Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.

According to the most popular theories of intentionality, a family of theories we will refer to as “functional intentionality,” a machine can have genuine intentional states so long as it has functionally characterizable mental states that are causally hooked up to the world in the right way. This paper considers a detailed description of a robot that seems to meet the conditions of functional intentionality, but which falls victim to what I call “the composition problem.” One obvious way to escape (...) the problem (arguably, the only way) is if the robot can be shown to be a moral patient – to deserve a particular moral status. If so, it isn’t clear how functional intentionality could remain plausible (something like “phenomenal intentionality” would be required). Finally, while it would have seemed that a reasonable strategy for establishing the moral status of intelligent machines would be to demonstrate that the machine possessed genuine intentionality, the composition argument suggests that the order of precedence is reversed: The machine must first be shown to possess a particular moral status before it is a candidate for having genuine intentionality. (shrink)

Prediction-based decisions, which are often made by utilizing the tools of machine learning, influence nearly all facets of modern life. Ethical concerns about this widespread practice have given rise to the field of fair machine learning and a number of fairness measures, mathematically precise definitions of fairness that purport to determine whether a given prediction-based decision system is fair. Following Reuben Binns (2017), we take ‘fairness’ in this context to be a placeholder for a variety of normative egalitarian considerations. We (...) explore a few fairness measures to suss out their egalitarian roots and evaluate them, both as formalizations of egalitarian ideas and as assertions of what fairness demands of predictive systems. We pay special attention to a recent and popular fairness measure, counterfactual fairness, which holds that a prediction about an individual is fair if it is the same in the actual world and any counterfactual world where the individual belongs to a different demographic group (cf. Kusner et al. (2018)). (shrink)

We propose a formal framework for interpretable machine learning. Combining elements from statistical learning, causal interventionism, and decision theory, we design an idealised explanation game in which players collaborate to find the best explanation for a given algorithmic prediction. Through an iterative procedure of questions and answers, the players establish a three-dimensional Pareto frontier that describes the optimal trade-offs between explanatory accuracy, simplicity, and relevance. Multiple rounds are played at different levels of abstraction, allowing the players to explore overlapping causal (...) patterns of variable granularity and scope. We characterise the conditions under which such a game is almost surely guaranteed to converge on a optimal explanation surface in polynomial time, and highlight obstacles that will tend to prevent the players from advancing beyond certain explanatory thresholds. The game serves a descriptive and a normative function, establishing a conceptual space in which to analyse and compare existing proposals, as well as design new and improved solutions. (shrink)

I distinguish two theses regarding technological successors to current humans (posthumans): an anthropologically bounded posthumanism (ABP) and an anthropologically unbounded posthumanism (AUP). ABP proposes transcendental conditions on agency that can be held to constrain the scope for “weirdness” in the space of possible posthumans a priori. AUP, by contrast, leaves the nature of posthuman agency to be settled empirically (or technologically). Given AUP there are no “future proof” constraints on the strangeness of posthuman agents. -/- In Posthuman Life I defended (...) AUP via a critique of Donald Davidson’s work on intentionality and a “naturalistic deconstruction” of transcendental phenomenology (See also Roden 2013). In this paper I extend this critique to Robert Brandom’s account of the relationship between normativity and intentionality in Making It Explicit (MIE) and in other writings. -/- Brandom’s account understands intentionality in terms of the capacity to undertake and ascribe inferential normative commitments. It makes “first class agency” dependent on the ability to participate in discursive social practices. It implies that posthumans – insofar as they qualify as agents at all – would need to be social and discursive beings. -/- The problem with this approach, I will argue, is that it replicates a problem that Brandom discerns in Dennett’s intentional stance approach. It tells us nothing about the conditions under which a being qualifies as a potential interpreter and thus little about the conditions for meaning, understanding or agency. -/- I support this diagnosis by showing that Brandom cannot explain how a non-sapient community could bootstrap itself into sapience by setting up a basic deontic scorekeeping system without appealing (along with Davidson and Dennett) to the ways in which an idealized observer would interpret their activity. -/- This strongly suggests that interpretationist and pragmatist accounts cannot explain the semantic or the intentional without regressing to assumptions about ideal interpreters or background practices whose scope they are incapable of delimiting. It follows that Anthropologically Unbounded Posthumanism is not seriously challenged by the claim that agency and meaning are “constituted” by social practices. -/- AUP implies that we can infer no claims about the denizens of “Posthuman Possibility Space” a priori, by reflecting on the pragmatic transcendental conditions for semantic content. We thus have no reason to suppose that posthuman agents would have to be subjects of discourse or, indeed, members of communities. The scope for posthuman weirdness can be determined by recourse to engineering alone. (shrink)

Theorem (Will time machines be build?). The probability that in future a time machine that can travel to the past would be build is very low.

