I’ve now completed my Pillars of Science series.  My goal was to analyze why Science is  such an amazingly effective method for discovering new truths about the world.  Here are the 6 “Pillars” I identified.  Of course, Science is a multifaceted word: it can refer to a method, a set of theories, or a community.  Understanding how Science works really requires thinking about all 3 together.

Intro:

• The Pillars of Science

A. How do we test scientific ideas?

• Pillar of Science I: Repeatable Observations
• Pillar of Science II: Elegant Hypotheses

B. What kinds of ideas can be tested scientifically?

• Pillar of Science III: Approximate Models
• Pillar of Science IV: Precise Descriptions

C. Who can test them effectively?

• Pillar of Science V: Ethical Integrity
• Pillar of Science VI: Community Examination

Having laid this preparatory groundwork, in the next few weeks I’d like to get to a more exciting and controversial topic: I plan to discuss Christianity specifically in the context of each of these 6 Pillars to see how well it holds up.  (But before I get to that, I plan to post a bit about whether there are any other evidence-based ways of looking at the world, besides Science.)

You see, in this blog I am taking seriously the “What about Science?” objection to Christianity.  Many people think that the basic principles of Science are somehow refute or undercut religious views.  These are supposedly based on something called “faith” which is diametrically opposed to “evidence”.  While everyone knows that some scientists are religious, many people think this is only possible because of “compartmentalized thinking” in which the two different approaches to life are somehow sealed off in different compartments so that the “evidence” compartment isn’t allowed to explode the “faith” compartment.

Now those of us who practice the spiritual discipline of Undivided Looking obviously approve of UN-compartmentalized thinking, in which we think of reality as a whole, without making special exemptions for parts of life we don’t want to subject to critical scrutiny.  Somewhat paradoxically, this does not require us to disapprove of compartmentalized thinking.  In certain respects Science itself is based on compartmentalized thinking (see Pillar III).

And we couldn’t stop doing it even if we tried, because our brains are wired for compartmentalized thinking.  (Especially the male brain, which is more likely to delegate tasks to particular regions of the brain, whereas the female brain is more likely to think using connections between different parts of the brain.  See e.g. this study.)  But what we can and should do sometimes, is make a conscious effort to look at things together, rather than separately.

Since I’m going to be referring back to these six Pillars of Science, I’d like to ask for some reader feedback.  Do you think my discussion of these Pillars could be improved?  I’d like to solicit criticisms on any of the following issues, or anything else you can think of:

• Is there any practice which is important to Science which I have not included in the Pillars?  Or which I should have emphasized more?

• Is there anything which I’ve said is important for Science, which actually isn’t?  Are there branches of Science which do without any of these things?

• My perspective is that of a physicist who works on fundamental issues.  But there’s lots of other scientific fields: Biology, Geology, Chemistry, etc.  Do you think someone from these fields might have prioritized different aspects of scientific practice than I did?

Scientific Results are Examined Collaboratively.

Scientists do not work alone, but in a particular kind of community.  The last stage of a research project is publishing and explaining the results.  Assuming these results get noticed, this begins the process of further review, critique, confirmation and rebuttal by other scientists.  No one person is smart enough to see things from all angles.  We need help from others to look in a clearer, less fragmented way.  Perhaps one could call this undivided looking?

Science is not just a set of facts, or an abstract procedure for testing ideas.  It is an ethical, truth-seeking community.  The love of truth is embodied in the alliance of particular, fallible humans, united by a common geeky interest in finding something out.  Together we create a public deposit of information which can be used to find new things out.

Because the community as a whole is truth-seeking, in the long run it reduces the need to trust the competency and ethics of the original researchers.  If someone fakes an experiment (or else just makes an innocent mistake), other people will be unable to replicate the result, and eventually the truth will come out.

Healthy scientific collaboration encourages reasonable dissent.   Otherwise group-think can insulate the community from effective criticism of accepted ideas.  Some people say that scientists should proportion their beliefs to the evidence.  However, there’s also some value in diversity of opinion, because it permits subgroups to work on unpopular hypotheses.  I suppose things work best when the scientific community taken as a whole proportions its research work to the evidence.

