Ioannis G. Ntagkas

This paper develops a new argument from consciousness to theism: the argument from psychophysical harmony. Roughly, psychophysical harmony consists in the fact that phenomenal states are correlated with physical states and with one another in strikingly fortunate ways. For example, phenomenal states are correlated with behavior and functioning that is justified or rationalized by those very phenomenal states, and phenomenal states are correlated with verbal reports and judgments that are made true by those very phenomenal states. We argue that psychophysical harmony is strong evidence for theism (or, at least, strong evidence against atheism in its standard naturalistic form).

The evolutionary argument is an argument against epiphenomenalism, designed to show that some mind-body theory that allows for the efficacy of qualia is true. First developed by Herbert Spencer and William James, the argument has gone through numerous incarnations and it has been criticized in a number of different ways. Yet many have found the criticisms of the argument in the literature unconvincing. Bearing this in mind, I examine two primary issues: first, whether the alleged insights employed in traditional versions of the argument have been correctly and consistently applied, and second, whether the alleged insights can withstand critical scrutiny. With respect to the first issue, I conclude that the proponents of the argument have tended to grossly oversimplify the considerations involved, incorrectly supposing that the evolutionary argument is properly conceived as a non-specific argument for the disjunction of physicalism and interactionist dualism and against epiphenomenalism. With respect to the second issue, I offer a new criticism that decisively refutes all arguments along the lines of the one I present. Finally, I draw positive lessons about the use of empirical considerations in debates over the mind-body problem.

This paper rejects an argument defending the view that the boundary between deception and manipulation is such that some manipulations intended to cause false beliefs count as non-deceptive. On the strongest version of this argument, if a specific behaviour involves compromising the victim’s reasoning, then the behaviour is manipulative but not deceptive, and if it involves exposing the victim to misleading evidence that justifies her false belief, then it is deceptive but not manipulative. This argument has been consistently used as a reason to reject the traditional analysis of human deception, according to which intentionally causing someone to acquire a false belief is sufficient for deception. And because the traditional analysis is also consistent with our most basic intuitions about deception, it does matter whether this argument succeeds.

A satisfactory analysis of human deception must rule out cases where it is a mistake or an accident that person B was misled by person A's behavior. Therefore, most scholars think that deceivers must intend to deceive. This article argues that there is a better solution: rather than appealing to the deceiver's intentions, we should appeal to the function of their behavior. After all, animals and plants engage in deception, and most of them are not capable of forming intentions. Accordingly, certain human behavior is deceptive if and only if its function is to mislead. This solves our problem because if the function of A's behavior was to mislead, B's ending up misled was not an accident or a mere mistake even if A did not intend to deceive B.

This paper examines the connection between lies, deception, and self-deception. Understanding this connection is important because the consensus is that you cannot deceive yourself by lying since you cannot make yourself believe as true a proposition you already believe is false – and, as a liar, you must assert a proposition you believe is false. My solution involves refining our analysis of lying: people can lie by asserting what they confidently believe is true. Thus, self-deceivers need not replace one belief with another; rather, they may just increase existing credence in a proposition they already believe is true.

In their paper published in 2017 in Philosophical Psychology, Ronja Rutschmann and Alex Wiegmann introduce a novel kind of lies, the indifferent lies. According to them, these lies are not intended to deceive simply because the liars do not care whether their audience is going to believe them or not. It seems as if indifferent lies avoid the objections raised against other kinds of lies supposedly not intended to deceive. I argue that this is not correct. Indifferent lies, too, are either intended to deceive or are not lies at all, since they do not involve genuine assertions

We conducted two experiments to determine whether common folk think that so-called _tell-tale sign_ bald-faced lies are intended to deceive—since they have not been tested before. These lies involve tell-tale signs (e.g. blushing) that show that the speaker is lying. Our study was designed to avoid problems earlier studies raise (these studies focus on a kind of bald-faced lie in which supposedly everyone knows that what the speaker says is false). Our main hypothesis was that the participants will think that the protagonists from our examples lied without intending to deceive, and the results of our surveys confirmed this hypothesis: most of our participants rated tell-tale sign lies as lies not intended to deceive. Therefore, our analysis suggests that common folk think that some lies are not intended to deceive.

This article defends the view that liars need not intend to deceive. I present common objections to this view in detail and then propose a case of a liar who can lie but who cannot deceive in any relevant sense. I then modify this case to get a situation in which this person lies intending to tell his hearer the truth and he does this by way of getting the hearer to recognize his intention to tell the truth by lying. This case, and further cases that I develop from it, demonstrate that lying without the intention to deceive is possible.

