Is Ridicule of ID Creationists Counter-Productive?

Over at Pharyngula, a couple of commenters brought up the subject of using ridicule to "turn people against a bad idea" (i.e. "Intelligent Design" creationism). I agreed with the second commenter, who was concerned that by being insulting we might turn away "the folks we should want to reach". Without suggesting an alternative, I said that the "divisive and polarising effect" of ridicule would work against us, unless a majority the audience were inclined to be driven into our camp already.

At this point PZ Myers complained that unless we stopped "sit[ting] around all deferential and crap", the likes of Hovind and Ham would be allowed to keep regurgitating their outrageous falsehoods without restraint, which is of course just what they want. Since that's not what I wanted to suggest, I tried to expand on my original thoughts, in a further comment, reproduced below:

Sorry if I gave the wrong impression in my previous comment. I'm certainly not advocating a policy of sitting politely in silence while outrageous falsehoods are flung around. In fact, I'm not advocating anything in particular yet, just turning some ideas around in my mind.

The truth needs to be defended vigorously against the BS peddled by the IDC crowd, and I want to figure out the most effective way to do that. That's why I'm suggesting that it's not enough to be right on the facts; it's important to have the right kind of presentation as well. By this, I just mean knowing the target audience and behaving in a way that will convince them.

The target audience isn't the community of real biologists, who know about evolution and don't need to be convinced of anything. And frankly, the target isn't the IDC true-believers either, whose brains have been turned to dogmatic mush - they're lost causes, and a pretty small minority anyway.

No, the real target audience who we need to win over to the side of reason are the vast millions who have never really thought too hard about evolution (or any scientific matter). They're the ones we have to convince, the ones who have to be prized away from the reassuring lures of comfortable falsehoods. For the most part they're pretty reasonable people, who just happen to be severely ignorant about what science is, how it works, what is known and not known, etc. There are millions of them, each with one ignorant uninformed vote to cast, so their opinions matter.

These 'floating voters' are the audience I was thinking of when I wrote my previous comment. They're so far down the 'non-expert' end of the scale that they can't even tell who the experts are. They see two people who disagree on a subject they're unfamiliar with, and they just use whatever clues they can find to decide who to believe.

To people like us who know about the subject, nonsense like talk of "the missing link" are enough to reveal someone as a phoney. But the average Joe can't do that, and has to use other (perhaps unreliable) indicators. The folks at the DI have learnt to use some of these indicators - calling themselves Professor, quoting well-known scientists, using complex terminology. To the uninformed layman this cargo-cult science is close enough to the real thing that he can't tell the difference. Meanwhile, if the real scientists make no arguments, get angry, and shout abuse, what kind of impression does that make?

We all know that any conflict that exists between evolution and IDC isn't scientific, it's political. The tactics and methods we use, then, have to be political to some degree. Merely having the facts on our side isn't enough. We have to present the facts in a way that wins the audience's trust, and reveals the IDC crowd for the clowns they are. Simply calling them clowns in front of an audience that has no reason to trust us isn't going to work in the long run. The trouble is, I don't know what is going to work - and that's why I'm not making specific suggestions.

There's certainly a place for mockery and ridicule, and Pharyngula is one of them. But in the larger public forum of newspapers, radio and TV we need to look carry on looking like scientists - because that's an act that the impersonators of the Discovery Institute are getting good enough at to fool the public.

On the Use of "Information Talk" in Biology - Useful or Misleading Analogies

[Likewise very drafty - same caveats apply]

Analogies form a vital tool in exploring a new field of study, since they provide a familiar structure into which we can attempt to arrange the new, unfamiliar phenomena. Faced with a structureless bulk of newly-discovered facts, a researcher may well struggle to find the inherent patterns that allow the data to be carved up into simpler blocks, divided into high-level structures and low-level details, and eventually re-described in a new language that allows for a unified understanding. However, if the investigation is guided by an analogy with some other, better-understood part of the world, the process can be accelerated; if we suspect that system XYZ has some structure analogous to known system ABC, and we find find that part X seems to play a role in XYZ like that of part A in ABC, then what could Y be? Quickly a couple of hypotheses suggest themselves...