One might argue that collaboration is not strictly necessary to Science.  Imagine a solo scientist doing careful experiments in secret, and drawing the correct conclusions from them.  (Even in this case the scientist would be drawing on public ideas which had gone before, “standing on the shoulders of giants”, as the saying goes.)  But in practice, the benefits of discussion are so great that it’s hard to imagine a successful modern scientist working completely alone.  Hence the symbiosis of Science with the Academy.

Individuals who think they can revolutionize Science all by themselves are almost always crackpots, the sort of crazy person I described one pillar ago.  If you want to see clearly, you have to expose yourself to the light.

Scientists must have Integrity.

Because Science involves an ethical principle, the love of truth, its practice cannot be unmoored from principles of morality.  A hypothesis can only be put to a fair test by a person who prefers knowing the truth even if it shows that their previous position was wrong (a corollary is that science becomes unreliable when there is political pressure to come to particular conclusions, such as the Lysenkoist biology mandated by Stalin, or the Deutschephysik of Nazi Germany).

This virtue is sometimes referred to as “objectivity”, but this word suggests a sort of dispassionate neutrality which is not actually characteristic of most real scientists—we actually tend to get rather excited about our work, or we wouldn’t be doing it.  A better term for this virtue is humility: when doing research the scientist must take the posture towards the universe of a learner, rather than a teacher.  Unfortunately, some effective scientists are conceited and arrogant towards their peers, but when scientists take the same attitude towards Nature, they continue to defend ideas long after they become discredited, and become useless to Science.

It’s also extremely common for working scientists to get mailings from laypersons who believe themselves to have revolutionized large areas of science, despite having imprecise, untested, and often meaningless ideas.  This psychotic disconnect from reality is nearly always accompanied by severe egoism, showing by contrast the way that humility characterizes true science.

Of course, humility does not involve taking the view that all knowledge is unreliable and tentative, since this would actually inhibit the discovery of truth!  (In modern times, revolutions in Science usually do not totally invalidate our previous understandings; instead the previous theories survive as approximations.)  The proper attitude of a learner is: “Test everything; hold onto what is good” (1 Thessalonians 5:21).

A second virtue of science is honesty.  Scientists must refrain from fudging results or misleading other scientists.  Honesty requires noting the factors weighing against a conclusion as well as those weighing for it.  They must also take precautions against bias, not in the sense of being unbiased (none of us are), but preventing that bias from contaminating their results.  Hence the need for experimentalists to do proper error analysis, use control groups, double-blind tests, etc.  Experiments that show the absence of an effect should be published as well as experiments that show the presence of an effect, even if such results are less likely to result in fame and respect.

I was going to include some juicy long excerpt from Feynman’s famous commencement address on “Cargo Cult Science”.  But too much of it was relevant to what I’m saying!  You should just go and read the whole thing.

Science involves Precise Description.

To be capable of being confirmed or ruled out at the high levels of reliability associated with Science, a hypothesis must be stated in a way which is precise enough to do definitive tests.  Even if a scientific hypothesis may not be experimentally testable at the present time, a precise formulation helps indicate ways that it could be tested in the future.  If experiment is capable of making everyone eventually agree on whether the idea worked or not, then the words it is expressed in shouldn’t mean different things to different people.

Mathematical models of the physical world are the most precise form of description available, because they can describe complicated systems with perfect exactitude.  In theoretical physics, this kind of quantitative description is the usual way to make things precise.  We like to think about systems that are simple enough to describe mathematically (of course, this requires first making certain approximations).  In fact, fundamental physics is so mathematical that, even when there are no or few experiments, one can often make progress just by demanding that the model be logically consistent, and that it conform to known physical principles.  (Known, because they have been tested in other situations where we can do experiments.)  Mathematical consistency is nearly our only guide in speculative fields like my own (quantum gravity); however, it cannot completely substitute for observations, since no matter how consistent or beautiful your model is, Nature could always do something else when you finally are able to take a look.

So Math is great when you can get it.  Nevertheless, systems which are less regular, more complex, or less well-understood (such as biological life) cannot always be described mathematically, but may still be described through technical vocabulary that minimizes imprecision, without removing it altogether.  I’m not a biologist, so I’m probably not the best person to ask how this usually works, but I didn’t want to give the impression that math is the only way to make ideas precise.  Even in physics, at one time it was possible to describe everything in words.  The great experimenter St. Faraday (whose work helped established the concept of the electromagnetic field), once wrote a letter to St. Maxwell (who wrote down the equations for electromagnetism) expressing surprise at Maxwell’s need to translate everything into mathematical equations.  Yet no one could accuse Faraday’s journals of being imprecise.

