Cross-disciplinary cross-talk.

So, who’s heard about the science wars?

While the wiki article makes it sound as though the conflict arose and faded during the 1990s, the same clashes continue in a more subdued manner. I think the decline has been partly due to the usual short public attention span; the attempts of scientists and non-science academics to bridge gaps and create demarcations; and the increased tendency for reactionaries to appropriate the language of critical theory to attack ideas cherished by both sides of the science wars.

It’s the second of these that I’d like to address, the attempts or failures of scientists and academics (shorthand for non-scientist academics) to understand what each other is saying, to understand how each side conducts their research, to understand the language used by each side, and to demarcate areas as scientific or non-scientific. Please bear in mind that anything I’m writing comes from the point-of-view of a scientist, who while they’ve been exposed to enough academic language and concepts to have some idea of what’s going on, is still a scientist.

Part of the problem, I feel, is political. Particularly in the USA, but also generally, the ability of science to answer questions and better society is frequently ignored or even called into question. This can be trivially seen in the modern rise of the anti-vaccination movement, and widespread doubt about medical science in general; the denial of the theory of evolution, often in favour of creationist ideas; and the denial of environmental problems, from population growth, to pollution in general, to greenhouse gas emissions and climate change.

Thus, scientists are often reflexively dismissive or wary of challenges to existing theories from outside of science. Science is very hard. Any modern field requires a lot of background knowledge to even understand what is being discussed, let alone to conduct one’s own experiments or research. It is not like 18th or 19th century science anymore – in the past five or six decades, scientific knowledge has expanded so rapidly that it is not really possible to conduct it as an interested hobbyist or outsider. And the challenges often betray a certain ignorance on the part of the challenger. I attended a conference on science and art, and one of the presenters was speaking about a project her group was planning, using EEG, blood pressure and heart-rate monitors, and other bio-recording devices. These would be turned on or off to create recordings during her students’ daily life, to record their physiology along with their memory.

The entire presentation put everyone’s backs up. For one, she talked about how EEG can ‘supposedly’ measure ‘brain waves’ which apparently ‘change’ during the day, and made light of the ability of anyone to ‘know’ this, or to know that what EEG measures reflects anything of what’s actually going on. But – EEG has been used for decades. Unlike, say, fMRI both EEG and what it’s measuring are quite well understood. The fact that EEG measures frequency and temporal changes in regional neuronal firing is trivial. But her words made it clear that she had never read any literature on the tools she was planning on using, and had no idea of how they were used in science. But the whole idea of the project was intended to critique how science uses its measuring tools. Secondly, many people in the audience looked at her project less as art, and more as an experiment. If one is critiquing the tools and measurements of science, one conducts experiments. But there was no protocol, no controls, no measures set for this project. And we didn’t get it.

It took a sympathetic artist in the crowd, a younger one who worked closely with scientists, to explain to us that this project was not an experiment, was not setting out to disprove anything. That the project simply looked at how we represent data, in the way that artists must make decisions when colouring telescopic photographs of nebulae or diagrams of the brain. Art and science are intertwined in how scientists represent their data, and this project was examining that.

And that’s pretty cool.

But both sides, mostly, didn’t understand anything about what the other was saying. The scientists were exasperated over the ignorance of the artists, and the artists were annoyed at the scientists’ obstinate refusal to understand that their project wasn’t addressing any truth claims.

Part of it, as you can see, is the language used. ‘Critique’ means something very different in science than it does in art. It’s synonymous with criticism, with attacking the way someone has conducted their research or reached their conclusions. In art, it is more of a discussion, a way of examining the artist’s and society’s perspective on a thing.

And part of it is just what people are studying, and what things are amenable to certain kinds of investigation. As you might have heard, the American Anthropological Association removed the word “science” from their long-range plans. This has caused something of a kerfuffle.

The above post, and particularly the discussion, are perfectly representative of what I’m talking about. One side calls the other side “positivists”, as though positivism has had much place in science since the 1960s. However, that all defines how you define positivism. As you can see by skimming down through that wiki article, while most scientists today are falsificationists, following a general view of things as set forth by Karl Popper and Imre Lakatos. But positivism, meaning supporting the scientific method as the best way of answering questions, is still present.

