On animals that speak, including humans.

On animals that speak, including humans.

Prairie-DogsWhen prairie dogs speak, they seem to use nouns – hawk, human, wooden cut-out – adjectives – red, blue – and adverbs – moving quickly, slowly.  They might use other parts of speech as well.  Prairie dogs chitter at each other constantly, making many sounds that no humans have yet decoded.

Ever wonder about the evolutionary origin of human intelligence?  The leading theory is that, over many generations, our ancestors became brilliant … in order to gossip better.  It takes a lot of working memory to keep track of the plot of a good soap opera, and our ancestors’ lives were soap operas.  But Carl knows that Shelly doesn’t know that Terrance and Uma are sleeping together, so …

Tool use is pretty cool.  So’s a symbolic understanding of the world – who doesn’t love cave art?  But gossip probably made us who we are.  All those juicy stories begged for a language to be shared.

Many types of birds, such as parrots and crows, spend their lives gossiping.  These busybodies also happen to be some of the smartest species (according to human metrics).  Each seems to have a unique name – through speech, the birds can reference particular individuals.  They clearly remember and can probably describe past events.  Crows can learn about dangerous humans from their fellows.

When I walk around town, squirrels sometimes tsk angrily at me.  But I’ve definitively observed only a single species using its capacity for speech to denounce all other animals.  From Tom Wolfe’s The Kingdom of Speech:

9780316404624_custom-3522b1f2a1f684ab94261905a4d4c9ddf86ca882-s400-c85There is a cardinal distinction between man and animal, a sheerly dividing line as abrupt and immovable as a cliff: namely, speech.

Without speech the human beast couldn’t have created any other artifacts, not the crudest club or the simplest hoe, not the wheel or the Atlas rocket, not dance, not music, not even hummed tunes, in fact not tunes at all, not even drumbeats, not rhythm of any kind, not even keeping time with his hands.

This claim is obviously false.  Several different species do create artifacts – either speech is unnecessary for this task, or else other species of animals can speak.  Or both.  In any case, this claim is so easily rebutted – all you’d need is an example of chimpanzees drumming, let along cooking – that it seems a strange conclusion for Wolfe to make.

Don’t get me wrong: humans are pretty great at thinking.  I’m more impressed by mathematical than emotional intelligence, which makes it easy for me to think that the average human is way brighter than the average elephant.

In all likelihood, though, humans have been pretty great at thinking for hundreds of thousands of years.  The cultural evolution that produced the Atlas rocket and skyscrapers was a very sudden development.  For most of the time that humans have been on the planet, our behavior probably didn’t look so different from the behavior of orcas, chimps, or parrots.

Throughout The Kingdom of Speech, Wolfe mocks the various theories about human language presented by Noam Chomsky.  (I’m ignoring Wolfe’s claims about evolution, which he says can’t be tested, replicated, or used to elucidate otherwise inexplicable phenomena – in his words, “sincere, but sheer, literature.”  Here and here are two of many recent experiments tracking evolution in progress.)

tom-wolfe-400I often found myself nodding in agreement with Wolfe.  For instance, I’d hope that a linguist making broad claims about human language would learn as many languages as possible.  I think that contradictory evidence from the real world holds more weight than pretty theories.  From Wolfe’s Kingdom of Speech:

In the heading of the [2007 New Yorker] article [“The Interpreter: Has a Remote Amazonian Tribe Upended Our Understanding of Language?”] was a photograph, reprinted many times since, of [Dan] Everett submerged up to his neck in the Maici River.  Only his smiling face is visible.  Right near him but above him is a thirty-five-or-so-year-old Piraha sitting in a canoe in his gym shorts.  It became the image that distinguished Everett from Chomsky.  Immersed! – up to his very neck, Everett is … immersed in the lives of a tribe of hitherto unknown na – er – indigenous peoples in the Amazon’s uncivilized northwest.  No linguist could help but contrast that with everybody’s mental picture of Chomsky sitting up high, very high, in an armchair in an air-conditioned office at MIT, spic-and-span … he never looks down, only inward.  He never leaves the building except to go to the airport to fly to other campuses to receive honorary degrees … more than forty at last count … and remain unmuddied by the Maici or any of the other muck of life down below.

