Puzzle solving in normal science involves a process of accommodation—auxiliary assumptions are changed, and parameter values are adjusted so as to eliminate the known discrepancies with the data. Accommodation is often contrasted with prediction. Predictions happen when one achieves a good fit with novel data without accommodation. So, what exactly is the distinction, and why is it important? The distinction, as I understand it, is relative to a model M and a data set D, where M is a set of (...) equations with adjustable parameters (i. e., M is a family of equations with no free parameters). Definition: Model M predicts data D if and only if either (a) all members of M fit D well, or (b) a particular predictive hypothesis is selected from M by fitting M to other data, and the fitted model fits D well. M merely accommodates D if and only if (i) M does not predict D, and (ii) the predictive hypothesis selected from M using other data does not fit D well. There will be cases in which a model M neither predicts nor accommodates D. These are the cases in which we are willing to say that data falsifies the model. So, the distinction between prediction and accommodation applies only when there is no falsification. (shrink)
Traditional analyses of the curve fitting problem maintain that the data do not indicate what form the fitted curve should take. Rather, this issue is said to be settled by prior probabilities, by simplicity, or by a background theory. In this paper, we describe a result due to Akaike , which shows how the data can underwrite an inference concerning the curve's form based on an estimate of how predictively accurate it will be. We argue that this approach throws light (...) on the theoretical virtues of parsimoniousness, unification, and non ad hocness, on the dispute about Bayesianism, and on empiricism and scientific realism. * Both of us gratefully acknowledge support from the Graduate School at the University of Wisconsin-Madison, and NSF grant DIR-8822278 (M.F.) and NSF grant SBE-9212294 (E.S.). Special thanks go to A. W. F. Edwards.William Harper. Martin Leckey. Brian Skyrms, and especially Peter Turney for helpful comments on an earlier draft. (shrink)
In “Connectionism and the fats of folk psychology”, Forster and Saidel argue that the central claim of Ramsey, Stich and Garon (1991)—that distributed connectionist models are incompatible with the causal discreteness of folk psychology—is mistaken. To establish their claim, they offer an intriguing model which allegedly shows how distributed representations can function in a causally discrete manner. They also challenge our position regarding projectibility of folk psychology. In this essay, I offer a response to their account and show how (...) their model fails to demonstrate that our original argument was mistaken. While I will discuss several difficulties with their model, my primary criticism will be that the features of their model that are causally discrete are not truly distributed, while the features that are distributed are not really discrete. Concerning the issue of projectibility, I am more inclined to agree with Forster and Saidel and I offer a revised account of what we should have said originally. (shrink)
E.M. Forster’s A Passage to India presents Brahman Hindu jurisprudence as an alternative to British rule of law, a utilitarian jurisprudence that hinges on mercantilism, central planning, and imperialism. Building on John Hasnas’s critiques of rule of law and Murray Rothbard’s critiques of Benthamite utilitarianism, this essay argues that Forster’s depictions [...].
In what may be the most radical business book ever published, philosopher Jay Ogilvy shows that living without a goal is the only way to accomplish anything. In the 1980s we ran our lives with all the direction and confidence filofaxes and to-do lists could provide. Always knowing exactly where we were headed, we climbed toward the goals corporate America held out in front of us like so many carrots: higher salaries, better titles, more impressive offices. But after a decade (...) of climbing, the air is getting thin. We crave the chance to create, to express ourselves, and to make a difference, not just a living. It is time, says businessman/philosopher James Ogilvy, to tear up the to-do lists and grant ourselves the freedom to enjoy what E. M. Forster calls "the lights and shades that exist in the greyest conversation." Ogilvy shows that richness and color and flavor flood back into our lives once we set aside the goals that hold us captive. He explores how philosophers (from Plato to Nietzsche), lovers, ideologues, and executives have at one time or another lived without goals. What emerges from his argument is a new look at how to achieve personal creativity and freedom by fashioning one's day to-day life, not as a larger goal-producing machine, but as a personal work of art. (shrink)