Explaining the connection, if any, between simplicity and truth is among the deepest problems facing the philosophy of science, statistics, and machine learning. Say that an efficient truth finding method minimizes worst case costs en route to converging to the true answer to a theory choice problem. Let the costs considered include the number of times a false answer is selected, the number of times opinion is reversed, and the times at which the reversals occur. It is demonstrated that (1) (...) always choosing the simplest theory compatible with experience, and (2) hanging onto it while it remains simplest, is both necessary and sufficient for efficiency. †To contact the author, please write to: Department of Philosophy, Carnegie Mellon University, Baker Hall 135, Pittsburgh, PA 15213-3890; e-mail: [email protected]. (shrink)

A widespread assumption in experimental comparative cognition is that, barring compelling evidence to the contrary, the default hypothesis should postulate the simplest cognitive ontology consistent with the animal’s behavior. I call this assumption the principle of cognitive simplicity . In this essay, I show that PoCS is pervasive but unjustified: a blanket preference for the simplest cognitive ontology is not justified by any of the available arguments. Moreover, without a clear sense of how cognitive ontologies are to be carved up (...) at the joints—and which tools are appropriate for the job—PoCS rests on shaky conceptual ground. (shrink)

The charge that anthropomorphizing nonhuman animals is a fallacy is itself largely misguided and mythic. Anthropomorphism in the study of animal behavior is placed in its original, theological context. Having set the historical stage, I then discuss its relationship to a number of other, related issues: the role of anecdotal evidence, the taxonomy of related anthropomorphic claims, its relationship to the attribution of psychological states in general, and the nature of the charge of anthropomorphism as a categorical claim. I then (...) argue that the categorical reading of anthropomorphism cannot work and that it misrepresents what is being claimed when one claims that traits are shared between humans and nonhumans. We should think of such claims not as anthropomorphic per se– because that implies the trait is intrinsically human and only derivatively nonhuman. Instead, traits shared with mammals are mammalomorphic, for example, or primatomorphic when shared by primates. (shrink)

In the context of animal cognitive research, anthropomorphism is defined as the attribution of uniquely human mental characteristics to animals. Those who worry about anthropomorphism in research, however, are immediately confronted with the question of which properties are uniquely human. One might think that researchers must first hypothesize the existence of a feature in an animal before they can, with warrant, claim that the property is uniquely human. But all too often, this isn't the approach. Rather, there is an a (...) priori argument against attributing some properties to animals. Which features are thought to be uniquely human on a priori grounds? The class can be quite large, including psychological states such as beliefs and desires, personality traits such as confidence or timidity, emotions such as happiness or anger, social organizational properties such as culture or friendship, moral behavior such as punishment or rape. For convenience, I will refer to the members of the class as "psychological properties". One critic includes feeling, purpose, intentionality, consciousness, and even cognition in his list of psychological properties that are incorrectly attributed to animals (Kennedy 1992). Among the critics, there is quite a bit of disagreement about what counts as an anthropomorphic attribution, and this alone should raise questions about the charge. We can identify two different questions about the practice of attributing psychological properties to animals within a scientific context. First we can ask whether it is scientifically respectable to examine questions about the mental, psychological, cultural, etc. states of animals. Those who bemoan anthropomorphism think that we ought not even ask such questions. I will look at the worries about asking the question, and argue that there is no special problem with it. The second question arises with an affirmative answer to the first. Given that it is scientifically respectable to examine whether an animal has a psychological property, there must be some scientifically respectable method for doing the examination.. (shrink)

I propose that empirical procedures, like computational procedures, are justified in terms of truth-finding efficiency. I contrast the idea with more standard philosophies of science and illustrate it by deriving Ockham's razor from the aim of minimizing dramatic changes of opinion en route to the truth.

Neyman-Pearson methods in statistics distinguish between Type I and Type II errors. Through rigid control of Type I error, the "null" hypothesis typically receives the benefit of the doubt. I compare philosophers' interpretations of this feature of Neyman-Pearson tests with interpretations given in statistics textbooks. The pragmatic view of the tests advocated by Neyman, largely rejected by philosophers, lives on in many textbooks. Birnbaum thought the pragmatic view has a useful "heuristic" role in understanding testing. I suggest that it may (...) have the opposite effect. (shrink)

I document some of the main evidence showing that E. S. Pearson rejected the key features of the behavioral-decision philosophy that became associated with the Neyman-Pearson Theory of statistics (NPT). I argue that NPT principles arose not out of behavioral aims, where the concern is solely with behaving correctly sufficiently often in some long run, but out of the epistemological aim of learning about causes of experimental results (e.g., distinguishing genuine from spurious effects). The view Pearson did hold gives a (...) deeper understanding of NPT tests than their typical formulation as accept-reject routines, against which criticisms of NPT are really directed. The Pearsonian view that emerges suggests how NPT tests may avoid these criticisms while still retaining what is central to these methods: the control of error probabilities. (shrink)

Despite its widespread use in science, the Neyman-Pearson Theory of Statistics (NPT) has been rejected as inadequate by most philosophers of induction and statistics. They base their rejection largely upon what the author refers to as after-trial criticisms of NPT. Such criticisms attempt to show that NPT fails to provide an adequate analysis of specific inferences after the trial is made, and the data is known. In this paper, the key types of after-trial criticisms are considered and it is argued (...) that each fails to demonstrate the inadequacy of NPT because each is based on judging NPT on the grounds of a criterion that is fundamentally alien to NPT. As such, each may be seen to either misconstrue the aims of NPT, or to beg the question against it. (shrink)

In Philosophical Problems of Statistical Inference, Seidenfeld argues that the Neyman-Pearson (NP) theory of confidence intervals is inadequate for a theory of inductive inference because, for a given situation, the 'best' NP confidence interval, [CIλ], sometimes yields intervals which are trivial (i.e., tautologous). I argue that (1) Seidenfeld's criticism of trivial intervals is based upon illegitimately interpreting confidence levels as measures of final precision; (2) for the situation which Seidenfeld considers, the 'best' NP confidence interval is not [CIλ] as Seidenfeld (...) suggests, but rather a one-sided interval [CI0]; and since [CI0] never yields trivial intervals, NP theory escapes Seidenfeld's criticism entirely; (3) Seidenfeld's criterion of non-triviality is inadequate, for it leads him to judge an alternative confidence interval, [CI alt. ], superior to [CIλ] although [CI alt. ] results in counterintuitive inferences. I conclude that Seidenfeld has not shown that the NP theory of confidence intervals is inadequate for a theory of inductive inference. (shrink)

This paper discusses Kevin Kelly’s recent attempt to justify Ockham’s Razor in terms of truth-finding efficiency. It is argued that Kelly’s justification fails to warrant confidence in the empirical content of theories recommended by Ockham’s Razor. This is a significant problem if, as Kelly and many others believe, considerations of simplicity play a pervasive role in scientific reasoning, underlying even our best tested theories, for the proposal will fail to warrant the use of these theories in practical prediction.