I forget exactly how I was introduced to Bayesian statistics; I suspect I may have stumbled across a few articles by chance, but it’s also possible Richard Carrier’s cheerleading was my first introduction. Either way, I began studying the subject with gusto.

By the time I’d started blogging over at Sinmantyx, I had a little experience with the subject and I was dying to flex it. And so Bayesian statistics became a major theme of my blog posts, to the point that I think it deserves its own section.

Speaking of which, I’ve decided to post-date any and all Sinmantyx posts that I re-post over here. There was never any real “publication date” for Proof of God, as it was never published and I constantly went back and revised it over the years I spent writing it, so I feel free to assign any date I want to them. The opposite is true of my Sinmantyx work, and so I’ll defer to their original publication date. This does create a problem in finding these posts, as more than likely they’ll never make the RSS feed. Not to worry: I’ll use this blog post to catalog them, so just bookmark this or look for it along my blog header.

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I Sure Hope Not

Neo-Nazis The Alt-Right seem to be on the ascendency in North America, so it’s time to get to know them.

With its angry, anti-liberal, race-obsessed, occasionally apocalyptic tone, the Rebel resembles Breitbart, the conservative American website once run by Stephen Bannon, who is now Donald Trump’s chief strategist (a typical headline: “Idaho Dems Exec Director: DNC Should Train People ‘How to Shut Their Mouths If They’re White’”). That’s no coincidence: [Erza] Levant said during the cruise that Breitbart was a major inspiration for the Rebel. Which is exactly why I spent a week of my life rubbing elbows with Levant’s most dedicated followers. Bannon’s acolytes, too, once were mocked and ridiculed as marginal loons—until they got their man into the White House. Could Levant manage the same trick here in Canada?

It might also serve as a wake-up call for those who say it can’t happen up here. What would they say to this?

How does an ordinary Canadian become a Rebel? During my week at sea, I began to classify Rebels according to the issues that made them angriest—the ones that had originally brought them into Levant’s orbit. Fear of Islam and a distrust of mainstream climate-change science were the most prevalent. Rebels might start out as temperate conservatives, centrists, or even leftists (Faith Goldy said that her conservatism had emerged from the ashes of a youthful hard-left zeal). But at some point, a gateway issue draws them in. […]

Finding scant support for his views in the mainstream media, the nascent Rebel turns to Google, where his search for truth might lead to one of the many clickbait videos posted on Levant’s web site. (The Rebel has racked up more than six million YouTube views per month since its launch in early 2015. No one writes a headline like Levant.) Driven by a convert’s zeal, the newly minted Rebel becomes not only a steady consumer of Rebel content but also a publisher—spamming his friends with the stuff on Twitter and Facebook.

One Rebel I met, a middle-aged oil-patch worker from northern Alberta, described his daily media consumption as follows: First he goes to Breitbart for news, then the Rebel for “analysis,” then his local Sun newspaper “for entertainment.” Time permitting, he’ll move on to the Globe and Mail or the Toronto Star or the CBC—but only if he isn’t already “angry enough.” (That last bit was said partly in jest, but the rest was in earnest.) I met members of two families for whom Rebel consumption is a daily bonding ritual: One retired couple keeps the laptop open on the breakfast table every morning, with Rebel videos turned up loud. One mother watches Rebel videos every night with her teenaged daughters.

That’s textbook radicalization, in this case disguised as a luxury cruise. It makes for a helluva story.

Proof from Intelligence (4)

Visual Processing

The same reasoning applies to visual processing.

Object recognition has always been one of our strongest points. Hand us a photo of an object, say a bicycle or a fire hydrant, then ask us to find it in another photo and we’ll have no problems. This simple task is actually incredibly difficult for a computer to pull off, since the target object may be rotated differently, obscured behind another one, differently coloured, or even have a texture overlaid on it. Tomaso Poggio of MIT thinks it’s as difficult a feat as simulating intelligence in general.

He should know: he’s partially cracked that problem.

In 2007, he released two papers that detailed a new method of object recognition. For one of those papers, he did exactly the task I outlined above.[45] The new algorithm was able to track down an object about 97% of the time, though it could range from 93% to 99.8% accuracy depending on the exact task. Unlike most other algorithms, which specialize in finding only one type of object, his method works equally well on a wide variety of objects.

There’s good reason for that: it’s modelled on the human visual system. His second paper demonstrates just how closely that model follows reality, by pitting man against machine.[46] Poggio sat human beings down in front of a computer, flashed them a single image for 1/50th of a second, then asked the humans if there was an animal in the scene or not. We’re literally born for this task; how fast you can tell if that’s a wild animal or a branch dropping towards you determines how likely you are to survive and pop out offspring. Unsurprisingly, human beings do pretty well at this, getting it right around 80% of the time.

