One of the reasons I’ve started this series of posts is because I have a huge respect for the scientific method – in fact, I’d go so far as to say that I think the scientific method is the only means we have of actually knowing anything about the world, or indeed anything at all – but I think that even many other people who claim to believe science to be important don’t fully understand how it works. I also think that many of the people who do know how the scientific method works are not fully aware of the implications of this.

This is not to say, of course, that I am an authority or an expert – in fact, questioning authority and experts is one of the things that defines the scientific method – but it does mean that I’ve thought about this stuff a lot, and might have something worthwhile to say.

To start with, let’s look at what the scientific method isn’t. When I talk about the scientific method here I’m talking about what is, in effect, a Platonic ideal version of science. Science as it is actually practiced has all sorts of baggage that comes with being a human being, or with working in a university environment. Try and imagine here that I am talking about the things that a hypothetical alien race’s science would have in common with ours.

The most important thing for us to note as being unnecessary for science is peer review. That’s not to say peer review is a bad thing – in fact it can be a very good thing, a way to separate out crackpottery from real science, and more importantly a way to discover what your embarassing mistakes are before you become committed to believing in them – but it’s not necessary for doing science. That can be shown rather easily by the fact that neither Newton’s Principia or Darwin’s On The Origin Of Species were peer-reviewed, but it would be hard to argue that Newton and Darwin weren’t scientists.

More importantly, there’s some evidence that peer review actually doesn’t do any better at telling good science from bad than choosing at random. I have some problems with the methodology of that study (I think meta-analyses are, if anything, actively bad science rather than just being neutral as peer review is), but other studies have shown that in fact the majority of published studies in peer-reviewed journals are likely to be false.

So if I’m not talking about science-as-it-is-practiced, with all its flaws and human errors, what am I talking about? What is the core of the scientific method?

Well, the first, and most important, part is feedback.

Feedback may be the single most important concept in science – so much so that it’s been reinvented under different names in several different disciplines. Feedback is the name it’s given in cybernetics – the science of control systems, which is what I’m most familliar with – and in information theory and engineering. In computer programming it’s known as recursion. In biology it’s known as evolution by natural selection. And in mathematics it’s called iteration. All of these are the same concept.

Feedback is what happens when the output of a system is used as one of the inputs (or the only input) of that system. So musicians will know that if you prop an electric guitar up against an amp, or have your microphone too near a speaker, you quickly get a high-pitched whining tone. That’s because the tone from the speaker is going into the guitar’s pickups, or into the mic, in such a way that the low frequencies cancel out while the high frequencies add up. The sound goes straight out of the speaker and back into the pickup or mic, and can quickly become overwhelmingly loud.

That’s what we call ‘positive feedback’. Positive feedback leads to exponential growth very quickly – in fact it’s pretty much always the cause of exponential growth. We can see how easily this happens using a computer program:

#!/usr/bin/perl

$myNumber = 2;

while ( $myNumber > 0 ) {

print $myNumber. ” “;
$myNumber *= $myNumber;

#This says that as long as myNumber is greater than
#0 – which it always is – the program should
#multiply it by itself, after printing it to the
#screen.

}

This program starts with the number two, multiplies it by itself, and then takes the number it gets and uses that as its input, multiplying it by itself. When I ran this program on my computer, the numbers got so big that the computer couldn’t cope with them before I had a chance to blink – it just kept saying the answer was infinity. The first few outputs, though, were 2, 4, 16, 256, 65536, 4294967296, 1.84467440737096 x 10^19. That last number is roughly a two with nineteen noughts following it, for those of you who don’t know exponential notation.

So positive feedback can make things change a huge amount very, very quickly. So what does negative feedback do?

Negative feedback does the opposite, of course, which means that it keeps things the same. The easiest example of negative feedback at work I can think of is a thermostat. A thermostat is set for a temperature – say eighteen degrees – and controls a heating and a cooling device. When the temperature hits nineteen degrees, it turns the heater off and the cooler on, and when it hits seventeen it turns the cooler off and the heater on. Again, the output (the temperature) is being used as the input, but this time the output does the opposite of what the input is doing – if the input moves up the output moves down – and so it keeps it steady.

Negative feedback is used in all control systems, because negative feedback looks just like an intelligence trying to find a particular goal. That’s because it is how intelligent agents (like people) try to get to their goals.