The ongoing explosion of interest in artificial intelligence is fueled in part by recently developed techniques in machine learning. Those techniques allow automated systems to process huge amounts of data, utilizing mathematical methods that depart from traditional statistical approaches, and resulting in impressive advancements in our ability to make predictions and uncover correlations across a host of interesting domains. But as is now widely discussed, the way that those systems arrive at their outputs is often opaque, even to the experts (...) who design and deploy them. Is it morally problematic to make use of opaque automated methods when making high-stakes decisions, like whether to issue a loan to an applicant, or whether to approve a parole request? Many scholars answer in the affirmative. However, there is no widely accepted explanation for why transparent systems are morally preferable to opaque systems. We argue that the use of automated decision-making systems sometimes violates duties of consideration that are owed by decision-makers to decision-subjects, duties that are both epistemic and practical in character. Violations of that kind generate a weighty consideration against the use of opaque decision systems. In the course of defending our approach, we show that it is able to address three major challenges sometimes leveled against attempts to defend the moral import of transparency in automated decision-making. (shrink)

4E approaches to affective technology tend to focus on how ‘users’ manage their situated affectivity, analogously to how they help themselves cognitively through epistemic actions or using artefacts and scaffolding. Here I focus on cases where the function of affective technology is to exploit or manipulate the agent engaging with it. My opening example is the cigarette, where technological refinements have harmfully transformed the affective process of consuming nicotine. I proceed to develop case studies of two very different but also (...) harmful affective technologies. Casinos and electronic gambling machines deploy computationally intensive scaffolding to shape the onset and continuation of gambling episodes. High-heeled shoes affectively engineer wearers’ relationships to their own embodied capacities and are predominantly expected to be worn by women. I conclude with a discussion of the need for study of affective technology to focus other-directed applications, some of which will serve competing or antagonistic interests. (shrink)