Poggio’s algorithm was then used to classify each image. The results? It guessed correctly  80% of the time. Eerily, when the researchers analysed the images the algorithm did poorly on, they discovered that the humans had struggled on those images as well.

This algorithm can still be improved. Our brains use feedback from other parts of the brain to improve our guesses further, something this method doesn’t handle. It also took much longer for this algorithm to come to a conclusion than our brains did, but that’s only a temporary problem. Computers improve in speed much faster than human brains do, and more efficient programming should reduce the number of necessary calculations.

Still, Poggio’s work hints very strongly that there’s no magic to our visual system.

Music

Sounds may be another matter, though. Not just any sound, though, but the semi-repetitive collections of sound we call music. Humans have spent centuries, probably even millennia, creating harmonies and melodies for no other reason than pleasure. No other species can dare make that claim.

Well, except birds. And maybe whales. Oh, and gibbons.

But before we get into the details, we first have to settle what music is. The suboscine branch of the bird family can have elaborate calls, but those are hard-wired into their genes. You can separate them from their parents, play the songs of other birds as often as you want, and they’ll still chirp out their innate tune. Most people would not consider this music; there must be an element of creativity involved, and while genes can produce variation through mutations, that happens on too long a time scale to qualify.

Songbirds are a different feather. Play them a tune at the right age, and they’ll pick it up and use it as their own. Deprive them of music, and they’ll sing poorly or not at all. While better, this still doesn’t quite qualify as a creative act since they’re just copying the songs they heard. Changes will happen over time due to accident, faster than they would through genes, but still not fast enough.

Not all songbirds are born alike, though. The Indigo Bunting will pluck a song out of thin air, with no resemblance to anything it’s heard before, then slowly mix in fragments from nearby competitors until it becomes a variation on a theme. Mockingbirds got their name from a remarkable ability to imitate sounds in their environment, everything from the calls of insects to the ring of a cell phone, which are then incorporated into their songs. Both species can be considered creative.

Both could also be dismissed as too greedy. Birdsong is primarily used to attract mates, warn about predators, and establish territory. It also makes a handy show of fitness; sick birds have difficulty carrying a tune, and it puts them at risk of an attack by predator. The music that human beings make has much purer motives, and is rarely used to show off.

Sorry, but I couldn’t keep a straight face while writing that last line. One of the leading theories of why we make music is that it’s a show a reproductive fitness. Humans can’t sing or play an instrument very well if they’re sick, either, and we frequently use music to set a romantic mood. As Geoffrey Miller of the University of New Mexico has pointed out, musical output peaks and declines with sexual ability, and a whopping 40% of all lyrics relate to sex or romance. Musicians are usually considered sexually desirable.

Consider Jimi Hendrix, for example.  This rock guitarist extraordinaire died at the age of 27 in 1970, overdosing on the drugs he used to fire his musical imagination.  His music output, three studio albums and hundreds of live concerts,  did him no survival favours.  But he did have sexual liaisons with hundreds of groupies, maintained parallel long-term relationships with at least two women, and fathered at least three children in the U.S., Germany, and Sweden.  Under ancestral conditions before birth control, he would have fathered many more.  […] As Darwin realized, music’s aesthetic and emotional power, far from indicating a transcendental origin, point to a sexual-selection origin, where too much is never enough.  Our ancestral hominid-Hendrixes could never say, “OK, our music’s good enough, we can stop now”, because they were competing with all the hominid-Eric-Claptons, hominid-Jerry-Garcias, and hominid-John-Lennons.  The aesthetic and emotional power of music is exactly what we would expect from sexual selection’s arms race to impress minds like ours.

(“Evolution of human music through sexual selection,” by Geoffery Miller. Published in “The origins of music,” edited by N. L. Wallin et al, 2000. )

Most damning of all is the genetic evidence. If music was related to reproduction, we should expect to find genes that control it. Not only do those genes exist, but they’re almost identical to the genes that give birds the ability to create songs.

The identification of FOXP2 as the monogenetic locus of a human speech disorder exhibited by members of the family referred to as KE enables the first examination of whether molecular mechanisms for vocal learning are shared between humans and songbirds. […] In support of this idea, we find that FOXP1 and FOXP2 expression patterns in human fetal brain are strikingly similar to those in the songbird, including localization to subcortical structures that function in sensorimotor integration and the control of skilled, coordinated movement. The specific colocalization of FoxP1 and FoxP2 found in several structures in the bird and human brain predicts that mutations in FOXP1 could also be related to speech disorders.

