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H A Prichard

question 29

Multiple Choice

H. A. Prichard: Does Moral Philosophy Rest on a Mistake?
Prichard begins by considering a skeptical question: "Is there really a reason why I should act in the ways in which hitherto I have thought I ought to act?" Consideration of this question leads us to seek a proof of our ethical convictions, which we previously accepted without proof. The trouble is, Prichard claims, that the available answers to this question are inadequate. On the one hand, one could try to show we ought to do some action because it is in our interest. But this, Prichard objects, would not show that we ought to perform that action; it would merely succeed in making us want to perform it. On the other hand, one could claim that we should do some action because of the goodness either of the action or of its consequences. Prichard argues, however, that neither of these suffices to show that the action is obligatory.
Contrasting his own view with these attempts to prove that we ought to do something via argument, Prichard claims that our sense of obligation to perform an action "is absolutely underivative or immediate," known directly via an act of moral thinking. Although we may need to figure out the consequences of an action before we can see whether it is right or wrong, Prichard argues that once we have done so, our knowledge of our obligations is noninferential. After clarifying several aspects of his view, Prichard address the original question: Does moral philosophy rest on a mistake? Prichard's answer is that if we conceive of moral philosophy as the attempt to give arguments that will prove that we do have certain obligations, then the enterprise does rest on a mistake. This is because, on Prichard's view, moral knowledge cannot be proven, but can only be known directly by applying our moral capacities to particular situations.
-Prichard compares Moral Philosophy to:

Definitions:

Proportion

A part, share, or number considered in comparative relation to a whole; a statistical measure often used to describe a characteristic of a sample.

Variability

The extent to which data points in a statistical distribution or dataset differ from the average or mean value.

Sample Size

The number of observations or data points collected in a sample from a population.

Central Limit Theorem

A statistical theory that states that, given a sufficiently large sample size from a population with a finite level of variance, the mean of all samples from the same population will be approximately equal to the mean of the population, and the samples will be distributed approximately normally.