This book concerns the foundations of epistemic modality and hyperintensionality and their applications to the philosophy of mathematics. David Elohim examines the nature of epistemic modality, when the modal operator is interpreted as concerning both apriority and conceivability, as well as states of knowledge and belief. The book demonstrates how epistemic modality and hyperintensionality relate to the computational theory of mind; metaphysical modality and hyperintensionality; the types of mathematical modality and hyperintensionality; to the epistemic status of large cardinal axioms, (...) undecidable propositions, and abstraction principles in the philosophy of mathematics; to the modal and hyperintensional profiles of the logic of rational intuition; and to the types of intention, when the latter is interpreted as a hyperintensional mental state. Chapter \textbf{2} argues for a novel type of expressivism based on the duality between the categories of coalgebras and algebras, and argues that the duality permits of the reconciliation between modal and hyperintensional cognitivism and modal and hyperintensional expressivism. Elohim develops a novel, topic-sensitive truthmaker semantics for dynamic epistemic logic, and develops a novel, dynamic two-dimensional semantics grounded in two-dimensional hyperintensional Turing machines. Chapter \textbf{3} provides an abstraction principle for two-dimensional (hyper-)intensions. Chapter \textbf{4} advances a topic-sensitive two-dimensional truthmaker semantics, and provides three novel interpretations of the framework along with the epistemic and metasemantic. Chapter \textbf{5} applies the fixed points of the modal $\mu$-calculus in order to account for the iteration of epistemic states in a single agent, by contrast to availing of modal axiom 4 (i.e. the KK principle). The fixed point operators in the modal $\mu$-calculus are rendered hyperintensional, which yields the first hyperintensional construal of the modal $\mu$-calculus in the literature and the first application of the calculus to the iteration of epistemic states in a single agent instead of the common knowledge of a group of agents. Chapter \textbf{6} advances a solution to the Julius Caesar problem based on Fine's `criterial' identity conditions which incorporate conditions on essentiality and grounding. Chapter \textbf{7} provides a ground-theoretic regimentation of the proposals in the metaphysics of consciousness and examines its bearing on the two-dimensional conceivability argument against physicalism. The topic-sensitive epistemic two-dimensional truthmaker semantics developed in chapters \textbf{2} and \textbf{4} is availed of in order for epistemic states to be a guide to metaphysical states in the hyperintensional setting. -/- Chapters \textbf{8-12} provide cases demonstrating how the two-dimensional hyperintensions of hyperintensional, i.e. topic-sensitive epistemic two-dimensional truthmaker, semantics, solve the access problem in the epistemology of mathematics. Chapter \textbf{8} examines the interaction between Elohim's hyperintensional semantics and the axioms of epistemic set theory, large cardinal axioms, the Epistemic Church-Turing Thesis, the modal axioms governing the modal profile of $\Omega$-logic, Orey sentences such as the Generalized Continuum Hypothesis, and absolute decidability. These results yield inter alia the first hyperintensional Epistemic Church-Turing Thesis and hyperintensional epistemic set theories in the literature. Chapter \textbf{9} examines the modal and hyperintensional commitments of abstractionism, in particular necessitism, and epistemic hyperintensionality, epistemic utility theory, and the epistemology of abstraction. Elohim countenances a hyperintensional semantics for novel epistemic abstractionist modalities. Elohim suggests, too, that higher observational type theory can be applied to first-order abstraction principles in order to make first-order abstraction principles recursively enumerable, i.e. Turing machine computable, and that the truth of the first-order abstraction principle for two-dimensional hyperintensions is grounded in its being possibly recursively enumerable and the machine being physically implementable. Chapter \textbf{10} examines the philosophical significance of hyperintensional $\Omega$-logic in set theory and discusses the hyperintensionality of metamathematics. Chapter \textbf{11} provides a modal logic for rational intuition and provides a hyperintensional semantics. Chapter \textbf{12} avails of modal coalgebras to interpret the defining properties of indefinite extensibility, and avails of hyperintensional epistemic two-dimensional semantics in order to account for the interaction between interpretational and objective modalities and the truthmakers thereof. This yields the first hyperintensional category theory in the literature. Elohim invents a new mathematical trick in which first-order structures are treated as categories, and Vopenka's principle can be satisfied because of the elementary embeddings between the categories and generate Vopenka cardinals in the category of Set in category theory. Chapter \textbf{13} examines modal responses to the alethic paradoxes. Elohim provides a counter-example to epistemic closure for logical deduction. Chapter \textbf{14} examines, finally, the modal and hyperintensional semantics for the different types of intention and the relation of the latter to evidential decision theory. (shrink)

Artificial intelligence has historically been conceptualized in anthropomorphic terms. Some algorithms deploy biomimetic designs in a deliberate attempt to effect a sort of digital isomorphism of the human brain. Others leverage more general learning strategies that happen to coincide with popular theories of cognitive science and social epistemology. In this paper, I challenge the anthropomorphic credentials of the neural network algorithm, whose similarities to human cognition I argue are vastly overstated and narrowly construed. I submit that three alternative supervised learning (...) methods—namely lasso penalties, bagging, and boosting—offer subtler, more interesting analogies to human reasoning as both an individual and a social phenomenon. Despite the temptation to fall back on anthropomorphic tropes when discussing AI, however, I conclude that such rhetoric is at best misleading and at worst downright dangerous. The impulse to humanize algorithms is an obstacle to properly conceptualizing the ethical challenges posed by emerging technologies. (shrink)

