It would be surprising if we were scientifically entirely unbiased. Cognitive biases caused by evolutionary traits inappropriate for the modern world have recently received a lot of attention. Many psychological effects in consumer behavior, opinion and decision making are well known by now (and frequently used and abused). Also the neurological origins of religious thought and superstition have been examined. One study particularly interesting in this context is Peter Brugger et al’s on the role of dopamine in identifying signals over noise.
If you bear with me for a paragraph, there’s something else interesting about Brugger’s study. I came across this study mentioned in Bild der Wissenschaft (a German popular science magazine, high quality, very recommendable), but no reference. So I checked Google scholar but didn’t find the paper. I checked the author’s website but nothing there either. Several Google web searches on related keywords however brought up first of all a note in NewScientist from July 2002. No journal reference. Then there’s literally dozens of articles mentioning the study after this. Some do refer to, some don’t refer to the NewScientist article, but they all sound like they copied from each other. The article was mentioned in Psychology Today, was quoted in Newspapers, etc. But no journal reference anywhere. Frustrated, I finally wrote to Peter Brugger asking for a reference. He replied almost immediately. Turns out the study was not published at all! Though it is meanwhile, after more than 7 years, written up and apparently in the publication process, I find it astonishing how much attention a study could get without having been peer reviewed.
Anyway, Brugger was kind enough to send me a copy of the paper in print, so I know now what they actually did. To briefly summarize it: they recruited two groups of people, 20 each. One were self-declared believers in the paranormal, the other one self-declared skeptics. This self-description was later quantified with commonly used questionnaires like the Australian Sheep-Goat Scale (with a point scale rather than binary though). These people performed two tasks. In one task they were briefly shown (short) words that sometimes were sensible words, sometimes just random letters. In the other task they were briefly shown faces or just random combination of facial features. (These both tasks apparently use different parts of the brain, but that’s not so relevant for our purposes. Also, they were shown both to the right and left visual field separately for the same reason, but that’s not so important for us either.)
The participants had to identify a “signal” (word/face) from the “noise” (random combination) in a short amount of time, too short to use the part of the brain necessary for rational thought. The researchers counted the hits and misses. They focused on two parameters from this measurement series. The one is the trend of the bias: whether it’s randomly wrong, has a bias for false positives or a bias for false negatives (Type I error or Type II error). The second parameter is how well the signal was identified in total. The experiment was repeated after a randomly selected half of the participants received a high dose of levodopa (a Parkinson medication that increases the dopamine level in the brain), the other half a placebo.
The result was the following. First, without the medication the skeptics had a bias for Type II errors (they more often discarded as noise what really was a signal), whereas the believers had a bias for Type I errors (they more often saw a signal where it was really just noise). The bias was equally strong for both, but in opposite directions. It is interesting though not too surprising that the expressed worldview correlates with unconscious cognitive characteristics. Overall, the skeptics were better at identifying the signal. Then, with the medication, the bias of both skeptics and believers tended towards the mean (random yes/no misses), but the skeptics overall became as bad at identifying signals as the believers who stayed equally bad as without extra dopamine.
The researcher’s conclusion is that the (previously made) claim that dopamine generally increases the signal to noise ratio is wrong, and that certain psychological traits (roughly the willingness to believe in the paranormal) correlates with a tendency to false positives. Moreover, other research results seem to have shown a correlation between high dopamine levels and various psychological disorders. One can roughly say if you fiddle with the dose you’ll start seeing “signals” everywhere and eventually go bonkers (psychotic, paranoid, schizoid, you name it). Not my field, so I can’t really comment on the status of this research. Sounds plausible enough (I’m seeing a signal here).
In any case, these research studies show that our brain chemistry contributes to us finding patters and signals, and, in extreme, also to assign meaning to the meaningless (there really is no hidden message in the word-verification). Evolutionary, type I errors in signal detection are vastly preferable: It’s fine if a breeze moving leaves gives you an adrenaline rush but you only mistake a tiger for a breeze once. Thus, today the world is full of believers (Al Gore is the antichrist) and paranoids who see a tiger in every bush/a feminist in every woman. Such overactive signal identification has also been argued to contribute to the wide spread of religions (a topic that currently seems to be fashionable). Seeing signals in noise is however also a source of creativity and inspiration. Genius and insanity, as they say, go hand in hand.
It seems however odd to me to blame religion on a cognitive bias for Type I errors. Searching for hidden relations on the risk that there are none per se doesn’t only characterize believers in The Almighty Something, but also scientists. The difference is in the procedure thereafter. The religious will see patterns and interpret them as signs of God. The scientist will see patterns and look for an explanation. (God can be aptly characterized as the ultimate non-explanation.) This means that Brugger’s (self-)classification of people by paranormal beliefs is somewhat besides the point (it likely depends on the education). You don’t have to believe in ESP to see patterns where there are none. If you read physics blogs you know there’s an abundance of people who have “theories” for everything from the planetary orbits, over the mass of the neutron, to the value of the gravitational constant. One of my favorites is the guy who noticed that in SI units G times c is to good precision 2/100. (Before you build a theory on that noise, recall that I told you last time the values of dimensionful parameters are meaningless.)