Of course, the above is only the loosest of sketches of how analogies can guide research[\footnote{For a more careful look at this subject, see [?],[?],and [Corfield]}]. An important fact to note, and a key fact in all that follows in the "biological information" debate, is that analogies can only give us good hypotheses if they themselves are "good" analogies (in a sense to be developed shortly). Of course, hypotheses that turn out to be disconfirmed by the investigations designed to test them can in the long run be useful, if that disconfirming evidence brings with it greater insights. By "good" hypotheses we mean those that bring deeper understanding, those that are confirmed and form part of a more developed theory of the system in question. Such hypotheses are (more likely to be) produced by correct ideas about the structure of the system.

Thus, to provide helpful guidance in our research, we need analogies which point to genuine correspondences with other systems. Moreover, the correspondences should be deep, rather than superficial, picking out important features of the systems referred to. Analogies are better or worse, (very) roughly speaking, depending upon how many features the related systems share, how significant those features are in their respective systems, and how well the relations between those features match up across the comparison. Put another way, good analogies are those that pick out deep abstract structures that are relevantly instantiated in both systems.[\footnote{Disclaimer again: this is necessarily a very rough sketch, but it will suffice.}]

On the Use of "Information Talk" in Biology - Introduction

[Note: This is clearly very much still a draft version. Very clearly, very drafty]

In biology, especially molecular biology and genetics, much use is made of the analogy between the structures and processes of genetics and those of the world of human artifacts such as computers and radios. Thus it is said that genes "carry information" about proteins and phenotypic traits, DNA is "read", translated, transcribed, and decoded; mutations arise by "copying errors", and are sometimes fixed during the duplication process by "proof-reading" mechanisms; and so on. Note that this is not merely a feature of popularizations of science, translating complex ideas into language more easily understood by the public; on the contrary, the information metaphor was vital to in developing the first understanding of how DNA functions. [\footnote{Quote JMS - no Rosetta stone; studying it just by chemistry would take forever.}]

However, the details of how good this analogy really is have come under considerable scrutiny by philosophers of science, with opinions varying widely as to whether such talk of "biological information carried in genes" is (at one extreme [JMS]) literally correct, and in need of precise fleshing out, or (on the other hand [Griffiths]) both imprecise and misleading.

The general question of what makes an analogy good or bad, useful or misleading,is obviously too large to be tackled within the scope of this essay [\footnote{Find some refs on goodness of analogies in the Phil Lang literature.}]; nor would it be appropriate to attempt to give a full account of how analogies are used and are understood, or how they inform, convey meaning, or provoke new ideas. Fortunately, such a detailed analysis of analogy and metaphor is unneccesary for the present case, and a few general remarks, outlined in the next section and developed elsewhere, will suffice.

Having set out some of this general background, we turn straight to the central disagreement between the two sides. Taking John Maynard Smith and Paul[?] Griffiths as representatives of the opposing camps, we find that the point of opposition is easily described. Maynard Smith thinks that the analogy with information storage and processing is a good one[\footnote{Indeed,good enough that such "information talk" should be taken as literal, not merely metaphorical - but this distinction goes beyond our present scope.}], while Griffiths claims that it is misguided, drawing from a too-limited stock of examples on the biological side, and therefore more misleading than useful.

To explore this disagreement, we will examine some of the ways JMS defines the analogy - the features of genetic systems that are analogous with conventional information processing technology - and defends it against some of the simpler objections of critics. We then consider some further objections by Griffiths, which seem to support a position that he calls "the Parity Principle", namely that 'there is no sense in which genes carry information about phenotypes that is not also exemplified by non-genetic factors'. Thus talk of "genes carrying information" (as distinct from non-genetic factors) implies a priviledged distinction where none exists, and so is misleading.

