Kris McDaniel

This Is Metaphysics


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it contains the word “ngricular,” which stands for a feature that things have when they are either not green or are circular. Let’s call this language “the gruesome language.”

      1.31 The speakers of the gruesome language are in a similar position with respect to the words “gricular,” “ngricular,” and “grincular.” If you asked them what they meant by “gricular,” they would have to resort to gesturing at things that are gricular and hope that we get the general idea. A few of the more scientifically literate speakers of the gruesome language might tell us that gricular things are those things that either reflect light of a wavelength of around 510 nanometers or are shaped so that the points on its boundary are all some fixed distance from a center point and from a continuous figure. But they wouldn’t be giving you a definition of “gricular.” What they would be doing instead is similar to what we do when we say what wavelength of light green reflects. Gricular is not a word in their language that can be explicitly defined in terms of other words in their language, not even by speakers fully competent in the gruesome language.

      1.32 Speakers of the gruesome language classify things in a way that seems odd to us. Just consider all of the things that are grincular. Is this a list of things that objectively belong together? If nothing objectively belongs together with anything else, then their way of classifying objects is not objectively better or worse in this way, although there might be practical reasons to prefer continuing to classify objects in the way that we do instead of changing wholesale to their systems of classification.

      1.33 I am going to begin to develop an argument for the conclusion that some things objectively belong together. This argument turns on the idea that certain words are projectable while others aren’t, and then goes on to claim that a classification system is a bad one if the words it uses to classify objects aren’t projectable.

      1.35 Here’s a second example. You notice that whenever you drop something heavy on your bare foot, like a laptop computer, it hurts quite a lot. You also notice that whenever you drop lighter things on your bare foot, such as a shoe or a pencil, it hurts a lot less. On the basis of these observations, you conclude that heavier things falling on bare feet tend to hurt more than lighter things falling on bare feet. (You should probably also conclude that you need to wear shoes more often.) You definitely believe this conclusion: were you forced to choose between dropping a feather on your foot or a piano, you know which one you’d choose. But you haven’t observed every possible object that could be dropped on your foot in order to assess how painful that experience would be. You are prepared to form a very general belief on the basis of a very limited number of observations, and you take yourself to be perfectly rational in doing this.

      1.36 The general pattern of reasoning we seem to be using in these situations is the following. Whenever we encounter a sufficiently large sample of things that each have a certain feature F, and each member of this sample also has the feature G, we generalize and believe that all things that have F also have G. Philosophers call this kind of reasoning “inductive generalization,” and the method of deriving conclusions in this way, “induction.” It’s hard to see how we can get by in the world if we aren’t justified in believing the conclusions of inductive generalizations. How do I know that this bread will nourish me rather than cause me to explode? Because every time I have sampled bread in the past, it has nourished me rather than caused explosions. My sample size is limited but I nonetheless conclude that I’ll be ok next time I have a sandwich.

      1.39 Here’s the new riddle of induction. We haven’t seen absolutely all of the emeralds in the world. Yet we have seen a large sample of them. And all of the ones that we have seen have