The question then arises, how frequently do scientists see patterns where there are none? And what impact does this cognitive bias have on the research projects we pursue? Did you know that the Higgs VEV is the geometric mean of the Planck mass and the 4th root of the Cosmological Constant? Ever heard of Koide’s formula? Anomalous alignments in the CMB? The 1.5 sigma “detection?” It can’t be coincidence our universe is “just right” for life. Or can it?
This then brings us back to my earlier post. (I warned you I would “expand” on the topic!) The question “What is natural” is a particularly simple and timely example where physicists search for an explanation. It seems though I left those readers confused who didn’t follow my advice: If you didn’t get what I said, just keep asking why. In the end the explanation is one of intuition, not of scientific derivation. It is possible that the Standard Model is finetuned. It’s just not satisfactory.
For example Lubos Motl, a blogger in Pilsen, Czech Republic, believes that naturalness is not an assumption but “tautologically true.” As “proof” he offers us that a number is natural when it is likely. What is likely however depends on the probability distribution used. This argument is thus tautological indeed: it merely shifts the question what is a natural from the numbers to what is a natural probability distribution. Unsurprisingly then, Motl has to assume the probability distribution is not based on an equation with “very awkward patterns,” and the argument collapses to “you won't get too far from 1 unless special, awkward, unlikely, unusual things appear.” Or in other words, things are natural unless they’re unnatural. (Calling it Bayesian inference doesn’t improve the argument. We’re not talking about the probability of a hypothesis, the hypothesis is the probability.) I am mentioning this sad case because it is exactly the kind of faulty argument that my post was warning of. (Motl also seems to find the cosine function more natural than the exponential function. As far as I am concerned the exponential function is very natural. Think otherwise? Well, zis why I’m saying it’s not a scientific argument.)
The other point that some readers misunderstood is my opinion on whether or not asking questions of naturalness is useful. I do think naturalness is a useful guide. The effectiveness of the human brain to describe Nature might be unreasonable (or at least unexplained), but it’s definitely well documented. Dimensionless numbers that are much larger or smaller than one have undeniably an itch-factor. I’m not claiming one should ignore this itch. But be aware that this want for explanation is an intuition, call it a brain child. I am not saying thou shell disregard your intuition. I say thou shell be clear what is intuition and what derivation. Don’t misconstrue for a signal what is none. And don’t scratch too much.
But more importantly it is worthwhile to as ask what formed our intuitions. On the one hand they are useful. On the other hand we might have evolutionary blind spots when it comes to scientific theories. We might ask the wrong questions. We might be on the wrong path because we believe to have seen a face in random noise, and miss other paths that could lead us forward. When a field has been stuck for decades one should consider the possibility something is done systematically wrong.
To some extend that possibility has been considered recently. Extreme examples for skeptics in science are proponents of the multiverse, Max Tegmark with his Mathematical Universe ahead of all. The multiverse is possibly the mother of all Type II errors, a complete denial that there is any signal.
In Tegmark’s universe it’s all just math. Tegmark unfortunately fails to notice it’s impossible for us to know that a theory is free of cognitive bias which he calls “human baggage.” (Where is the control group?) Just because we cannot today think of anything better than math to describe Nature doesn't mean there is nothing. Genius and insanity...
For what the multiversists are concerned, the “principle of mediocrity” has dawned upon them, and now they ask for a probability distribution in the multiverse according to which our own universe is “common.” (Otherwise they had nothing left to explain. Not the kind of research area you want to work in.) That however is but a modified probabilistic version of the original conundrum: trying to explain why our theories have the features they have. The question why our universe is special is replaced by why is our universe especially unspecial. Same emperor, different clothes. The logical consequence of the multiversial way is a theory like Lee Smolin’s Cosmological Natural Selection (see also). It might take string theorists some more decades to notice though. (And then what? It’s going to be highly entertaining. Unless of course the main proponents are dead by then.)
Now I’m wondering what would happen if you gave Max Tegmark a dose of levodopa?
It would be interesting if a version of Brugger’s test was available online and we could test for a correlation between Type I/II errors and sympathy for the multiverse (rather than a believe in ESP). I would like to know how I score. While I am a clear non-believer when it comes to NewScientist articles, I do see patterns in the CMB ;-)
[Click here if you don't see what I see]
The title of this post is of course totally biased. I could have replaced physics with science but tend to think physics first.
Conclusion: I was asking may it be that we are biased to miss clues necessary for progress in physics? I am concluding it is more likely we're jumping on clues that are none.
Purpose: This post is supposed to make you think about what you think about.
Reminder: You're not supposed to comment without first having completely read this post.