(“Parallel FoxP1 and FoxP2 Expression in Songbird and Human Brain Predicts Functional Interaction,” by Ikuko Teramitsu et al. The Journal of Neuroscience, March 31, 2004, 24(13):3152-3163)

There’s still an objection to be made, even if we agree with Miller and others. An evolved trait may be used differently at different times. Music in human beings may have started as a show of fitness, but it need not stay that way. After all, very few people actively pursue a career in music; the majority instead write songs privately, for their own enjoyment. Human beings may have once sung for sex, but nowadays we’re more likely to sing for ourselves.

Against this stands the Brown Thrasher. Birdsong comes in roughly five flavours:[47] mating song (“I’m here, and I’m sexy!”), companion calling (“I’m here, where are you my mate/friend?”), begging by young birds (“GIMMMIE FOOOOD NOOOOOOOW!!”), trespass threats (“Get out of my area, you upstart, or else!”), and predator alerts (“I see something dangerous!”). Sometimes the lines can blur a bit (“Everybody, come help me harass this predator!”), and some species have multiple calls within each flavour (“Head’s up, it’s a predator from the sky!”), but a grand total of a dozen or two should be more than enough for most birds. And it is, generally.

So why does the Brown Thrasher have a library of 2,000 calls? To give that a baseline, the average vocabulary of a human being consists of 10,000 words.

 It’s tempting to dismiss all that variation as invention. The Thrasher may be taking a “base” song and improvising new versions of it. If this is the case, we’d expect very few songs to be repeated; instead, Thrashers can recall a song they tweeted nineteen days earlier.

Alternatively, that vast song repertoire may be a way to show off to the opposite sex. There’s a problem, however; most female songbirds are not attracted to males with a giant songbook.[48] One study showed that Brown Thrashers were actually more interested in a limited sample of Thrasher calls than the full collection, provided they displayed more versatility in singing ability.[49]

It’s tough to draw a definitive conclusion from a single study, so I won’t. What I will say is that it’s plausible the Brown Thrasher’s vast library is more for personal kicks than practical use.

Intrapersonal and Self-Awareness

Humans are quite good at understanding the personal. We’ve got an entire branch of science devoted to it, named psychology. Philosophers from Plato onward have valued looking inward, to discover what we really are like. Surely no other species can come close to us here.

So far as we know, none has. It’s hardly their fault, though; we have only two ways to learn about the inner lives of others, by direct communication and indirect brain scanning. With no way to ask other animals how they feel, and quite different brain structures between us, plumbing the depths of other species’ cognition ranges from difficult to impossible.

It doesn’t help that we tend to project ourselves onto other creatures. Alexandra Horowitz conducted a study that asked dog owners to forbid their pets to eat a treat. When the humans left the room, Horowitz randomly fed some of the dogs that forbidden fruit; when they came back, she randomly told some of the owners that the dog had eaten the treat. The humans that were told their pet had broken their order thought their dogs looked guilty, even if they never ate the treat. When punished, the pets that looked most guilty were actually the ones which never got a lick at the prize.[50] Any interpretation of animal behaviour has to be done very, very careful to filter out our inner biases.

We do, however, have a proxy for inner knowledge: knowledge of the self. If you have no concept of “you,” there’s no self to learn about. And once you realize there’s a “you” there, curiosity will drive you to give it a quick once-over, at minimum.

The standard test for self-awareness is pretty simple: place an animal in front of a mirror, and let them get used to it. Then put them to sleep, paint a dot on an area of their body that they can’t normally see, then wake them up and place them by the mirror. If they try to rub off or touch the dot, they must know the animal in the mirror is actually themselves, and must be capable of mapping between the image and themselves. Human children pass this test easily, as do all primates, elephants, dolphins, and European magpies.[51] Other species, such as pigs and pigeons, fail this test but can demonstrate that they know the image in the mirror reflects reality. In the case of pigeons, this can even be used to “train” them for the test, resulting in a pass.[52]

Those last results have been used to criticise the test; perhaps a species just doesn’t care about cleaning off the dot, leading researchers to falsely conclude it isn’t self-aware. Another problem is that self-recognition may not be tied to self-awareness; humans with prosopagnosia cannot recognize themselves, yet clearly are self-aware. Note however that both arguments lead us to conclude there are more self-aware species than we realize, not less.

[45] “Robust Object Recognition with Cortex-Like Mechanisms ,” Thomas Serre et al. IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol 29 No 3, March 2007 .