But Chomsky being wrong doesn’t make Wolfe right.

9780262533492In Why Only Us, authors Robert Berwick and Noam Chomsky make some suspicious claims.  They argue that human language stems from an innate neurological process that they’ve dubbed “merge,” akin to the combination of two sets to produce a single, indivisible result.  {A} merged to {B} yields {C}, where {C} contains all the elements of {A} and {B}.

This sounds pretty abstract, so an example might help.  Berwick & Chomsky think that a verb and a direct object would be combined into a single “verb phrase” that is treated as a single unit by our brain.  Or, even more complexly, the word “that” leading into a subordinate clause would produce a whole slew of words that is treated as a single unit by our brain.  (In the preceding sentence, the phrase “that is treated as a single unit by our brain” would be one object.)

Robert C. Berwick and Noam ChomskyBerwick & Chomsky’s idea is that complex sentences can be built either by listing the final units in a row or using that hierarchical “merge” operation again, i.e. putting a verb phrase inside a subordinate clause, or one subordinate clause inside another.  Leading eventually to the tangled, twisty syntax of Marcel Proust.

But as far as I could tell (their book has a lot of jargon, and I read it while walking laps of the YMCA track with a sleeping baby strapped to my chest, so it’s possible I missed something), they don’t discuss the difference between two ideas being placed at the same level of interpretation, such as two independent clauses joined by an “and” or “or,” versus a dependent clause adjoined to an independent clause with “but,” “which,” “that,” or what have you.  I couldn’t identify a feature of their argument that suggested why some adjacent words would be processed by a human brain is this special way but others would not.  I could certainly address the way this happens in English, but an evolutionary argument ought to apply to all human language, and I know so little about most others that my opinions seem unhelpful here.

Some of Berwick & Chomsky’s ideas don’t seem to hold even in English, though.  For instance, they claim that:

there is no room in this picture for any precursors to language – say a language-like system with only short sentences.  There is no rationale for positing such a system: to go from seven-word sentences to the discrete infinity of human language requires emergence of the same recursive procedure as to go from zero to infinity, and there is of course no direct evidence for such “protolanguages.”  Similar observations hold for language acquisition, despite appearances, a matter that we put to the side here.

But we’re very confidant that spoken language arose long before written language, and the process they describe isn’t how many humans interact with spoken language.  There are definite limits to how many clauses most people can keep in mind at any one time – indeed, much of Why Only Us would sound incomprehensible if read aloud.

Is it reasonable to compare human written language with the spoken language of other animals?  The former is decidedly more complex.  Sure.  But the language actually used by most humans, most of the time, seems much simpler.

When I write, I can strangle syntax as well as any other pedant.  But when I actually talk with people, most of what I say is pretty straightforward.  I get confused if somebody says something to me with too many embedded clauses, or if words intended to operate together on a “structural” level aren’t in close proximity – Berwick & Chomsky spend a while writing about the phrase “instinctively birds that fly swim,” which sounds like gibberish to me.  Just say either “birds that fly instinctively can swim” or “birds that fly can swim instinctively” and you won’t get as many funny looks.  Except for the fact that I don’t think this is true, in either phrasing.  Syntactically, though, you’d be all set!

Colorful_Parrots_CoupleIn any case, all you’d need to show to demonstrate a linguistically equivalent behavior in other animals would be two parrots discussing the beliefs of a third.  This would be the same recursion that Berwick & Chomsky claim produces the “infinity of human language.”

Given that other social animals understand the (false) beliefs of their compatriots, I’d be shocked if they didn’t talk about it.  We just haven’t learned how to listen.