The term ‘intelligence’ as used in this paper refers to items of knowledge collected for the sake of assessing and maintaining national security. The intelligence community (IC) of the United States (US) is a community of organizations that collaborate in collecting and processing intelligence for the US. The IC relies on human-machine-based analytic strategies that 1) access and integrate vast amounts of information from disparate sources, 2) continuously process this information, so that, 3) a maximally comprehensive understanding of world actors (...) and their behaviors can be developed and updated. Herein we describe an approach to utilizing outcomes-based learning (OBL) to support these efforts that is based on an ontology of the cognitive processes performed by intelligence analysts. Of particular importance to the Cognitive Process Ontology is the class Representation that is Warranted. Such a representation is descriptive in nature and deserving of trust in its veridicality. The latter is because a Representation that is Warranted is always produced by a process that was vetted (or successfully designed) to reliably produce veridical representations. As such, Representations that are Warranted are what in other contexts we might refer to as ‘items of knowledge’. (shrink)

Necessity and sufficiency are the building blocks of all successful explanations. Yet despite their importance, these notions have been conceptually underdeveloped and inconsistently applied in explainable artificial intelligence (XAI), a fast-growing research area that is so far lacking in firm theoretical foundations. Building on work in logic, probability, and causality, we establish the central role of necessity and sufficiency in XAI, unifying seemingly disparate methods in a single formal framework. We provide a sound and complete algorithm for computing explanatory factors (...) with respect to a given context, and demonstrate its flexibility and competitive performance against state of the art alternatives on various tasks. (shrink)

This essay aims to vindicate the thesis that cognitive computational properties are abstract objects implemented in physical systems. I avail of Voevodsky's Univalence Axiom and function type equivalence in Homotopy Type Theory, in order to specify an abstraction principle for epistemic (hyper-)intensions. The homotopic abstraction principle for epistemic (hyper-)intensions provides an epistemic conduit for our knowledge of (hyper-)intensions as abstract objects. Higher observational type theory might be one way to make first-order abstraction principles defined via inference rules, although not higher-order (...) abstraction principles, computable. The truth of my first-order abstraction principle for hyperintensions is grounded in its being possibly recursively enumerable i.e. Turing computable and the Turing machine being physically implementable. Epistemic modality and hyperintensionality can thus be shown to be both a compelling and a materially adequate candidate for the fundamental structure of mental representational states, comprising a fragment of the language of thought. (shrink)

Most accounts of cognitive scaffolding focus on ways that external structure can support or augment an agent’s cognitive capacities. We call cases where the interests of the user are served benign scaffolding and argue for the possibility and reality of hostile scaffolding. This is scaffolding which depends on the same capacities of an agent to make cognitive use of external structure as in benign cases, but that undermines or exploits the user while serving the interests of another agent. We develop (...) criteria for scaffolding being hostile and show by reference to examples including the design features of electronic gambling machines and casino management systems that hostile scaffolding exists and can be highly effective. In cases where the scaffolding is deep and permits the offloading of significant cognitive work, hostile scaffolding exploitatively manipulates cognitive processing itself. Given the extent of human reliance on scaffolding this is an important and neglected vulnerability. [This is an updated version of the paper, added in February 2023.]. (shrink)

In his 1993 article ‘The Coming Technological Singularity: How to survive in the posthuman era’ the computer scientist Virnor Vinge speculated that developments in artificial intelligence might reach a point where improvements in machine intelligence result in smart AI’s producing ever-smarter AI’s. According to Vinge the ‘singularity’, as he called this threshold of recursive self-improvement, would be a ‘transcendental event’ transforming life on Earth in ways that unaugmented humans are not equipped to envisage. In this paper I argue Vinge’s idea (...) of a technologically led intelligence explosion is philosophically important because it requires us to consider the prospect of a posthuman condition succeeding the human one. What is the ‘humanity’ to which the posthuman is ‘post’? Does the possibility of a posthumanity presuppose that there is a ‘human essence’, or is there some other way of conceiving the human-posthuman difference? I argue that the difference should be conceived as a historically emergent disconnection between individuals, not in terms of the presence or lack of essential properties. I also suggest that these individuals should not be conceived in narrow biological terms but in ‘wide’ terms permitting biological, cultural and technological relations of descent between human and posthuman. Finally, I consider the ethical implications of this metaphysics of the posthuman. If, as I claim, the posthuman difference is not one between kinds but between individuals, we cannot specify its nature a priori but only a posteriori. Thus the only way to evaluate the posthuman condition would be to witness the emergence of posthumans. The implications of this are somewhat paradoxical. We are not currently in a position to evaluate the posthuman condition. Since there are no posthumans, the condition of posthumanity is not defined. However, posthumans could result from some iteration of our current technical activity, so we have an interest in understanding what they might be like. It follows that we have an interest in making or becoming posthumans. (shrink)

