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Empirical justification is the justification for our beliefs that is grounded in experience. In this dissertation, I defend three aspects of empirical justification that stem from Descartes' epistemological framework: foundationalism, individualism, and the epistemic privilege of experiences. Chapter 1 is an overview of the dissertation. Chapter 2 argues that contemporary theorists have overstated the case against the epistemic privilege of experiences, though I point out that there are compelling reasons for thinking this connection ought to be understood in a fallibilistic manner. Chapter 3 discusses contemporary theories of evidence and proposes a Cartesian-inspired account of evidence. Chapter 4 turns the typical discussion of skepticism and empirical justification on its head: instead of explaining how ordinary beliefs are justified in the face of skeptical threats, I aim to explain the structure of justified beliefs in skeptical threats given the falsity of skepticism qua philosophical doctrine. Chapter 5 discusses a plethora of morally loaded and ideological cases that are sometimes invoked in an attempt to cast doubt on individualistic accounts of epistemic justification. After critically analyzing these cases, I advance an individualistic theory that accommodates them.

Most people think that empathy is a valuable trait, that (all things equal) an empathetic person is a good person. Recently this idea has been challenged by psychologists and philosophers who are worried by findings that indicate a general tendency to empathize more reliably with people who are similar to us than those who are not. This strikes a blow to those who would have hoped that empathy is precisely the sort of thing that can bridge difference. In this dissertation, I aim to challenge the implicit notion that empathy’s value comes from its usefulness as a tool. Empathy can be a tool, true, but it is not just that. It is a way of relating to others that is valuable for what it is and, perhaps, what it expresses, in addition to what it does. In Chapter 1, I aim to provide an answer to the titular question: “How Should We Think About Empathy?” The first answer is that we should think about it in terms of what I call the AAA Model, which is to say, we should understand empathy as having an attention-attribution-acquisition structure. When we empathize, we first attend to affective indicators, then make an emotion attribution on the basis of those indicators, before finally acquiring an isomorphic emotional state in virtue of making the attribution. This structure allows for plenty of flexibility, and I therefore describe this way of conceptualizing empathy as a generic approach, a framework within which other theorists could be narrower in their conceptions of empathy according to their aims and preferences. Crucially, I also argue that we should think of empathy as one of a number of fellow feelings – affective responses that bear variations on an attention-attribution-acquisition structure. In Chapter 2, “Reasons for Empathy,” I introduce a way of thinking about empathy non-instrumentally through the concept of fittingness. The recent literature in philosophy of emotion has converged on a separation between fitting and non-fitting (i.e., value-based, instrument

I defend the surprising claim that scientists often do—and always should—reason about complex adaptive systems as if they were bound by normative standards that exist independently of (a) the scientists’ own normative commitments and (b) the actual features of the complex adaptive systems (including their normative commitments, if they’re capable of such). Following David Enoch, I refer to such standards as “robustly normative”. Chapters 1 and 2 show that molecular biologists and neuroethologists reason as though certain kinds of functions and mechanisms, respectively, are robustly normative. Chapters 3 and 4 show that (a) psychologists who study logical and moral reasoning, respectively, do not reason as though rationality were robustly normative and (b) this creates deep problems that cannot be solved unless they do reason as though rationality were robustly normative. Through my dissertation, I suggest an even stronger, metaphysical claim: that scientists always should reason about complex adaptive systems as if they were bound by robust norms because they are, in fact, bound by robust norms. Chapter 1 develops a template for this argument: it explains how normativity emerges from the causal structure of the photoreceptor protein rhodopsin and argues that this emergent structure licenses the kinds of explanatory roles that normativity plays in the complexity sciences. Future work will modify this template for the other explanatory roles that I attribute to norms in Chapters 2–4.

In the philosophy of science, there have been a number of attempts to characterize high-level phenomena as patterns in lower-level phenomena. In computer science, there has been a great deal of effort devoted to recognizing patterns and to representing those patterns using formal models. This dissertation engages with the philosophical literature on patterns from a perspective informed by relevant work in computer science. My aim is not to correct philosophers' errors or misconceptions by appeal to results in computer science---though that may occasionally be appropriate. Rather, my aim is to bolster the philosophical literature by introducing helpful conceptual tools drawn from fields like machine learning, computational modeling, pattern recognition, and algorithmic information theory. As I argue, these conceptual tools allow us to place pattern-based accounts of non-fundamental ontology (esp. Dennett, 1991) on a firmer theoretical foundation. More concretely, I propose a novel, rigorous, and scientifically-informed criterion for the reality of patterns in the physical world. I also propose a more general approach to understanding non-fundamental ontology using ideas from machine learning, such as features and feature selection. This approach to non-fundamental ontology, I argue, will allow us to better understand scientific modeling, inter-level relations, scientific reduction, and other important issues in the philosophy of science.

There is something that it is like to be us as we go about our waking and dreaming lives. There is something that it is like to see red, to feel a pressure, or to taste hot coffee. Each of our experiences has a phenomenal character. Our conscious experiences also represent the world around us; they have representational or intentional contents. An experience as of a moderate pressure against one’s shin represents a force being exerted against that part of one’s body. If there is a force of that degree at that location, then the experience is accurate; otherwise, it is inaccurate. In addition to representing the world around us, we also represent the phenomenal characters of our experiences by thinking about them. We can prefer some experiences to others, for instance. This dissertation concerns the role of phenomenal consciousness in the representational mind. It explores the connections between what our experiences are like, what those experiences represent, and how we think about those experiences. In particular, it explores various structural connections between the phenomenal characters and intentional contents of our mental states. In ‘The Price of Twin Earth’, I consider the extent to which the representational contents of our perceptual experiences are reflected in their phenomenal characters. I do so by taking the debate between liberals and conservatives about the contents of perceptual experience as a case study and showing how to generalize those results. Liberals claim that our perceptual experiences (a) can represent specific, familiar individuals and kinds as such, and (b) that these representations are reflected in the phenomenal characters of our perceptual experiences: those of our perceptual experiences that represent their object as being one familiar individual or kind differ in their phenomenal character from those that represent their object as being a different individual or kind or that do not represent their object as being a familiar indivi