In the final section of the essay, we consider how a defender of the analogy such as JMS should respond to Griffiths' objections. Can his examples of non-genetic factors which meet JMS's definition of information-cariers be somehow excluded? Can this definition be further refined or re-worked in order to cover all and only the factors JMS requires for the information analogy to hold firm? To answer this question, we need to know what it is about the analogy that makes it worth defending. Why does JMS want to justify talk of "molecular biology as a branch of information theory"? It can only be that he thinks such a view will be useful in developing our understanding of biological systems. Bearing this in mind, we consider how an information analogy (refined to take account of all the relevant data about genetic and non-genetic factors etc.) could be useful in biology, and how it might be possible to establish such an analogy more rigorously.

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Because, after all, a sequential collection of written articles doesn't officially count as a blog unless it has a picture of a cat on it. I don't make the rules...

What is Lie Theory?

Chris Hillman posted an extensive introduction to Lie groups and Lie algebras to sci.physics.relativity back in September 2000. There's also a snapshot of this post and a couple of sequels available via the Wayback Machine.

Research Proposal

I intend to examine and develop the approach to probability proposed by Edwin Jaynes, as described in his extensive published work and particularly in his book "Probability Theory: The Logic of Science", and to demonstrate the natural resolution this approach provides to a number of current problems in the philosophy of probability.

Jaynes' view of probability is a variant of Bayesianism, one in which all probability ascriptions are conditional probabilities, the rules for manipulating probabilities are derived from elementary desiderata (via Cox's Theorem), and the assignment of prior probabilities is the encoding of available evidence (or assumptions, or premises) in numerical form. Thus the "problem of priors" is viewed as a technical problem, to be solved by methods such as Jaynes' "Maximum Entropy" algorithm.

Jaynes worked as a physicist rather than a philosopher, and so was interested in demonstrating that his methods were internally consistent, were powerful enough to solve practical problems, and avoided the conceptual confusions of rival methods (such as frequentist statistics). My first aim is therefore to fill in the gaps left by Jaynes in order to provide a philosophically coherent package, by giving a careful and detailed account of the underlying assumptions and interpretation of probability implicit in his view.

After examining the philosophical requirements and implications associated with a Jaynesian view of probability, I will compare it with a number of alternative accounts in the literature, in particular focusing on the puzzles, problems and apparent paradoxes that are frequently discussed. The advantage of the Jaynesian approach will be demonstrated by its ability to solve (and in some cases simply avoid) many of the common difficulties, while naturally resolving some long-standing debates in an intuitively sensible manner.

Structural Realism sketchy intro

There are a variety of flavours of Structural Realism; the main division is between Ontic and Epistemic versions, which say respectively that "structure" is all that exists, or at least all that we can have knowledge of, in the world. Any SR theory has to give an acount of what structure is, and what knowledge of it we can come to have (if any), alongside dealing with whatever questions the theory is proposed to answer in the first place.

ESR itself divides into two major varieties, which Stathis Psillos has dubbed the "upward" and "downward" paths. The downward path, as championed by Worrall (with foreshadowing by Poincare), starts with the problem of theory change in science, and wonders just what it is that science is getting right even when its old theories are shown to be wrong. The anti-realist says "nothing", and is confronted with the then seemingly inexplicable successes of scientific prediction; the full-on realist says "everything" (at least, the most naive kind does), and then has some explaining to do whenever a field of science seems to undergo a radical shift. Worrall aims to steer a middle course, by finding something substantial that is retained even through radical theory change. This something is "structure" - specifically, the mathematical (or otherwise abstract) structures onto which interpretations are pasted. His standard example is Fresnel's account of light as transverse waves in a luminiferous aether: throw out the aether and bring in electromagnetic fields, and Maxwell's acount of light looks very similar in many important respects. The wave equations and other key features are preserved from Fresnel even while the basic ontology is overturned.

The upward path, which is associated with Russell, deals with questions about the correspondence between our perceptions and the outside world. In brief, it proposes that there are objects with relations between them in the world, and that our perceptions and the relations between them are in some way a reflection of those outside. Exactly what the connection might be, and how strong it is, has been debated by (for example) Psillos and Ioannis Votsis.