[46]”A feedforward architecture accounts for rapid categorization,” Thomas Serre et al. Proceedings of the National Academy of Sciences, vol. 104 no. 15 6424-6429, April 10, 2007.

[47] http://www.natureskills.com/birds/bird-language/

[48] http://www.sciencedirect.com/science/article/pii/S000334720800496X

[49]Boughey, M. J. and Thompson, N. S. (1981), “Song Variety in the Brown Thrasher (Toxostoma rufum). Zeitschrift für Tierpsychologie, 56: 47–58. doi: 10.1111/j.1439-0310.1981.tb01283.x

[50] http://www.elsevier.com/wps/find/authored_newsitem.cws_home/companynews05_01246

[51] http://www.plosbiology.org/article/info:doi/10.1371/journal.pbio.0060202

[52] http://www.sciencemag.org/content/212/4495/695

Zvan on the Gendered Pay Gap

I have a really nice document about the gendered pay gap buried on a hard drive. To write it, I spent a good few months reading policy documents and research study after research study after research study after research stu– well, you get the point. My favorite of the bunch is this one. The gender breakdown of an industry tends to vary with time, so Emily Murphy and Daniel Oesch looked into whether or not that effected pay.

Both baseline models suggest that moving from a male to a female occupation – or staying within an occupation that feminizes – entails a sizeable wage loss. Adding controls for the workplace (M1) and general human capital (M2) makes no difference: the wage penalty associated with FEM amounts to about 15 per cent for British women, British men and Swiss women, 15 and to about 5 per cent for German women, German men and Swiss men.
If women rush to your occupation, your wages drop… even if you’re a man or a childless woman. This is tough to explain as anything but discrimination.
While I’ve been mulling over how and when to release my document, Stephanie Zvan independently came up with her own version.
Let’s start by noting that at least one person who studies the factors that account for pay gaps says that choice of careers, while a factor in unequal pay, is not the silver-bullet solution that pay–gap critics suggest. It isn’t even the biggest factor driving the difference between men’s and women’s wages. […]
… even though women work fewer paid hours than men, they work the same number of hours overall. The reason women more frequently require constrained work weeks and more flexibility in their schedules is that they do the bulk of the unpaid work that makes our society run, particularly caregiving, both for children and for other adults.
It may not have an excessive number of footnotes, but her version states much the same thing as mine in fewer words and clearer language. Give it a read, in honour of International Why-Isn’t-There-An-International-Men’s-Day Day.

Proof from Intelligence (3)

Problem Solving

In the meantime, let’s start with a big one: problem solving. We pride ourselves on being able to fix situations that wouldn’t occur naturally. The lives of the Apollo 13 astronauts depended on fitting a square carbon dioxide filter into a smaller round hole, otherwise they would suffocate on their own breath. Nothing in that scenario is natural.

Wire isn’t natural, either, yet a crow surprised us by bending it into a hook. New Caledonian crows have been making hooks for some time, actually, but in the wild they use twigs instead. They learn this trick by watching other crows do it, too, and not by figuring out for themselves. For one of them to bend a material they’d never seen before, in a way they’ve never witnessed, is a significantly harder problem.

Betty pulled it off on her first attempt.

Jackie Chappell and company didn’t mean to test that. Betty and Alex, a male crow, were presented with a collection of bent and straight wire, then tested to see if they could use them to grab a tasty treat that was otherwise out of reach. Wire was used because both crows had rarely seen it in their lives. When Alex nabbed the only bent wire and flew off, Betty grabbed a straight piece and bent it into a hook with her beak and feet.

After the researchers picked themselves up off the floor, they devised a new test. Separately, each crow was given a straight wire and a treat that was otherwise out of reach. Out of ten trials, Alex only succeeded once, and even then he cheated. Nine times out of ten, Betty tried to pick up the treat with the straight wire, failed, then bent the wire into a hook using her beak, feet, or the tube containing the food, and succeeded in getting the treat.

Betty had be raised in captivity, so she couldn’t have learned this trick from her wild peers. She had to analyse this new situation, find a solution using what she knew about the materials and herself, then put it in motion. That’s novel problem solving, done in a species with a much smaller brain than ours.

There’s also the case of a feisty octopus at the Sea Star Aquarium in Coburg, Germany. It did not like captivity one bit, and found creative ways to protest. Otto would juggle its non-mobile tank-mates, sometimes hiding them under grate covers, and several times shorted out a bright light by squirting it.

