abstracts: table of contents
In approximately reverse chronological order:
Dissertation abstract: Belief-desire coherence
Belief-desire coherence addresses a question central to
normative epistemology - namely, "what makes for good thinking?" My
answer is an epistemic norm that is internal, coherentist, and
computationally amenable. It is designed to draw from (and contribute
to) progress in artificial intelligence and cognitive psychology.
Belief-desire coherence is also, as the name might suggest, ultimately
a pragmatic norm for thinking. The first three chapters of the
dissertation provide positive motivation for my particular epistemic
proposal; the fourth considers more general reasons to prefer such a
pragmatic epistemology over traditional, directly truth-based
accounts.
Chapter one focuses on the controversial topic of epistemic
guidance. I begin by exploring what it is for a creature -
natural or artificial - to be intelligent. Arguing that adaptability
is fundamental to intelligence, and that learning is fundamental to
adaptability, I develop an account of what it is for a creature to
learn to think better. Starting with a functional
characterization of creatures, I argue that for a creature to learn
better thinking requires a feedback mechanism internal to its
cognition. The result is a naturalistic and more precise version of
epistemic guidance - one that captures the fundamental intuitions of
"internal" epistemic norms. This characterization of internal
epistemology suggests, in turn, that the only internally available
standard for better thinking is pragmatic, to do ultimately with
fulfilling the creature's basic aims.
In the second chapter I consider the wishful thinking objection to any
internal pragmatic epistemology, and in response argue for a modified
coherentist approach to the evaluation of both beliefs and desires.
An internally measurable standard of good thoughts, both desire-like
and belief-like, is the level of coherence among them. The proposed
coherence has defeasible foundations in the "default" thoughts that
come with the fundamental design of the creature.
This pragmatic coherence measure, I claim, can provide the internal
feedback required for learning. In the third chapter I show how to
model this coherence and feedback computationally. Then, with the
full theory in place, I outline its several advantages for cognitive
science, accounts of folk psychology and emotions, and even ethics.
Eric Lormand (chair)
Jessica Wilson
James Joyce
Thad Polk (psychology)
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Functions, creatures, learning, emotion: abstract
I propose a conceptual framework for emotions according to which they
are best understood as the feedback mechanism a creature possesses in
virtue of its function to learn. More specifically, emotions can be
neatly modeled as a measure of harmony in a certain kind of constraint
satisfaction problem. This measure can be used as error for weight
adjustment (learning) in an unsupervised connectionist network.
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Internal epistemology as learning: abstract
This paper first unifies different notions of internal epistemology
under the rubric of
epistemic guidance. It then argues that a
naturalistic construal of such epistemic guidance amounts to a
creature's capacity to learn. Learning, in turn, is the performance
of a function to adjust cognitive dispositions toward better
satisfaction of the creature's aims. The resulting learning-based
epistemology not only captures internalist intuitions, but is also
naturalistic in a strong sense, since it is clear how any
information-processing creature could embody it. It also coheres well
with intuitions on
recherché brain-in-vat cases. The
proposed epistemology is, strictly speaking, pragmatic--but this is
argued not to be such a bad thing.
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Analysis, schmanalysis: abstract
The first section of this paper examines a handy, underrated trick in
philosophy. Saul Kripke, for example, employs it in
Naming and
Necessity, when he invents the term 'schmidentity' to argue
indirectly for his favored account of identity. Kripke notes in a
footnote that he wishes someday "to elaborate on the utility of this
device"; I take up this elaboration on his behalf. In the second
section, I apply this trick to unveil an appealing but somewhat
unorthodox picture of conceptual analysis - one according to which it
is a process of determining
what to do with our words. This
picture can recover a naturalistically respectable notion of the
philosopher's task. It can also help resolve debates that turn on the
place of conceptual analysis, such as the recent debate over
consciousness.
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The ethics of robot servitude: abstract
Assume we could someday create artificial creatures with
intelligence comparable to our own. Could it be ethical use them as
unpaid labor? There is very little philosophical literature on this
topic, but the consensus so far has been that such robot servitude
would merely be a new form of slavery. Against this consensus I
defend the permissibility of robot servitude, and in particular the
controversial case of designing robots so that they
want to
serve (more or less particular) human ends. A typical objection to
this case draws an analogy to the genetic engineering of humans: if
designing eager robot servants is permissible, it should also be
permissible to design eager human servants. Few ethical views can
easily explain even the wrongness of such human engineering, however,
and those few explanations that are available break the analogy with
engineering robots. The case turns out to be illustrative of
profound problems in the field of population ethics.
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Construing faith as action won't save Pascal's wager: abstract
Arthur Falk has proposed a new construal of faith according to which
it is not a mere species of belief, but has essential components in
action. This twist on faith promises to resurrect Pascal's Wager,
making faith compatible with reason by believing as the scientist
but acting as the theist. I argue that Falk's proposal leaves
religious faith in no better shape; in particular, it merely
reframes the question in terms of rational desires rather than
rational beliefs.
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Naturalism is (literally) self-explanatory: abstract
Naturalism has more problems than most of us naturalists are willing
to admit. I focus on four serious problems, namely 1) naturalism
itself seems to be an anti-naturalistic position; 2)
contra
naturalism, traditional science seems radically discontinuous with
philosophy; 3) no one seems able to say just what projects are
"naturalistic" in the first place; and 4) it is unclear what
normative force grounds its frequent rhetorical use. I aim to set
the naturalist at ease about these problems by proposing a solution
to them
via three plausible hypotheses, namely 1) naturalism
is a methodological commitment to science; 2) the scientific method
is inference to the best explanation; and 3) explanation is
unification. Among other good results, this position allows
naturalism to be literally self-explanatory.
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