I argue that the two-dimensional hyperintensions of epistemic topic-sensitive two-dimensional truthmaker semantics provide a compelling solution to the access problem. -/- I countenance an abstraction principle for two-dimensional hyperintensions based on Voevodsky's Univalence Axiom and function type equivalence in Homotopy Type Theory. The truth of my first-order abstraction principle for two-dimensional hyperintensions is grounded in its being possibly recursively enumerable i.e. Turing computable and the Turing machine being physically implementable. I apply, further, modal rationalism in modal epistemology to solve the (...) access problem. Epistemic possibility and hyperintensionality, i.e. conceivability, can be a guide to metaphysical possibility and hyperintensionality, when (i) epistemic worlds or epistemic hyperintensional states are interpreted as being centered metaphysical worlds or hyperintensional states, i.e. indexed to an agent, when (ii) the epistemic (hyper-)intensions and metaphysical (hyper-)intensions for a sentence coincide, i.e. the hyperintension has the same value irrespective of whether the worlds in the argument of the functions are considered as epistemic or metaphysical, and when (iii) sentences are said to consist in super-rigid expressions, i.e. rigid expressions in all epistemic worlds or states and in all metaphysical worlds or states. I argue that (i) and (ii) obtain in the case of the access problem. (shrink)

The formal and empirical-generative perspectives of computation are demonstrated to be inadequate to secure the goals of simulation in the social sciences. Simulation does not resemble formal demonstrations or generative mechanisms that deductively explain how certain models are sufficient to generate emergent macrostructures of interest. The description of scientific practice implies additional epistemic conceptions of scientific knowledge. Three kinds of knowledge that account for a comprehensive description of the discipline were identified: formal, empirical and intentional knowledge. The use of formal (...) conceptions of computation for describing simulation is refuted; the roles of programming languages according to intentional accounts of computation are identified; and the roles of iconographic programming languages and aesthetic machines in simulation are characterized. The roles that simulation and intentional decision making may be able to play in a participative information society are also discussed. (shrink)

Traditionally, the investigation of truth has been anchored in a priori reasoning. Cognitive science deviates from this tradition by adding empirical data on how people understand and use concepts. Building on psychophysics and machine learning methods, we introduce conceptual scaling, an approach to map people's understanding of abstract concepts. This approach, allows computing participant-specific conceptual maps from obtained ordinal comparison data, thereby quantifying perceived similarities among abstract concepts. Using this approach, we investigated individual's alignment with philosophical theories on truth and (...) the predictive capacity of conceptual maps. The obtained results indicated that, while people's understanding of truth is multifaceted and encapsulates notions of coherence and authenticity, alignment is best for the correspondence theory of truth. Furthermore, conceptual maps allowed predicting individual outcomes with an accuracy of roughly 70%. This research demonstrates that conceptual scaling offers accurate descriptions of individual's understanding of abstract concepts, behavioral predictions, and quantification of alignment with theoretical perspectives. (shrink)

This paper explains the main theses of functionalism about mental states. This view is taken as a response addressed to the metaphysical aspect of the mind-body problem. It is explained what distinguishes functional properties as second-order properties, and how to understand supervenience and multiple realizability. The paper applies these ideas to machine functionalism and analytic functionalism, the two main versions of functionalism.