Humans are great.  We’ve accomplished a lot, especially in these last few thousand years (which is incredibly fast compared to evolutionary timescales).  The world has changed even in the short time that I’ve been alive.  But the unfounded claims in both The Kingdom of Speech and Why Only Us made me feel sad: with so much to be proud of, why should we humans also strive to distinguish ourselves with supremacist arrogance?

On perception and learning.

On perception and learning.

Cuddly.

Fearful.

Monstrous.

Peering with the unwavering focus of a watchful overlord.

A cat could seem to be many different things, and Brendan Wenzel’s recent picture book They All Saw a Cat conveys these vagrancies of perception beautifully. Though we share the world, we all see and hear and taste it differently. Each creature’s mind filters a torrential influx of information into manageable experience; we all filter the world differently.

They All Saw a Cat ends with a composite image. We see the various components that were focused on by each of the other animals, amalgamated into something approaching “cat-ness.” A human child noticed the cat’s soft fur, a mouse noticed its sharp claws, a fox noticed its swift speed, a bird noticed that it can’t fly.

All these properties are essential descriptors, but so much is blurred away by our minds. When I look at a domesticated cat, I tend to forget about the sharp claws and teeth. I certainly don’t remark on its lack of flight – being landbound myself, this seems perfectly ordinary to me. To be ensnared by gravity only seems strange from the perspective of a bird.

theyallsawThere is another way of developing the concept of “cat-ness,” though. Instead of compiling many creatures’ perceptions of a single cat, we could consider a single perceptive entity’s response to many specimens. How, for instance, do our brains learn to recognize cats?

When a friend (who teaches upper-level philosophy) and I were talking about Ludwig Wittgenstein’s Philosophical Investigations, I mentioned that I felt many of the aims of that book could be accomplished with a description of principal component analysis paired with Gideon Lewis-Kraus’s lovely New York Times Magazine article on Google Translate.

My friend looked at me with a mix of puzzlement and pity and said, “No.” Then added, as regards Philosophical Investigations, “You read it too fast.”

wittgensteinOne of Wittgenstein’s aims is to show how humans can learn to use language… which is complicated by the fact that, in my friend’s words, “Any group of objects will share more than one commonality.” He posits that no matter how many red objects you point to, they’ll always share properties other than red-ness in common.

Or cats… when you’re teaching a child how to speak and point out many cats, will they have properties other than cat-ness in common?

In some ways, I agree. After all, I think the boundaries between species are porous. I don’t think there is a set of rules that could be used to determine whether a creature qualifies for personhood, so it’d be a bit silly if I also claimed that cat-ness could be clearly defined.

But when I point and say “That’s a cat!”, chances are that you’ll think so too. Even if no one had ever taught us what cats are, most people in the United States have seen enough of them to think “All those furry, four-legged, swivel-tailed, pointy-eared, pouncing things were probably the same type of creature!”

Even a computer can pick out these commonalities. When we learn about the world, we have a huge quantity of sensory data to draw upon – cats make those noises, they look like that when they find a sunny patch of grass to lie in, they look like that when they don’t want me to pet them – but a computer can learn to identify cat-ness using nothing more than grainy stills from Youtube.

Quoc Le et al. fed a few million images from Youtube videos to a computer algorithm that was searching for commonalities between the pictures. Even though the algorithm was given no hints as to the nature of the videos, it learned that many shared an emphasis on oblong shapes with triangles on top… cat faces. Indeed, when Le et al. made a visualization of the patterns that were causing their algorithm to cluster these particular videos together, we can recognize a cat in that blur of pixels.

