<p>My dissertation is about good arguments and why they fail to persuade. Besides being a common experience of everyday life, this is an old worry of Plato's that continues to motivate two contemporary lines of research. The first concerns what makes something a good argument, and the second concerns what a mind must be like to be moved by one. Together, these lines guide my project and divide it into two parts. Part I is about good reasons, specifically epistemic reasons. In my first chapter, I defend epistemic instrumentalism, the position that epistemic reasons are good reasons only relative to one's epistemic preferences. I acknowledge that epistemic instrumentalism opens the door to a terrible proliferation of incompatible preferences, but claim that this is merely a potential problem, and not an actual problem to be solved. In my second chapter, I discuss the nature of reasonhood, and argue, contrary to orthodoxy, that there is no compelling reason to accept the skeptic's claim that, because of the inconsistency of three very basic epistemic preferences, it is impossible for any position to be conclusively safe to hold. Part II is about immovable minds. Immovable minds are minds that are unpersuaded by good reasons. In my third chapter, I argue that for good reasons to be persuasive, the properties that make them good reasons must be identified, through habituation, with other desirable qualities like pleasure or success. Identifying the merits of good reasons with other rewards cultivates intellectual character, and intellectual character, as I argue in my final chapter, remains worth cultivating, notwithstanding situationist doubts about the existence of character and intuitionist concerns about human rationality.</p> / Dissertation

The idea that humans are prone to widespread and systematic biases has dominated the psychological study of thinking and decision-making. The conclusion that has often been drawn is that people are irrational. In recent decades, however, a number of psychologists have started to call into question key claims and findings in research on human biases. In particular, a body of research has come together under the heading of adaptive rationality (henceforth AR). AR theorists argue that people should not be assessed against formal principles of rationality but rather against the goals they entertain. Moreover, AR theorists maintain that the conclusion that people are irrational is unsupported: people are often remarkably successful once assessed against their goals and given the cognitive and external constraints imposed by the environment. The growth of literature around AR is what motivates the present investigation, and assessing the plausibility of the AR challenge to research on human biases is the goal of this thesis. My enquiry analyses several aspects of this suggested turn in the empirical study of rationality and provides one of the first philosophically-informed appraisals of the prospects of AR. First and foremost, my thesis seeks to provide a qualified defence of the AR project. On the one hand, I agree with AR theorists that there is room for a conceptual revolution in the study of thinking and decision-making: while it is commonly argued that behaviour and cognition should be assessed against formal principles of rationality, I stress the importance of assessing behaviour against the goals that people entertain. However, I also contend that AR theorists have hitherto failed to provide compelling evidence in support of their most ambitious and optimistic theses about people’s rationality. In particular, I present a great deal of evidence suggesting that people are often unsuccessful at achieving prudential and epistemic goals and I argue that AR theorists have not made clear how, in light of this evidence, optimistic claims about human rationality could be defended.

Walking is one of the most commonplace forms of human expressions, yet the forms, motivations, and practices of walking vary greatly and are often at odds with dominant discourses in urban and transportation planning. As interest in pedestrian-oriented studies continues to grow, there is danger that dominant discourses will continue to reinforce the framing of pedestrians and the practices of walking as slower moving versions of the private automobile and ignore deeply embedded emotional, personal, and cognitive aspects. As such, understandings of pedestrian transportation and human agency during walking must be explored in increasingly human-centered terms in order to understand how changes to the material environment actually impact people and daily practices. The purpose of this dissertation is to give considerably more attention to the human elements of walking by creating a set of new theoretical and practical frameworks for deeper representations of the pedestrian in the urban space and within a larger transportation system. The three articles presented in this dissertation outline an alternative, human-centered representation of the pedestrian, providing theoretical, methodological, and practical solutions to conceptualize how soft variables such as emotion, motivation, and especially cognition influence the practices of walking. / 10000-01-01