But not all concepts will do.  Ideas that are apprehended in words or images rich with heavy associations or mottled with variegated meanings—in short, using the common language of humanity—such ideas are excluded from Science.  Not because it is impossible to discuss and test these ideas; if that were true, then it would be impossible to think accurately at all about most matters of ordinary human concern.  Rather, it is because they involve elements of human and holistic judgement which are unsuitable for scientific inquiry.  The question “Is xenophobia a frequent cause of war?” could be given an informed and accurate answer by a historian, but it does not become a scientific question until the terms “xenophobia”, “frequent”, and “war” are given technical meanings sufficiently precise that a social scientist can do a statistical analysis.

Science requires Approximations.

Every kind of professional activity changes the way you think.  It rewires your brain so that even when you’re off the job, things start looking a certain way.  For example, to a computer programmer everything looks like an algorithm.  To a teacher, everything is pedagogical.  As a physicist, what goes through my head every day is approximations.

Every time I think about a situation involving black holes, or prove a theorem, or do a calculation, I always have to keep in the back of my mind what kinds of physical effects I’m ignoring, not taking into account.  This habit has leaked out into my thinking about life in general.  Ideas don’t have to be just true or false, instead they can be good approximations in some contexts, and bad approximations in other contexts.

(Partly related: before I started doing physics seriously, I think I had the idea in the back of my head that when I went to grad school, I’d learn how to calculate the really hard problems.  But it turns out there is no way to calculate the answers to the hard math problems.  There are only clever tricks for simplifying hard problems so that they become easy problems.  Frequently, the clever trick is finding some parameter that can be taken to be small, in order to justify some approximation.  The way this works is: first you figure out what happens if the parameter is zero, and then you calculate the tiny effects of it not quite being zero.)

It is impossible for any model of the universe to capture every feature of reality, or else it would be too complicated for human beings to analyze, or to compare to experiment, at the high level of precision demanded by science.  Consequently every scientific theory is applicable only to some limited range of phenomena.  In other words, it isolates some feature of reality which is as free as possible from contaminating influences, and which is simple enough to be either measured experimentally or calculated theoretically (ideally, one can do both, to compare the theory to the experiment).

Therefore, Science consists of a bunch of partly overlapping models which cover different patches of reality. Some of these patches are smaller, and cover very specific situations (e.g. Bernoulli’s principle for fluid dynamics) and others cover a very broad range of situations (e.g. Quantum Electrodynamics, which covers everything related to electricity, chemistry, and light). None of these patches covers everything, and the two broadest patches, Quantum Field Theory and General Relativity, cannot yet be fully reconciled with one another.

One of the implications of this principle is that scientific revolutions seldom result in the complete discrediting of the old well-established theory. The reason is that if the first theory explained a significant patch of data, the new theory can only supercede the old one if it explains all the things the first one explained, and more. Usually this means that the old theory is a limiting situation or special case of the new theory. Thus the old theory is still valid, just in a smaller patch than the new theory. For example, Einstein’s theory of General Relativity superceded Newton’s theory of gravity, but it predicts nearly the same results as Newton in the special case that the objects being considered are travelling much slower than light, and their gravitational fields are not too strong.

Thus the empirical predictions of Newton’s theory are still correct when applied in the proper domain.  However, the philosophical implications regarding the nature of space and time could hardly be more different in the two theories, because the Newtonian theory regards space and time as fixed, immutable, separate entities, while Einsteinian theory regards spacetime as a single contingent field capable of being affected by the flow of energy and momentum through the spacetime.

Philosophers who reason from scientific discoveries should take warning from this: although the empirical predictions of a theory usually survive revolution, the philosophical implications often do not.  Thus our current scientific views on such matters should be taken as somewhat provisional.  On the other hand, it would be even more foolhardy to try to discuss the philosophical nature of space, time, causality, etc. without taking into account the radical changes which Science has made to our naïve intuitions about these concepts.  Some improvement of our thinking is better than none.