A number of arguments purport to show that vague properties determine sharp boundaries at higher orders. That is, although we may countenance vagueness concerning the location of boundaries for vague predicates, every predicate can instead be associated with precise knowable cut-off points deriving from precision in their higher order boundaries. I argue that this conclusion is indeed paradoxical, and identify the assumption responsible for the paradox as the Brouwerian principle B for vagueness: that if p then it's determinate that it's not determinate that not p. Other paradoxes which do not appear to turn on B turn instead on some subtle issues concerning the relation between assertion, belief and higher order vagueness. In this paper a theory of assertion, knowledge and logic is outlined which allows one to avoid any kind of higher order precision. A class of realistic models containing counterexamples to B and a number of weakenings of B are introduced and its logic is shown to support vagueness at every order.

Virtue epistemology is a diverse and flourishing field, one of the most exciting developments in epistemology to emerge over the last three decades. Virtue epistemology begins with the premise that epistemology is a normative discipline and, accordingly, a central task of epistemology is to explain the sort of normativity that knowledge, justified belief, and the like involve. A second premise is that a focus on the intellectual virtues (individual intellectual excellences) is essential to carrying out this central task. This collection offers some of the most influential and agenda-setting work at the heart of virtue epistemology's research program. Taken together, they will equip the reader to enter the ongoing discussion and debate in the field. The selections range from seminal contributions by Ernest Sosa, who introduced the notion of intellectual virtue into the contemporary literature, to a study of "epistemic justice" that draws on _To Kill a Mockingbird_ and The Talented Mr. Ripley. The readings include overviews of the field that also serve to advance the discussion; investigations of the nature of knowledge; reflections on the value of knowledge; examinations of credit and luck; and explorations of future directions for research. The hardcover edition does not include a dust jacket.

EPISTEMOLOGY “This is a superb companion to Epistemology: An Anthology. It consists of sixty commentaries, one for each of the sixty entries in that anthology. Turri is an extremely lucid writer, with a wonderful knack for finding and laying out argumentative structure, and for explaining crucial concepts. His commentary will greatly aid student comprehension and enhance class discussion.” Ernest Sosa, Rutgers University “Turri’s discussions are engaging and lucid. They are written for beginning students and will serve that purpose beautifully, but they are so well done that even veteran epistemologists will find them helpful.” John Greco, Saint Louis University Epistemology: A Guide is a straightforward and accessible introduction to contemporary epistemology for those studying the topic for the first time. It introduces and explains the main arguments of the most influential publications in the field from the last 50 years. Balancing simplicity of argument with accuracy and detail, this guide covers the central topics of theory of knowledge, including skepticism, epistemic justification, epistemic closure, virtue epistemology, and naturalized epistemology. Instead of artificially treating themes in isolation, it provides a clear context for key topics and concepts. Designed to stand alone or to accompany the second edition of Epistemology: An Anthology (Wiley Blackwell, 2008), this is a deft and concise introduction to a foundational topic in philosophy.

Fully updated with new topics covering the latest developments and debates, the second edition of this highly influential text retains its unique combination of accessibility and originality. Second edition of a highly influential text that has already become a standard in the field, for students and professional researchers alike, due to its impressive line-up of contributors, and its unique combination of accessibility and originality Twenty-six essays in total, covering 13 essential topics Features five new topics that bring readers up to speed on some of the latest developments in the field, and give them a glimpse of where it's headed: Should knowledge come first? Do practical matters affect whether you know? Is virtuous motivation essential to knowing? Can knowledge be lucky? Can evidence be permissive? Substantially updates two other debates: Is there immediate justification? Can belief be justified through coherence alone?

Traditional theories of knowledge explain knowledge in terms of things like justification and belief. Knowledge-first theories of justification and belief explain justification and belief in terms of knowledge. When epistemologists ask whether knowledge "comes first," they are asking whether traditional theories of knowledge take the right approach, or whether knowledge-first theories of things like justification and belief take the right approach. In her contribution to this debate, Mona Simion defends knowledge-first epistemology by defending a knowledge-first theory of belief and using this theory of belief to motivate a knowledge-first theory of justification. In his contribution to this debate, Aidan McGlynn defends traditional epistemology by critiquing Simion's knowledge-first theory of belief. As Simion and McGlynn both recognize, Simion's argument depends on the idea that beliefs that do not amount to knowledge are epistemically defective. While Simion thinks this is plausible, McGlynn thinks we can produce examples of epistemically non-defective beliefs that do not amount to knowledge. As McGlynn acknowledges, his contribution to the debate does not provide a traditional theory of knowledge in place of Simion's knowledge-first theories of justification and belief. However, if McGlynn is right that we can produce examples of epistemically non-defective beliefs that do not amount to knowledge, this casts doubt on at least one central idea in knowledge-first epistemology: that knowledge has explanatory priority over belief.