The attraction effect reveals that people do not compare alternatives independently of one another. Instead, they make comparisons, such that preferences between two alternatives can be reversed by adding or removing otherwise irrelevant alternatives. This behaviour is particularly difficult for rational models of decision making to explain since such models require the independent evaluation of alternatives. As such these models describe preference reversal behaviour as irrational. This thesis examines what rational decision making should look like once a person's cognitive bounds have been taken into account. The key finding is that contextual preference reversals like the attraction effect, far from being irrational, actually result from people making better decisions than they would if they assessed alternatives independently of one another. The research was grouped into three objectives concerning the attraction effect and the rationality of human cognition. The first of these was to identify under what conditions people exhibit the attraction effect, and what consequences the behaviour has for the outcomes they experience. Two experiments revealed that the effect is only exhibited in choice sets where alternatives are approximately equal in value and therefore hard to tell apart. This finding also means that the potential negative consequences of exhibiting the attraction effect are very small, because it only occurs when alternatives are similar in value. The second objective was to develop a computationally rational model of the attraction effect. Computational rationality is an approach that identifies what the optimal behaviour is given the constraints imposed by cognition, and the environment. Our model reveals why people exhibit the attraction effect. With the assumption that people cannot calculate expected value perfectly accurately, the model shows that in choices between prospects, the attraction effect actually results in decisions with a higher expected value. This is because noisy expected value estimates can be improved by taking into account the contextual information provided by the other alternatives in a choice set. The final objective was to provide evidence for our model, and the computational rationality approach, by making a novel prediction. We conducted an experiment to test the model's prediction that the attraction effect should be much reduced in the loss domain. We replicated existing attraction effect studies and extended them to the loss domain. The results replicated previous results in the gain domain and simultaneously revealed the novel finding that people did not exhibit the effect in the loss domain. People exhibit the attraction effect as a result of making the best decision possible given the cognitive resources they have. Understanding decision making as computationally rational can provide deep insights into existing phenomena. The method allows us to ascertain the causal link between cognitive mechanisms, a person's goal, and their decision making.

The literature on bounded rationality and learning in macroeconomics has often used recursive algorithms to depict the evolution of agents' beliefs over time. In this thesis we assess this practice from an applied perspective, focusing on the use of such algorithms for the computation of forecasts of macroeconomic variables. Our analysis develops around three issues we find to have been previously neglected in the literature: (i) the initialization of the learning algorithms; (ii) the determination and calibration of the learning gains, which are key parameters of the algorithms' specifications; and, (iii) the choice of a representative learning mechanism. In order to approach these issues we establish an estimation framework under which we unify the two main algorithms considered in this literature, namely the least squares and the stochastic gradient algorithms. We then propose an evaluation framework that mimics the real-time process of expectation formation through learning-to-forecast exercises. To analyze the quality of the forecasts associated to the learning approach, we evaluate their forecasting accuracy and resemblance to surveys, these latter taken as proxy for agents' expectations. In spite of taking these two criteria as mutually desirable, it is not clear whether they are compatible with each other: whilst forecasting accuracy represents the goal of optimizing agents, resemblance to surveys is indicative of actual agents behavior. We carry out these exercises using real-time quarterly data on US inflation and output growth covering a broad post-WWII period of time. Our main contribution is to show that a proper assessment of the adaptive learning approach requires going beyond the previous views in the literature about these issues. For the initialization of the learning algorithms we argue that such initial estimates need to be coherent with the ongoing learning process that was already in place at the beginning of our sample of data. We find that the previous initialization methods in the literature are vulnerable to this requirement, and propose a new smoothing-based method that is not prone to this critic. Regarding the learning gains, we distinguish between two possible rationales to its determination: as a choice of agents; or, as a primitive parameter of agents learning-to-forecast behavior. Our results provide strong evidence in favor of the gain as a primitive approach, hence favoring the use of surveys data for their calibration. In the third issue, about the choice of a representative algorithm, we challenge the view that learning should be represented by only one of the above algorithms; on the basis of our two evaluation criteria, our results suggest that using a single algorithm represents a misspecification. That motivate us to propose the use of hybrid forms of the LS and SG algorithms, for which we find favorable evidence as representatives of how agents learn. Finally, our analysis concludes with an optimistic assessment on the plausibility of adaptive learning, though conditioned to an appropriate treatment of the above issues. We hope our results provide some guidance on that respect.