Anyways. One of the commentators I thought was particularly good was someone going by “Sam”. One of their comments included this paragraph:

“As an anthropologist I would probably not be interested in testing a proposition of the order ‘does coffee increase concentration?’. Rather, for me the question would be ‘what do people believe about coffee?, ‘what are the consequences of this belief?’ ‘how does this belief manifest? Do people believe this all the time? . So yes, we are concerned abut validity and truth in our accounts of the world but usually not in assessing the truthfulness of the claims of the people we investigate (not because the latter is not important but because we have other, still compelling, concerns).”

See, that sort of thing helps. A lot of the time it’s hard for people in science to understand how someone might not see the scientific method as a necessary part of any research. But in the case above, one’s procedure of investigation need not be scientific in the sense of hypothesis-testing through experimentation. History and anthropology both resemble traditional natural sciences in that they proceed largely through observation and inquiry, and cannot be directly tested.

Scientists get a bit twitchy because, for instance, modern methods of anthropology often seem to take a step further. Rather than just acknowledging a demarcation, some people do seem to insist that “science” is simply one of many epistemologies, culturally Western, and no more valid for making claims about the world than any other “ways of knowing.” Obviously I disagree – but it’s hard for scientists to wrap their heads around the difference between “valid” and “correct”. Something which is valid is true from one person’s perspective, regardless of the purely historical facts of the matter. As to something being “correct”, well, that’s tricky.

I’m getting a bit far afield here, so I’ll finish up.

What I think we need, and by “we” I mean intellectuals, academics, and others involved in knowledge-based careers, is people who can speak across disciplines. Artists who are into science, scientists with friends involved in critical theory, anthropolgists who work with doctors, and pyschologists who study philosophy on the side.

Well, maybe not that last. That often seems to lead to trouble. But you get the idea.

The Measure of a Man

So, AI.

I’m going to be a sadly stereotypical geek and start off with a Star Trek reference. In my defence, I’ve only just started watching it, and will be moving onto the 3rd season as soon as I find a cheap / free way to get it that doesn’t involve hours upon hours of downloading.

In an episode in the second season, a Federation scientist requisitions Data (an android, essentially a unique being) with the plan of uploading Data’s data to another computer and then slowly deconstructing his positronic brain to fill in the gaps in his research.

There was a lot to like in this episode. Unlike a lot of the knee-jerk anti-technology/science attitudes in the show (which are always pretty jarring), Data doesn’t object to this in principal. Rather, he feels that the scientist’s research is not sufficiently advanced to ensure that Data’s consciousness will be preserved intact. A legitimate concern, I’m sure you’ll agree.

Eventually we get to the meat of the episode. Data is essentially requisitioned by the scientist, and a trial ensues to determine whether Data is Federation property, or if he is an independent being.

The good stuff continues. Riker is assigned to the prosecution, and executes a fairly emotional attack on Data by switching him off, playing up Data’s existence as a machine. The best part of the episode comes when Picard acts as the defense.

“Commander Riker has dramatically demonstrated to this court that Lieutenant Commander Data is a machine. Do we deny that? No, because it is not relevant – we too are machines, just machines of a different type.”

An excellent line. Picard further demands to know the scientist’s criteria for a sentient being. The scientist seems rather caught off-guard, a bit surprising given that anyone remotely involved in AI research gets caught up in questions of consciousness and sentience. He ends up defining sentience as self-awareness, intelligence, and consciousness.

Now, right there we have a problem. All three criteria over-lap quite a bit. Self-awareness in a basic sense is easy – as machines that have to move about and do things, both Data and humans are aware that they are beings distinct from their surroundings. In different sense, both types of machines are also capable of some degree of introspection or self-monitoring. This is a key evolutionary feature, as it allows one to judge internal changes due to external stimuli, and then to make compensatory changes.