Although Kant envisaged a prominent role for logic in the argumentative structure of his Critique of pure reason [12], logicians and philosophers have generally judged Kant’s logic negatively. What Kant called ‘general’ or ‘formal’ logic has been dismissed as a fairly arbitrary subsystem of first order logic, and what he called ‘transcendental logic’ is considered to be not a logic at all: no syntax, no semantics, no definition of validity. Against this, we argue that Kant’s ‘transcendental logic’ is a logic in the strict formal sense, albeit with a semantics and a definition of validity that are vastly more complex than that of first order logic. The main technical application of the formalism developed here is a formal proof that Kant’s Table of Judgements in §9 of the Critique of pure reason, is indeed, as Kant claimed, complete for the kind of semantics he had in mind. This result implies that Kant’s ’general’ logic is after all a distinguished subsystem of first order logic, namely what is known as geometric logic.

The central claim of normative pragmatism is that intentional states can be explained in terms of participation in practices. My aim in this paper is not so much to defend this claim as to rearticulate it in a different medium: the medium of computation. I describe two computer programs in which this claim is re-expressed. The first is the latest version of THE SIMS, in which participation in practices enables the Sims to do and understand more. The second is a prototype simulation of philosophical debate. In this second program, normative pragmatism is expressed at two different levels: once as the theory powering the implementation, and once as a set of claims which are debated by the simulated philosophers. Here, a philosophical theory is used to implement a system in which that very same theory is articulated, challenged, and justified.

We are able to participate in countless different sorts of social practice. This indefinite set of capacities must be explainable in terms of a finite stock of capacities. This paper compares and contrasts two different explanations. A standard decomposition of the capacity to participate in social practices goes something like this: the interpreter arrives on the scene with a stock of generic practice-types. He looks at the current scene to fill-in the current tokens of these types. He looks at the current state of these practice tokens to see what actions are available to him. He uses his current desires to choose between these various possible actions. I argue that this standard explanation is defective, drawing on arguments by Searle and Wittgenstein and Garfinkel. I propose an alternative explanation, in which the participants must continually show each other the state of the scene in order to maintain the scene’s intelligibility. I provide a simple formal language in which to describe this alternative approach, in which we can state quite precisely what someone is doing when they participate in a practice. This language is related to both deontic and epistemic logics, but it is much simpler – it does not include the classic propositional connectives, and it is driven by a very different set of assumptions. The inspirations for this formal language are Searle’s analysis of directions of fit, Wittgenstein’s remarks on rule-following and Garfinkel’s ethnomethodology.

Research in multi-agent systems typically assumes a regulative model of social practice. This model starts with agents who are already capable of acting autonomously to further their individual ends. A social practice, according to this view, is a way of achieving coordination between multiple agents by restricting the set of actions available. For example, in a world containing cars but no driving regulations, agents are free to drive on either side of the road. To prevent collisions, we introduce driving regulations, insisting that everyone drives on the left hand side of the road. We accept this limitation on our freedom because it lowers the probability of a collision. This paper describes AI systems that are based on the constitutive view of social practice. According to this alternative view, there are certain actions that are only available to the agent because he is participating in a practice of a certain sort. For example, you can swing a peculiarly shaped piece of wood without participating in any particular practice - but this action will only constitute a strike if you are participating in a game of baseball. I can raise my hand whenever I like, but this only counts as voting for the motion within the institution of voting. But not all the examples are from frivolous, optional or institutional activities. Sellars and Brandom argue that even the fundamental act of assertion is only possible within the context of a particular social practice: the Game of Giving and Asking for Reasons. The constitutive view, which is familiar to philosophers, is relatively unknown within the AI community. The central aim of this paper is to show how the constitutive view of practice can be put to use in AI applications.

In this paper, I reinterpret Kant’s Transcendental Analytic as a description of a cognitive architecture. I describe a computer implementation of this architecture, and show how it has been applied to two unsupervised learning tasks. The resulting program is very data efficient, able to learn from a tiny handful of examples. I show how the program achieves data-efficiency: the constraints described in the Analytic of Principles are reinterpreted as strong prior knowledge, constraining the set of possible solutions.