Imagine you’re driving a car – the input is what you see through the windscreen, while the output is the way your hands turn the steering wheel. You want to go in a straight line, but you see that the car is veering to the left – as a result, you turn the steering wheel slightly to the right. If it veers to the right, you turn the steering wheel to the left. If you’re a good driver, this feedback becomes almost automatic and you do this in a series of almost imperceptible adjustments. (If you’re me, you veer wildly all over the road and your driving instructor quits in fear for his life).

So what happens when you put positive and negative feedback together? The answer is you get evolution by natural selection.

A lot of people, for some reason, seem to have difficulty grasping the idea of evolution (and not just religious fundamentalists, either). Evolution by natural selection is actually a stunningly simple idea – if you get something that copies itself (like an amoeba, or a plant, or a person), eventually you’ll get tons of copies of it all over the place – positive feedback. But things that copy themselves need resources – like food and water – in order to make more copies. If there aren’t enough resources for everything, then some of them will die (negative feedback from the environment – the environment ‘saying’ “OK, we’ve got enough of you little replicators now”).

Only the ones that live will be able to make more copies of themselves, so if some of the copies are slightly different (giraffes with longer necks, or people who are clever enough to avoid being eaten by sabre-toothed tigers), the ones whose differences help them live longest will make the most copies.

And those differences will then be used as the starting point for the next rounds of feedback, both positive and negative – so the differences get amplified very quickly when they’re useful, and die off very quickly when they’re useless, so you soon end up with giraffes whose necks are taller than my house, and humans who can invent quantum physics and write Finnegans Wake, within what is, from the point of view of the universe, the blink of an eye.

But what has that to do with the scientific method?

Everything – in fact, in essence, it is the scientific method.

To do science, you need to do three – and only three – things. You need to have a hypothesis, perform an experiment to test that hypothesis, and revise your hypothesis in accordance with the result. It’s a process exactly like that of natural selection.

In particular, for science we want negative feedback – we desperately want to prove ourselves wrong. We come up with a hypothesis – let’s say “All things fall to the ground, except computer monitors, which float”. We now want to see if our hypothesis will survive, just like our giraffes or people did. So we want negative feedback. So we have to ask what test will prove us wrong?

What we don’t want is a test that seems to confirm our hypothesis – that’s boring. We got our hypothesis from looking at the world – maybe I dropped a cup on the floor and it broke (that’s where positive feedback from the environment comes in – we need something from the environment to start the ball rolling). So we don’t want to run a test where we already know the answer – we’re not trying to prove to ourselves that we’re right. So we don’t try dropping another cup.

A test that might go wrong there is dropping a computer monitor. If we try that, we discover that our initial hypothesis was wrong – computer monitors don’t float. So we revise our hypothesis – maybe to “All things fall to the ground, and if you put your foot under a monitor when you drop it, it really hurts” – and then we test the new hypothesis.

When your hypothesis matches experiment time and again – when everything you or anyone else can think to throw at it, that might prove it wrong, matches what your hypothesis says – then you’ve got a theory you can use to make predictions. You’ve suddenly got the ability to predict the future! That’s pretty impressive, for something that is, in essence, no different from what my guitar does when leaned against an amp.

You can also use it to ‘predict’ the past, in the same way – which is why things like paleontology are sciences, and why social sciences like history are called social sciences rather than arts. You can do the same thing there, except that the experiments involve looking for things that have already happened but you don’t know, rather than trying new things and seeing what happened. You might, for example, come up with the hypothesis “Tyrannosaurus Rex was actually a vegetarian.” Using that hypothesis, you’d make various predictions – that if you looked at a T. Rex skull it would have lots of flat teeth, suitable for grinding vegetation, for example. Then you’d go and look at the skull, and examine the teeth, and see that in fact it had tons of razor-sharp teeth suitable for ripping flesh, and revise your hypothesis, maybe coming up with “Tyrannosaurus Rex was actually not a vegetarian.”

(Apologies to my friends Mike and Debi, whose field I have grossly oversimplified there).

This is the big difference between scientists and other groups – like conspiracy theorists or a sadly-large number of politicians. Conspiracy theorists go looking for evidence that confirms their ‘theories’, and they find it. You can always find confirmation of anything, if you’re willing to ignore enough negative evidence. If you go looking for evidence that you’re wrong – and you do so sincerely, and invite others to aid you in your search – and you don’t find it, you’re probably right.

Next week – how to choose between alternative theories.