Think about that last one. Octopuses live entirely underwater, where they swim by sucking in and squirting out water. Light bends when it moves from air to water or vice versa, and even we humans take a fair bit of training to compensate for that. So in order to hit that light, Otto had to take an organ it uses for a single purpose and put it to a different use in a habitat it never visits with physics quite different from its home turf, and hit a small target that isn’t where it appears to be.

Nothing about that is natural, either.

Mathematics and Logical Thinking

Neither is calculus, for that matter. And yet human beings have no problems doing complicated arithmetic in their heads, or pondering long chains of subtle logic. Our fellow species can barely count, in comparison.

There is one crucial difference, however: Homo Sapiens Sapiens goes to school. We’re not born math wizards, we have to be taught via long, intensive training sessions. Remove those, and our huge advantage goes with it. Good proof of this comes from the languages of hunter-gatherers. They spent most of their time sleeping, doing chores, gathering food, or fighting. There was no time or need to invent mathematics, so whatever number systems they came up with reflect our uneducated understanding of number.

Their achievements are depressing. Many hunter-gatherers could barely count, usually reaching no higher than one or two before invoking words that mean “few” or “many.” Some didn’t even have the concept of “one”:

In Pirahã, there are two words which prototypically mean ’one’ and ’a couple’ respectively, but it has been checked fairly extensively that their meanings are fuzzy ’one’ and ’two’ rather than discrete quantities (Everett 2005, 2004, Frank et al. 2008). It is not possible to combine or repeat them to denote higher (inexact?) quantities either (Gordon 2004). The Pirahã have the same cognitive capabilities as other humans and they are able to perform tasks which require discerning exact numeration up to the subitizing limit, i.e. about 3 (Gordon 2004). They just do not have normed expressions even for low quantities, and live their life happily without paying much attention to exact numbers.


(Unsupervised Learning of Morphology and the Languages of the World,” chapter Nine. Harald Hammarström , 2009)

The last two sentences of that quote bring up more evidence; our subitizing limit, better known as our working memory capacity, is only three or four items.[44] If you’ve had no training on how to count or do math, that’s the only storage space you have for numbers, and thus it limits how high you can count.

Interestingly, our species’ subitizing limit is on par with other species.

In a study published last summer in the Proceedings of the Royal Society B, Kevin C. Burns of Victoria University of Wellington in New Zealand and his colleagues burrowed holes in fallen logs and stored varying numbers of mealworms (beetle larvae) in these holes in full view of wild New Zealand robins at the Karori Wildlife Sanctuary. Not only did the robins flock first to the holes with the most mealworms, but if Burns tricked them, removing some of the insects when they weren’t looking, the robins spent twice as long scouring the hole for the missing mealworms. “They probably have some innate ability to discern between small numbers” as three and four, Burns thinks, but they also “use their number sense on a daily basis, and so through trial and error, they can train themselves to identify numbers up to 12.”

More recently, in the April issue of the same Royal Society journal, Rosa Rugani of the University of Trento in Italy and her team demonstrated arithmetic in newly hatched chickens. The scientists reared the chicks with five identical objects, and the newborns imprinted on these objects, considering them their parents. But when the scientists subtracted two or three of the original objects and left the remainders behind screens, the chicks went looking for the larger number of objects, sensing that Mom was more like a three and not a two. Rugani also varied the size of the objects to rule out the possibility the chicks were identifying groups based simply on the fact that larger numbers of items take up more space than smaller numbers.

(“More Animals Seem to Have Some Ability to Count,” by Michael Tennesen. Scientific American, September 2009.)

We’ve managed to out-reason other species because we found a very efficient way to gather food, which freed up enough spare time to come up with wonderful systems of math, and because our longer lifespans increased the odds of us stumbling on a technique, or gave us more time to learn it from someone else. No other species has pulled off both feats; elephants and whales rarely use tools to gather food, and wild crows only live eight years.

When you provide both time and training, other species can break past the subitizing limit too.

[Pepperburg] discovered that Alex could accurately add two sets of objects, such as crackers or jelly beans, so long as the total was six or fewer. In related work, Alex learned to order the Arabic numerals 1 through 8 (in the form of multi-coloured refrigerator magnets) in the correct order. She says he then spontaneously learned to equate these symbols with the appropriate number of objects.

In the newly published work, Pepperberg tested whether Alex could correctly add the Arabic numerals and also whether he could sum three sets of objects totalling 6 or less. Both experiments were cut short when Alex died, but Pepperberg says that the parrot did better than chance in both experiments.

In 12 trials of the Arabic numeral addition task, when asked “How many total?” he indicated the correct sum 9 times, demonstrating that 3 + 4 is 7, 4 + 2 is 6, 4 + 4 is 8 and so on. When presented sequentially with three sets of objects hidden under three cups, and asked how many, Alex offered the correct answer eight out of 10 times. He determined, for instance, that one, two and one jelly beans adds up to four.

