Entry tags:

formal_ed, phil.sci

Philosophy of Science: * scientific understanding; * philosophy in practice; * theory engineering
W. H. Newton-Smith's "Companion to the Philosophy of Science" is an excellent encyclopedia-style book. I might buy it if it weren't so bulky (the lighter I travel, the better)

Scientific Understanding

Understanding Scientific Understanding is an interesting project. I would like to unify Minsky's notion of "understanding as multiple representations" with Lakatos's models of reasoning and theory change. Understanding can also come in the form of explanatory redundancy: if you derive the same result in two different ways, you are justified in saying that you understand it, at least with respect to the theory. One could call this "understanding as deductive confirmation", and it's similar to the confidence that you get by double-checking a computation by implementing an algorithm in different ways, or by proving things with Coq: the probability that there's a mistake is greatly reduced.

But "understanding" usually means more than just increased confidence. I think understanding involves generalization: could you answer another question about the derived result? This reminds me of work on computational analogy, and the idea of applying theory formation to generating questions that test student understanding (I've heard of work on this by Simon Colton via Alison Pease). I'd really like to see math problem generators that go beyond changing parameters. (At AIED, I met Henry Halff, an independent developer of physics-tutoring systems who was interested in this very problem, and wasn't aware of the possibility of applying theory-formation, which I had learned by talking to Alison just 3 months before).

---

The Practical Importance of Philosophy

H.W. de Regt, 'Are physicists' philosophies irrelevant idiosyncrasies?' Philosophica 58 (1996, 2) 125-151.

This article argues that individual philosophical commitments of scientists can decisively influence scientific practice. Two examples from the history of physics, concerning controversies between physicists over central problems in their discipline, are presented to support this thesis. Confrontation of the examples with the theories of Kuhn, Lakatos, and Laudan, reveals their inadequacy to explain the role of individual commitments. It is concluded that an adequate model of scientific change should exhibit a three-level structure.

---

Theory Engineering

I have long criticized "Philosophy of X" when you already have a "Science of X". e.g. let X be "language". Why have a philosophy of language if we already have linguistics?
The standard answer, I think, is that linguists make assumptions that need to be questioned, and we need philosophers to do that. But my view is that linguists themselves should be doing this: they should know the real philosophical significance of their work, and science should not be divorced from philosophy. Is there ever a case when it would be better for the linguist to remain ignorant of what their work really says?

One big difference between the practice of science and the practice of philosophy seems to be that philosophers are always inventing new words, reinventing the wheel, creating new ontologies. Most scientists, on the other hand, don't do this enough. While philosophers are always trying to break out of their paradigms, most scientists seem content in "doing good work" within the frameworks that were set up by the pioneers of the field.

In other words, philosophers are always designing conceptual systems (often reinventing the wheel), whereas scientists will usually just use the libraries given to them (compare with Kuhn's idea of "puzzle solving"). For these reasons, software engineering should be a standard part of a philosophy education, and philosophy of science should be a standard part of a science education.

Problems like commensurability, theory change, theory relations, etc. should all yield to a formal approach. In fact, I cannot think of any kind of scientific reasoning that could not be automated. But this is not surprising coming from a "computational reductionist" like me (I don't like the term "Strong AI", because the concept of "self-awareness" is loaded)

Here's a disappointing Google search, except maybe for this.

Here's a more promising one.