The computer learns in a way vaguely analogous to the formation of social cliques in a middle school cafeteria. Each kid is a beautiful and unique snowflake, sure, but there are certain properties that cause them to cluster together: the sporty ones, the bookish ones, the D&D kids. For a neural network, each individual is only distinguished by voting “yes” or “no,” but you can cluster the individuals who tend to vote “yes” at the same time. For a small grid of black and white pixels, some individuals will be assigned to the pixels and vote “yes” only when their pixels are white… but others will watch the votes of those first responders and vote “yes” if they see a long line of “yes” votes in the top quadrants, perhaps… and others could watch those votes, allowing for layers upon layers of complexity in analysis.

three-body-problem-by-cixin-liu-616x975And I should mention that I feel indebted to Liu Cixin’s sci-fi novel The Three-Body Problem for thinking to humanize a computer algorithm this way. Liu includes a lovely description of a human motherboard, with triads of trained soldiers hoisting red or green flags forming each logic gate.

In the end, the algorithm developed by Le et al. clustered only 75% of the frames from Youtube cat videos together – it could recognize many of these as being somehow similar, but it was worse at identifying cat-ness than the average human child. But it’s pretty easy to realize why: after all, Le et al. titled their paper “Building high-level features using large scale unsupervised learning.”

Proceedings of the International Conference on Machine Learning 2010
You might have to squint, but there’s a cat here. Or so says their algorithm.

When Wittgenstein writes about someone watching builders – one person calls out “Slab!”, the other brings a large flat rock – he is also considering unsupervised learning. And so it is easy for Wittgenstein to imagine that the watcher, even after exclaiming “Now I’ve got it!”, could be stymied by a situation that went beyond the training.

Many human cultures have utilized unsupervised learning as a major component of childrearing – kids are expected to watch their elders and puzzle out on their own how to do everything in life – but this potential inflexibility that Wittgenstein alludes to underlies David Lancy’s advice in The Anthropology of Childhood that children will fair best in our modern world when they have someone guiding their education and development.

Unsupervised learning may be sufficient to prepare children for life in an agrarian village. Unsupervised learning is sufficient for chimpanzees learning how to crack nuts. And unsupervised learning is sufficient to for a computer to develop an idea about what cats are.

But the best human learning employs the scientific method – purposefully seeking out “no.”

I assume most children reflexively follow the scientific method – my daughter started shortly after her first birthday. I was teaching her about animals, and we started with dogs. At first, she pointed primarily to creatures that looked like her Uncle Max. Big, brown, four-legged, slobbery.

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Good dog.

Eventually she started pointing to creatures that looked slightly different: white dogs, black dogs, small dogs, quiet dogs. And then the scientific method kicked in.

She’d point to a non-dog, emphatically claiming it to be a dog as well. And then I’d explain why her choice wasn’t a dog. What features cause an object to be excluded from the set of correct answers?

Eventually she caught on.

Many adults, sadly, are worse at this style of thinking than children. As we grow, it becomes more pressing to seem competent. We adults want our guesses to be right – we want to hear yes all the time – which makes it harder to learn.

The New York Times recently presented a clever demonstration of this. They showed a series of numbers that follow a rule, let readers type in new numbers to see if their guesses also followed the rule, and asked for readers to describe what the rule was.

A scientist would approach this type of puzzle by guessing a rule and then plugging in numbers that don’t follow it – nothing is ever really proven in science, but we validate theories by designing experiments that should tell us “no” if our theory is wrong. Only theories that all “falsifiable” fall under the purvey of science. And the best fields of science devote considerable resources to seeking out opportunities to prove ourselves wrong.

But many adults, wanting to seem smart all the time, fear mistakes. When that New York Times puzzle was made public, 80% of readers proposed a rule without ever hearing that a set of numbers didn’t follow it.

Wittgenstein’s watcher can’t really learn what “Slab!” means until perversely hauling over some other type of rock and being told, “no.”

We adults can’t fix the world until we learn from children that it’s okay to look ignorant sometimes. It’s okay to be wrong – just say “sorry” and “I’ll try to do better next time.”

Otherwise we’re stuck digging in our heels and arguing for things we should know to be ridiculous.

It doesn’t hurt so bad. Watch: nope, that one’s not a cat.

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Photo by John Mason on Flickr.