(“Alex the parrot’s last experiment shows his mathematical genius,” Ewen Callaway. Nature News Blog. )

Even if you don’t agree with the above argument, there’s still the mechanistic one. As I write this, the fastest computer in the world can perform about 8,162,000,000,000,000 math operations per second, to sixteen digits of precision. The computer I’m typing this document on can manage roughly 1,570,000,000, and even my phone does 6,900,000. In comparison, try working out this slightly easier calculation entirely in your head:

 

29669907

x

42669080

 

 Currently, Marc Jornet Sanz is the fastest multiplier on this planet. He can do the math above in about thirty seconds, without any mechanical aids, which translates to roughly 0.04 calculations per second.

Computers can do more than mundane arithmetic, too. Mathematicians have begun to rely on them for proving theorems. They are commonly used to verify proofs, a tedious and error-prone task, but computers are increasingly generating their own proofs. To name one example, the Robbins conjecture was proven by EQP, a computer program developed at Argonne National Laboratory in the United States.

If mathematics and logic can be done as well, or even better, by a machine, we have no reason to think of them as gifts from a god.

[44] Thanks to a misunderstanding, most people think this number is actually seven. See “Seven plus or minus two,” by Jeanne Farrington. Performance Improvement Quarterly, 23: 113–116.

BBC’s “Transgender Kids, Who Knows Best?” p4: Dirty Sexy Brains

This series on BBC’s “Transgender Kids: Who Knows Best?” is co-authored by HJ Hornbeck and Siobhan O’Leary. It attempts to fact-check and explore the many claims of the documentary concerning gender variant youth. You can follow the rest of the series here:

  1. Part One: You got Autism in my Gender Dysphoria!
  2. Part Two: Say it with me now…
  3. Part Three: My old friend, eighty percent
  4. Part Four: Dirty Sexy Brains

In North America, one of our pet obsessions is dividing everything up according to sex. Gendered toys, gendered clothes, gendered bathrooms, even gendered jobs. And yet if you follow those links, you’ll find these divisions were always in flux: gender-neutral toys used to be common yet are increasingly rare; dresses were gender-neutral, and colours weren’t gendered until roughly World War I; there were no public women’s washrooms in the US until the 1880’s, because women weren’t allowed in public; and computer science flipped from being women’s work to men’s work in the span of a few decades, leading to increased salaries and prestige.

This extends all the way down to our organs.

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A Wee Peek

Ugh, I wish I had more time to sink into this blog. What’s worst, most of what I’m focused on can’t or is too boring to share over here.

Most. There are always exceptions, of course.

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Proof from Intelligence (2)

Divine Gift or Solvable Mystery?

Suppose, for argument’s sake, we claimed long-term memory as definitive proof of the intellectual superiority of human beings over all its peers. Suppose that a few decades from now, scientists crack their current roadblocks and come up with a complicated but complete understanding of the brain processes responsible. Obviously, we’d look like fools for casting our chips on a losing bet, and begin looking for some other mystery of intelligence to claim as a divine gift.

But how can we tell the difference between a divine gift and a solvable mystery?

A divine gift could never be understood by scientific means. A solvable mystery will be, if you don’t mind waiting a while. In the here-and-now, though, both are equally baffling. You can’t tell how long you’d need to wait, because then that mystery wouldn’t be much of a mystery. Turning to holy texts isn’t much help, as I’ll outline in another chapter.

We’re stuck in something like the Prisoner’s Dilemma (see the Morality proof), with four possibilities:

It’s a Divine Gift

It’s a Solvable Mystery

Treat it as Divine

No problem!

You look like an idiot when it gets solved.

Treat it as Solvable

Either you’ll run into proof it’s divine, or it’ll perpetually be studied with no direct answer

No problem, plus you know more about the world!

If we treat this portion of intelligence as divine, we reach a dead end where we no longer study it in detail. You could argue this saves energy, since if we treat it as solvable when it really is divine we’d just grind our gears forever. That won’t happen; the process of evolution ensures all species have a certain level of curiosity, since a little exploration might lead to fertile new areas with no competition. Human beings will always search for answers, via science or some other means, no matter what the question actually is. Instead of saving energy, treating something as divine will simply shift our curiosity elsewhere, and have no net savings.