Intelligence is even harder. The debate over just what it is, if there is one measure of several independent types of intelligence, and how to measure it has gone on pretty much since the word was first used in the modern sense. Intelligence tests at one point were almost trivia or general knowledge tests, and you lost IQ points for not knowing the name of US legislative bodies, or the years of the first world war. These days IQ tests rely much more on abstract reasoning, pattern recognition, and that sort of thing, but the debates continue (rightly, to my mind). I’d say intelligence as a criterion for sentience is pretty much useless, especially across species boundaries (in a setting where there are multiple ‘civilizations’ of different species).

Still, the episode once again uses a fairly trivial definition of ‘intelligence’, and Data rattles off some math and facts to mislead the viewing public as to just what makes people ‘smart’.

Now we come to the meat of the question. Consciousness. Now, anyone with even a passing familiarity with philosophy, AI, neuroscience, psychology, etc knows there is basically zero consensus about consciousness.

Can we measure it? Can we accurately report it? Which phenomena count as ‘conscious’, and which count as ‘unconscious’? Where is it located? Are animals conscious (or are the just intelligent)?

Picard goes back to one of my favourite arguments, functionalist that I am. He asks the scientist if he, Picard, is conscious. The scientist replies in the affirmative. He then asks the scientist to prove it. This puts the scientist in a bit of a bind, since Data is pretty clearly able to pass a Turing test. After all, he only lacks a bit of vocal intonation and knowledge of common social interaction, which are also found among humans.

This all leads to a huge facepalm on my part, as the adjudicator exclaims that the entire trial is to see if Data has a soul. Which makes me think that either the writer’s didn’t understand anything they’d written for the entire rest of the episode, or that they felt they had to dumb it down for the audience. Star Trek’s vitalistic tendencies are a whole other issue, though. You’d also think the Federation would have guidelines for dealing with any machine races they ran into, but no. It seems centuries of theorizing about full AI somehow never penetrated the Federation’s policy structure.

Well, this has ended up being more of an episode review than the essay on AI I’d intended. Clearly I’ll need to revisit the subject.

The take-home messages here: when defining your terms, don’t paint yourself into a corner. And don’t try to designate something as non-sentient that is able to carry on lengthy, unscripted conversations. We’ve already covered that. I wonder if we could call this the ‘Turing Trap’.

Non-manifest truth, induction, and theories

Last week I wrote about the idea that truth is manifest, obvious to those who look without prejudice.  Several things come of this, including the conspiracy theory of ignorance, and the idea that others who disagree with what you claim to be true are in some way sinful, prejudiced, or mislead.

It also leads to the idea of science via induction.  Popper’s opposition to this idea is one of the main features of his philosophy of science, and I’ve not yet found a reason to disagree with him.

Induction proceeds like this: I see things occurring in the world.  For example, I might see a white sheep.  Eventually, I will observe many white sheep.  Therefore, as a general rule, sheep are white.  Every white sheep I see ‘verifies’ my theory of the whiteness of sheep.  Observations, he argues, cannot have any value except in light of a pre-existing theory, even if the theories are ‘sheep wool has colours’, ‘white is a colour found with sheep’.  Rather, what we start from is a theory – ‘sheep are white’ – and then proceed to test that theory via observation.

I’ll try to return to this question of induction vs. deduction via theory more, because I think it is very important.

Truly scientific theories, according to Popper, are not formulated by observing the self-evident truth of things.  Instead, theories are first formulated based on prior theories, which have either been refuted or not.  Falsifiability, whereby a theory can be refuted, is a necessary component of any scientific theory, according to Popper.  We cannot support our case through bulk of observation (where would our cut-offs be for the number of necessary observation?) but must instead attempt to refute our theory.  Theories which have survived many strict tests are then to be considered better approximations of the truth than ones which have been tested less rigorously.

I’ll finish by describing some conclusions Popper has drawn regarding scientific theories.

1. It is easy to confirm or verify theories by observation, when we look for confirmations.  If you’ve ever heard of confirmation bias, then you will understand why that is.

2. Confirmations count only if they result from risky predictions.  If your observations run counter to what you would have expected before formulating your theory, so that you expected to find a result which would have been impossible in light of your theory, they can be said to ‘confirm’ the theory.