In this thesis I argue that emotion is integral to practical rationality, contrary to the dominant tradition that has held that emotions are irrational and dangerous disruptive influences that we’d be better off without. In Chapter 1 I argue that practical rationality consists in doing what one has most normative reason to do, and in Chapter 2 that an agent is practically rational to the extent that she responds to her reasons; this is how she guides her actions in line with the norm of doing what she has most reason to do. This can be done in ways other than by the employment of practical reasoning. In Chapter 3 I argue for a picture of practical reasoning that stands against the division of emotion and rationality. This account makes room for the overwhelming evidence that challenges the traditional view of emotions as the enemy of practical rationality. Chapter 4 gives a brief overview of the philosophical literature of emotions, and their place in practical rationality. In Chapter 5 I argue that emotions provide us with the necessary access to our reasons for action which we need in order to be able to respond to them, and thereby to be practically rational. Further, as I argue in Chapter 6, emotions play vital roles in the process of practical reasoning itself. Thus practical rationality would not be better off without emotion. In Chapter 7 I argue that we should distinguish between two types of incontinent action (acting against ones all things considered judgement about what one has most reason to do) and that one of these – weakness of will – is necessarily irrational, but the other – akrasia – is not. In Chapter 8 I apply my thesis to the question in the practical domain of what it means to ‘lose self-control’ in the context of killing in response to a provocation, which is a defence to murder. I argue that the ‘control’ that is lost is the regulative guiding control characteristic of the reason-responder. Understanding practical agency as reason-responsiveness, and understanding the role that emotions play within it as per my thesis, enables this coherent understanding. Thus I am arguing for neither a pro-emotion nor anti-emotion view of the role of emotion in practical rationality. Emotions should not be seen as either ‘for’ rationality nor ‘against’ rationality: they are simply part of rationality.

<p>NR 20140805</p>

Work with gallery space, painting, objects, and theirs context.

Bayesian Epistemology is a general framework for thinking about agents who have beliefs that come in degrees. Theories in this framework give accounts of rational belief and rational belief change, which share two key features: (i) rational belief states are represented with probability functions, and (ii) rational belief change results from the acquisition of evidence. This dissertation focuses specifically on the second feature. I pose the Evidence Question: What is it to have evidence? Before addressing this question we must have an understanding of Bayesian Epistemology. The first chapter argues that we should understand Bayesian Epistemology as giving us theories that are evaluative and not action-guiding. I reach this verdict after considering the popular ‘ought’-implies-‘can’ objection to Bayesian Epistemology. The second chapter argues that it is important for theories in Bayesian Epistemology to answer the Evidence Question, and distinguishes between internalist and externalist answers. The third and fourth chapters present and defend a specific answer to the Evidence Question. The account is inspired by reliabilist accounts of justification, and attempts to understand what it is to have evidence by appealing solely to considerations of reliability. Chapter 3 explains how to understand reliability, and how the account fits with Bayesian Epistemology, in particular, the requirement that an agent’s evidence receive probability 1. Chapter 4 responds to objections, which maintain that the account gives the wrong verdict in a variety of situations including skeptical scenarios, lottery cases, scientific cases, and cases involving inference. After slight modifications, I argue that my account has the resources to answer the objections. The fifth chapter considers the possibility of losing evidence. I show how my account can model these cases. To do so, however, we require a modification to Conditionalization, the orthodox principle governing belief change. I present such a modification. The sixth and seventh chapters propose a new understanding of Dutch Book Arguments, historically important arguments for Bayesian principles. The proposal shows that the Dutch Book Arguments for implausible principles are defective, while the ones for plausible principles are not. The final chapter is a conclusion.

This project examines concepts and theories of the posthuman, or posthumanism, in contemporary popular and theoretical texts. The term "natural perversions" is an apparent paradox, but one that can point to some of the contradictions inherent in humanism; its use here suggests some of the profound challenges posthuman theory presents to exploitative institutions and power structures based on human privilege. Natural perversions is an attempt to naturalize, in a sense, the notion of perversion, but also to turn the nonnative language of perversion back onto dominant humanist institutions and discourses, especially anthropocentric visions of economics, evolution, and sexuality. Economics, evolution and sexuality are implicated in reiterating and supporting each other in their humanist and anthropocentric attitudes and assumptions. Interrogating humanist assumptions in these three areas of knowledge is increasingly necessary, this study contends, in the face of current environmental, economic and political crises such as pollution, peak oil and global warming. Despite their privileging of a human subject, economics, evolution and sexuality can each be considered inhuman systems from a certain point of view, systems that in the words of Elizabeth Grosz "function beyond or above the control of their participants." This project works to problematize human ideals such as reason and rationality, interrogating whether humans can indeed be distinguished from other beings by their rationality and contending that both man-made and natural economies (such as evolution and sexuality) do not function as rationalized and efficient systems in the ways that human thought has generally envisioned. Humans frequently do not behave in their own rational self interest, a foundational assumption of economic theory. The critical theory and popular texts considered here suggest that exuberant, decadent, luxurious, wasteful, and chaotic systems and economies and natural systems may be paradoxically more productive than highly rationalized ones. / Thesis / Doctor of Philosophy (PhD)