That assumes everyone treats that problem as divine, of course. If different religions have different ideas of divine, the off-limit topics will get studied anyway. In the case of intelligence and the brain, the Gelung Tibetan Buddhists are willing to give science a try:

In a final decision, the Society [for Neuroscience] will move forward with the Dalai Lama’s lecture at Neuroscience 2005 in Washington, DC, as planned. At its July meeting, the SfN Council expressed overwhelming support for proceeding with the Dalai Lama’s talk on “The Neuroscience of Meditation.”

(Fall 2005 Neuroscience Quarterly, official publication of the SfN)

My confidence in venturing into science lies in my basic belief that as in science, so in Buddhism, understanding the nature of reality is pursued by means of critical investigation. […] If scientific analysis were conclusively to demonstrate certain claims in Buddhism to be false, then we must accept the findings of science and abandon those claims.


(Tenzin Gyatso, the 14th Dalai Lama, leader of the Gelung Tibetan Buddhists)

Treating the components of intellect as solvable mysteries makes more sense, in every case.  Importantly, this reasoning can be used against any claim of a divine gift, not just intelligence. Examples of this include a designed universe (Fine-Tuning) or designed body (Teleological), moral guidance (Morality), or any Miracle.

Cogs in the Machine

But before I get further side-tracked and forget, we should return to memory.

I hope you noticed that some parts of intelligence seem to have little to do with intelligence. A good short-term memory is certainly helpful when solving problems, but only as a helper to some other form of processing. There’s otherwise little special about short-term memory, and it seems widespread across all life. Indeed, an experiment done by Keir G. Pearson[37] suggests that cats can remember a barrier they’ve seen for a few seconds after it goes out of view. Interestingly, if they also step over the barrier with their front legs, they will remember to step over with the back ones even after a ten-minute long distraction. Even goldfish, which urban legends claim have a memory lasting only a few seconds, can actually remember some things for a span of three months.[38]

Long-term memory has been studied to a ridiculous level. We know new permanent memories are formed by creating proteins which decrease the resistance to transmit signals between neurons. Memories are not stored in any single place, but seem to be tied to global patterns of brain activity. There’s an alphabet soup of receptors involved: NMDA, AMPA, CaMKII, PKC, and many more. The interactions between all of them are complicated, and this has kept scientists from understanding the full mechanics of it.

Still, it just doesn’t have the type of specialness that we’d attribute to the actions of a god. Why is that?

Part of the reason may be that it seems easy to expand. If we know, say, elephants can keep the current location of seventeen to thirty family members in their head,[39] we can easily picture another creature that can manage twice as many. That skill is a mere numbers game, and bumping up its capacity is probably as easy as enlarging some part of the brain.

However, I suspect the main reason is that it doesn’t seem mysterious. Decades of research have taken their toll, and even our limited knowledge of memory suggests there’s a good mechanistic explanation of the entire process out there.

Both reasons are variations on the same theme: if a machine can do it, it can’t be special. For instance, Gordon Bell estimates that he could archive all the books, photos, mail, and movies that a typical person encounters in a lifetime in about one terabyte of computer storage.[40] In comparison, I own a computer that can store four lifetimes, and I could add one more in exchange for a day’s wages. This computer can also do math much, much faster than I ever could, has a reaction time that makes mine look positively glacial, and can crunch through more data than my poor brain could ever hope to, all while making fewer mistakes and never getting tired.

This also applies to biology, as well. We understand how human arms and legs work in excellent detail, from the force absorbed by the skeletal structure to the conversion of ATP[41] into mechanical energy. While our artificial versions are not nearly as efficient or flexible, we have no reason to suspect that’ll be permanently true.

Thanks to this, we can cut out a few categories of intelligence. Memory gets chucked completely, as does processing speed, reaction time, and kinesthetic ability. I’ll also invoke the mechanical argument for visual and auditory processing, logic and mathematics, and spatial intelligence, though I want to go into more detail than can comfortably fit in this introduction.

Language

Language needs no introduction. You already know the power of language, because you’re decoding it right now. Without language, we would have no way to indicate we’re planning a big hunt tomorrow, describe the motions of the planets, or enjoy pictures of cats with captions added. Surely no other animal can claim to be nearly as advanced.

Unfortunately, we can’t be sure. We have not decoded the language used by elephants or whales, for instance, so entirely possible that they’re top of the heap. Whales in particular have access to one trick that we’ve only duplicated in the last few decades. They communicate with a series of clicks and yelps that can be heard from thousands of kilometres away. If you’re a fan of submarines, you might know about the “SOund Fixing And Ranging” channel. It’s a layer of water that acts much like an optical fibre; sound waves that enter it never leave, they just bounce around within the layer until they fade out, which can be the length of an entire ocean. We’ve spotted Humpback Whales taking advantage of this, so we know at least one species uses SOFAR on occasion.