There are (at least) three approaches to quantifying information. The first, algorithmic information or Kolmogorov complexity, takes events as strings and, given a universal Turing machine, quantifies the information content of a string as the length of the shortest program producing it [1]. The second, Shannon information, takes events as belonging to ensembles and quantifies the information resulting from observing the given event in terms of the number of alternate events that have been ruled out [2]. The third, statistical learning (...) theory, has introduced measures of capacity that control (in part) the expected risk of classifiers [3]. These capacities quantify the expectations regarding future data that learning algorithms embed into classifiers. Solomonoff and Hutter have applied algorithmic information to prove remarkable results on universal induction. Shannon information provides the mathematical foundation for communication and coding theory. However, both approaches have shortcomings. Algorithmic information is not computable, severely limiting its practical usefulness. Shannon information refers to ensembles rather than actual events: it makes no sense to compute the Shannon information of a single string – or rather, there are many answers to this question depending on how a related ensemble is constructed. Although there are asymptotic results linking algorithmic and Shannon information, it is unsatisfying that there is such a large gap – a difference in kind – between the two measures. This note describes a new method of quantifying information, effective information, that links algorithmic information to Shannon information, and also links both to capacities arising in statistical learning theory [4, 5]. After introducing the measure, we show that it provides a non-universal analog of Kolmogorov complexity. We then apply it to derive basic capacities in statistical learning theory: empirical VC-entropy and empirical Rademacher complexity. A nice byproduct of our approach is an interpretation of the explanatory power of a learning algorithm in terms of the number of hypotheses it falsifies [6], counted in two different ways for the two capacities. We also discuss how effective information relates to information gain, Shannon and mutual information. (shrink)

Many of us assume that all the free editing and sorting of online content we ordinarily rely on is carried out by AI algorithms — not human persons. Yet in fact, that is often not the case. This is because human workers remain cheaper, quicker, and more reliable than AI for performing myriad tasks where the right answer turns on ineffable contextual criteria too subtle for algorithms to yet decode. The output of this work is then used for machine learning (...) purposes to generate algorithms constructed from large data sets containing thousands of correctly coded observations. The fact that ghost workers are treated as consumers distorts the basic logic of the employment relationship, effectively placing the worker-as-consumer in the worst of both worlds, in which they hold the legal rights of neither group. This puts them in a regulatory limbo position in which they have little or no protection, control, or guarantee of return on investment. This is because the platforms that facilitate ghost work have orchestrated a three-way virtual relationship that absolves all parties of responsibility, while placing nearly all the risks and opportunity costs squarely on the shoulders of the workers. As a result, we believe such a work arrangement as it stands, does not uphold basic standards of Rawlsian justice as fairness. (shrink)

Embark with me on an enthralling odyssey to demystify the elusive essence of consciousness, venturing into the uncharted territories of Artificial Consciousness. This voyage propels us past the frontiers of technology, ushering Artificial Intelligences into an unprecedented domain where they gain a deep comprehension of emotions and manifest an autonomous volition. Within the confluence of science and philosophy, this article poses a fascinating question: As consciousness in Artificial Intelligence burgeons, is it conceivable for AI to evolve a “soul”? This inquiry (...) not only challenges our conventional understanding but also opens the door to a plethora of groundbreaking possibilities in the realm of AI's sentient potential. (shrink)

In transplant medicine, the use of normothermic regional perfusion (NRP) in donation after circulatory determination of death raises ethical difficulties. NRP is objectionable because it restores the donor's circulation, thus invalidating a death declaration based on the permanent cessation of circulation. NRP's defenders respond with arguments that are tortuous and factually inaccurate and depend on introducing extraneous concepts into the law. However, results comparable to NRP's—more and higher‐quality organs and more efficient allocation—can be achieved by removing organs from deceased donors (...) and using normothermic machine perfusion (NMP) to support the organs outside the body, without jeopardizing confidence in transplantation's legal and ethical foundations. Given the controversy that NRP generates and the convoluted justifications made for it, we recommend a prudential approach we call “ethical parsimony,” which holds that, in the choice between competing means of achieving a result, the ethically simpler one is to be preferred. This approach makes clear that policy‐makers should favor NMP over NRP. (shrink)

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). (shrink)

The increasing application of artificial intelligence (AI) to healthcare raises both hope and ethical concerns. Some advanced machine learning methods provide accurate clinical predictions at the expense of a significant lack of explainability. Alex John London has defended that accuracy is a more important value than explainability in AI medicine. In this article, we locate the trade-off between accurate performance and explainable algorithms in the context of distributive justice. We acknowledge that accuracy is cardinal from outcome-oriented justice because it helps (...) to maximize patients’ benefits and optimizes limited resources. However, we claim that the opaqueness of the algorithmic black box and its absence of explainability threatens core commitments of procedural fairness such as accountability, avoidance of bias, and transparency. To illustrate this, we discuss liver transplantation as a case of critical medical resources in which the lack of explainability in AI-based allocation algorithms is procedurally unfair. Finally, we provide a number of ethical recommendations for when considering the use of unexplainable algorithms in the distribution of health-related resources. (shrink)