This paper formalizes part of the cognitive architecture that Kant develops in the Critique of Pure Reason. The central Kantian notion that we formalize is the rule. As we interpret Kant, a rule is not a declarative conditional stating what would be true if such and such conditions hold. Rather, a Kantian rule is a general procedure, represented by a conditional imperative or permissive, indicating which acts must or may be performed, given certain acts that are already being performed. These acts are not propositions; they do not have truth-values. Our formalization is related to the input/ output logics, a family of logics designed to capture relations between elements that need not have truth-values. In this paper, we introduce KL3 as a formalization of Kant’s conception of rules as conditional imperatives and permissives. We explain how it differs from standard input/output logics, geometric logic, and first-order logic, as well as how it translates natural language sentences not well captured by first-order logic. Finally, we show how the various distinctions in Kant’s much-maligned Table of Judgements emerge as the most natural way of dividing up the various types and sub-types of rule in KL3. Our analysis sheds new light on the way in which normative notions play a fundamental role in the conception of logic at the heart of Kant’s theoretical philosophy.

This paper attempts to answer a central question in unsupervised learning: what does it mean to “make sense” of a sensory sequence? In our formalization, making sense involves constructing a symbolic causal theory that both explains the sensory sequence and also satisfies a set of unity conditions. The unity conditions insist that the constituents of the causal theory – objects, properties, and laws – must be integrated into a coherent whole. On our account, making sense of sensory input is a type of program synthesis, but it is unsupervised program synthesis. Our second contribution is a computer implementation, the Apperception Engine, that was designed to satisfy the above requirements. Our system is able to produce interpretable human-readable causal theories from very small amounts of data, because of the strong inductive bias provided by the unity conditions. A causal theory produced by our system is able to predict future sensor readings, as well as retrodict earlier readings, and impute (fill in the blanks of) missing sensory readings, in any combination. In fact, it is able to do all three tasks simultaneously. We tested the engine in a diverse variety of domains, including cellular automata, rhythms and simple nursery tunes, multi-modal binding problems, occlusion tasks, and sequence induction intelligence tests. In each domain, we test our engine's ability to predict future sensor values, retrodict earlier sensor values, and impute missing sensory data. The Apperception Engine performs well in all these domains, significantly out-performing neural net baselines. We note in particular that in the sequence induction intelligence tests, our system achieved human-level performance. This is notable because our system is not a bespoke system designed specifically to solve intelligence tests, but a general-purpose system that was designed to make sense of any sensory sequence.

How should a machine intelligence perform unsupervised structure discovery over streams of sensory input? One approach to this problem is to cast it as an apperception task [1]. Here, the task is to construct an explicit interpretable theory that both explains the sensory sequence and also satisfies a set of unity conditions, designed to ensure that the constituents of the theory are connected in a relational structure. However, the original formulation of the apperception task had one fundamental limitation: it assumed the raw sensory input had already been parsed using a set of discrete categories, so that all the system had to do was receive this already-digested symbolic input, and make sense of it. But what if we don't have access to pre-parsed input? What if our sensory sequence is raw unprocessed information? The central contribution of this paper is a neuro-symbolic framework for distilling interpretable theories out of streams of raw, unprocessed sensory experience. First, we extend the definition of the apperception task to include ambiguous (but still symbolic) input: sequences of sets of disjunctions. Next, we use a neural network to map raw sensory input to disjunctive input. Our binary neural network is encoded as a logic program, so the weights of the network and the rules of the theory can be solved jointly as a single SAT problem. This way, we are able to jointly learn how to perceive (mapping raw sensory information to concepts) and apperceive (combining concepts into declarative rules).

In this paper, I attempt to address a fundamental challenge for machine intelligence: to understand whether and how a machine’s internal states and external outputs can exhibit original non-derivative intentionality. This question has three aspects. First, what does it take for a machine to exhibit original de dicto intentionality? Second, what does it take to exhibit original de re intentionality? Third, what is required for the machine to defer to the external objective world by respecting the word-to-world direction of fit? I attempt to answer the first challenge by providing a constitutive counts-as understanding of de dicto intentionality. This analysis involves repurposing Kant’s vision of a self-legislating agent as a specification of a machine that reprograms itself. I attempt to answer the second and third challenges by extending Kant’s synchronic model of de dicto intentionality with Brandom’s interpretation of Hegel’s diachronic model of de re intentionality, using Hegel’s notion of recollection to provide an understanding of what is involved in achieving deference to the external world.

The psychology of belief in the paranormal has often been used to stigmatize believers but it has also been used with a more open-minded approach. This paper describes some research of this kind in which believers were found to report more mystical experience, have more creative personalities, report more manic and depressive experience, and more magical ideation, unwittingly suggesting a link with bipolar disorder and schizotypal personality. In addition, however, these six variables were all found to correlate positively and significantly with each other. The positive manifold suggested a single underlying factor, which indeed emerged from principal components analysis. It was speculated that the underlying factor was “transliminality”—a gating mechanism modulating the flow of information and affect from subliminal levels into supraliminal. Later studies have not as clearly confirmed the existence of the positive manifold but nevertheless the concept of transliminality may be a useful one for understanding paranormal experience and hence paranormal belief