It’s a staggering thought. For millions of years before us, whales had access to their own World Wide Web.

Elephant calls can carry pretty far themselves, thanks to their low frequency, but alas there is no SOFAR near the ground.[42] Like many other animals, though, elephants do have specific calls for specific instances. When elephants are menaced by bees, they’ll make a distinctive call that causes other elephants to take defensive measures. Lucy King, and others at Oxford, have tested this call by playing back several different versions of it to wild elephants. Altered calls didn’t result in head-shaking, used to keep bees away from the pachyderm’s face, or the tossing of trunk-fulls of dirt to keep bees from everything else.

Prairie dogs have an elaborate set of calls that warn not only what type of predator is approaching, but what size, shape, colour, and speed it has. All that is strung together in a basic grammar. Based on that information, prairie dogs can actually recognize the predator as an individual, and adapt their responses to it. Different colonies even have different accents, suggesting this chatter is a learned behaviour instead of hard-wired genetics.

C.N. Slohodchikoff wanted to confirm that, so he set up a simple experiment where plywood cutouts of a coyote, skunk, and an oval were randomly brought towards a dog colony. The warning call for the coyote was close to, but not quite the same, as the call for a normal coyote. All three received very different calls, even though two of them weren’t predators. That fact reinforces the theory that this “language” is learned; both the oval and skunk are novel situations, since skunks are nocturnal, so if alarm calls were hard-wired in via evolution you’d expect both calls to be similar.

Admittedly, this proto-language is nowhere near as complicated as ours. That doesn’t prove prairie dogs cannot develop a true language, only that they haven’t had the need to. The verbal skills of non-humans may be dormant, sleeping contentedly until some twist of fate forces them to develop.

Parrots, while ranked as one of the smartest birds to grace the skies, were considered too stupid for complex language. Their brains lack a folded structure called the cerebral cortex, which helps pack a ridiculous amount of neurons into a tiny area and was thought to be necessary for high-level intelligence. Humans, dolphins, and chimps all have this structure.

Irene Pepperberg disagreed, and decided to prove her point by picking up a random parrot from an ordinary pet shop, and trying to teach it our language.

Alex exceeded all expectations. He could recognize 150 words, including five shapes and seven colours, and could string them together in a sensible manner. One memorable day, he was presented with an apple for the first time and asked what it was. His response: “ban-erry.” While he didn’t know what an apple was, he knew about bananas and cherries. This strange fruit seemed to be a cross between the two of them, so he created an appropriate word on the fly.

Another time he was presented with a tray full of coloured blocks. When asked “What colour two?,” for instance, he would examine the tray, find that there were two red blocks, and answer “red.” After Irene had asked him about the “three” blocks several times, and Alex correctly responded with “blue” each time, he started replying “five” instead. Irene tried to coax the correct answer out of him, but eventually gave up in frustration and said “fine, what colour five?” Alex replied “none,” as there were no set of five blocks with the same colour.

He wasn’t confused, merely bored with the exercise, and was acting up like a human child would do in the same situation.

Alex would apologize if he ticked off one of the researchers, though he was never taught this. When he got bored of testing, he would ask to be put back into his cage; again, he was never taught that. He was taught the difference between “I” and “You,” to retrieve any number of any type of object from a tray, and as shown above understood the concept of “none.” He understood relations between objects, like “different” or “smaller.” He sometimes practised his lessons on his own, yet never saw any-one or -thing doing the same, and would help the researchers train other parrots, even though he was never taught to.

Pepperberg estimates he was as intelligent as a five-year old human, or the smartest dolphins and gorillas.

And speaking of primates: recent research by Catherine Hobaiter and others at the University of St. Andrews have shown that wild chimps can communicate with at least sixty-six different gestures.[43] It’s a good reminder that there are more ways to speak than through sound.

[38] http://www.plymouth.ac.uk/pages/view.asp?page=7705

[39] According to a study by Richard Byrne published in Biology Letters, DOI:10.1098/sbl.2007.0529

[40] http://totalrecallbook.com/about-the-authors/

[41] Adenosine-5′-triphosphate, the molecule all Earth life runs on. A human being consumes its body weight of the stuff in a single day!

[42]  A similar layer of air might exist at higher altitudes. A top-secret research project that would have confirmed this was cancelled, unfortunately, but not before one of their test balloons made a big splash near Roswell, New Mexico.

[43]  http://news.bbc.co.uk/earth/hi/earth_news/newsid_9475000/9475408.stm