3. Every valid scientific theory is prohibitory.  The theory should lay out things that cannot happen if the theory is correct.  And the more things the theory forbids, the better.  A very general theory, under which many things are possible, is not as testable as one which greatly restricts possible events.  This is similar to the idea that it is easier to make a list of objects which aren’t in a closed box than to make a list of the items which could be in the box.

4. A theory which cannot be refuted in any way is not a scientific theory.  Irrefutability is a weakness, not a strength, because a theory which is correct no matter your potential findings is meaningless, because it either prohibits everything or nothing.

5. Every sincere test of a theory is one which attempts to falsify or refute the theory.  Testability is a measure of falsifiability.  Not all theories are equally testable – ones which are more exposed to refutation, which are ‘riskier’, are more valuable if we find ourselves unable to refute them.

6. Confirming or corroborating evidence is only valid if it results from a serious attempt to falsify the theory.  A theory which survives multiple attempts to refute it can be said to be confirmed or corroborated by the evidence.

7. Theories can be modified post hoc to accommodate a refutation of part of that theory, but this lowers the theory’s value as it is no longer as prohibitory as before.

This last point is sharply debated, especially by Thomas Kuhn.  When I get through Popper and have some time to tackle his major book, I’ll try to address some of their disputes.

Human demarcation

I’m wrestling with a post on Popper and manifest truth, but in the meantime, some thoughts on drawing species lines.

What came first, the chicken or the egg? I read an answer somewhere which was quite good – ‘a slightly different egg.’ The first hen, you see, would not have been recognized as such. This is because you cannot point to a single animal and say ‘See? That’s the first chicken.’ Individuals do not evolve, and they do not found whole species. Eve is a myth. (The case of the modern domestic chicken (Gallus gallus domesticus) is a bit confused, as it might have come about due to deliberate cross-breeding between related species, so let’s just say ‘chicken’ to denote a generic bird of a definite species.)

In fact, new species are almost entirely noted in retrospect, when you can say ‘This chicken descended from this chicken-like ancestor.’ The ancestor is not a chicken, and likely cannot breed with modern chickens (an sufficient but not necessary aspect of a distinct species). Many proto-chickens likely bore young which were very similar to modern chickens, many of which bore young which were even more similar to modern chickens, until eventually without realizing it you have ancestral chickens and modern chickens, and aren’t quite sure when in the last hundred/thousand/more years it happened.

This is entirely the same with humans.

An amusing pastime is watching ‘creation scientists’ try to demarcate archaeological finds of hominid (Hominidae refers to all of the great apes, including Homo sapiens) as either ape or human. By ignoring the various gradations, and the fact that any shift from ‘more ape’ to ‘more human’ is obvious only because the fragmentary nature of the fossil record gives us snapshots rather than a continuous view of hominid evolution. This game can be played all across the internet (and in real life), but some good examples of it in play are here, here, and here.

What is human, and what is not, are not clear distinctions. At the risk of digging myself a deeper hole that I can write myself out of in the next year or so, I plan to return to this concept, that in science while there are categories they are non-rigid categories. Something similar applies to sex and gender, but that’s whole other kettle of fish.

But – since this was on my mind today – how do you draw the distinction between human and cyborg? I know this might seem something of a non-sequitor, but it’s something of great interest to me. I and many of my friends read sci-fi, and have played games, in which the characters are part-human and part-machine. These media typically assume that as you add artificial limbs or functions you become less human.

Are we less human now? Because much of the speculation in the books revolves around things we already possess and do. Artificial eyes? (We have them). Are they somehow different than looking through a camera with your own eyes, aside from considerations of rejection or infection? Does wearing night-vision goggles make you a cyborg? How about surgically implanted memory storage? It’s no different than storing information on a computer, which becomes an accessory to your memory function. Computers in fact make much of this debate possible, as for many people in developed countries they are a daily necessity for their jobs. If I lose a tooth and have it replaced by a plastic tooth, am I a cyborg? What if I receive a hip replacement? An artificial leg?

At what point am I no longer human? The answer, I think, is so long as my brain is intact I will remain human, for all intents and purposes – or at least enough of one to pass a Turing test.