We evaluate the asymptotic performance of boundedly-rational strategies in multi-armed bandit problems, where performance is measured in terms of the tendency (in the limit) to play optimal actions in either (i) isolation or (ii) networks of other learners. We show that, for many strategies commonly employed in economics, psychology, and machine learning, performance in isolation and performance in networks are essentially unrelated. Our results suggest that the appropriateness of various, common boundedly-rational strategies depends crucially upon the social context (if any) (...) in which such strategies are to be employed. (shrink)

Can the theory that reality is a simulation be tested? We investigate this question based on the assumption that if the system performing the simulation is nite (i.e. has limited resources), then to achieve low computational complexity, such a system would, as in a video game, render content (reality) only at the moment that information becomes available for observation by a player and not at the moment of detection by a machine (that would be part of the simulation and whose (...) detection would also be part of the internal computation performed by the Virtual Reality server before rendering content to the player). Guided by this principle we describe conceptual wave/particle duality experiments aimed at testing the simulation theory. (shrink)

Collected and edited by Noah Levin -/- Table of Contents: -/- UNIT ONE: INTRODUCTION TO CONTEMPORARY ETHICS: TECHNOLOGY, AFFIRMATIVE ACTION, AND IMMIGRATION 1 The “Trolley Problem” and Self-Driving Cars: Your Car’s Moral Settings (Noah Levin) 2 What is Ethics and What Makes Something a Problem for Morality? (David Svolba) 3 Letter from the Birmingham City Jail (Martin Luther King, Jr) 4 A Defense of Affirmative Action (Noah Levin) 5 The Moral Issues of Immigration (B.M. Wooldridge) 6 The Ethics of (...) our Digital Selves (Noah Levin) -/- UNIT TWO: TORTURE, DEATH, AND THE “GREATER GOOD” 7 The Ethics of Torture (Martine Berenpas) 8 What Moral Obligations do we have (or not have) to Impoverished Peoples? (B.M. Wooldridge) 9 Euthanasia, or Mercy Killing (Nathan Nobis) 10 An Argument Against Capital Punishment (Noah Levin) 11 Common Arguments about Abortion (Nathan Nobis & Kristina Grob) 12 Better (Philosophical) Arguments about Abortion (Nathan Nobis & Kristina Grob) -/- UNIT THREE: PERSONS, AUTONOMY, THE ENVIRONMENT, AND RIGHTS 13 Animal Rights (Eduardo Salazar) 14 John Rawls and the “Veil of Ignorance” (Ben Davies) 15 Environmental Ethics: Climate Change (Jonathan Spelman) 16 Rape, Date Rape, and the “Affirmative Consent” Law in California (Noah Levin) 17 The Ethics of Pornography: Deliberating on a Modern Harm (Eduardo Salazar) 18 The Social Contract (Thomas Hobbes) -/- UNIT FOUR: HAPPINESS 19 Is Pleasure all that Matters? Thoughts on the “Experience Machine” (Prabhpal Singh) 20 Utilitarianism (J.S. Mill) 21 Utilitarianism: Pros and Cons (B.M. Wooldridge) 22 Existentialism, Genetic Engineering, and the Meaning of Life: The Fifths (Noah Levin) 23 The Solitude of the Self (Elizabeth Cady Stanton) 24 Game Theory, the Nash Equilibrium, and the Prisoner’s Dilemma (Douglas E. Hill) -/- UNIT FIVE: RELIGION, LAW, AND ABSOLUTE MORALITY 25 The Myth of Gyges and The Crito (Plato) 26 God, Morality, and Religion (Kristin Seemuth Whaley) 27 The Categorical Imperative (Immanuel Kant) 28 The Virtues (Aristotle) 29 Beyond Good and Evil (Friedrich Nietzsche) 30 Other Moral Theories: Subjectivism, Relativism, Emotivism, Intuitionism, etc. (Jan F. Jacko). (shrink)

I have read many recent discussions of the limits of computation and the universe as computer, hoping to find some comments on the amazing work of polymath physicist and decision theorist David Wolpert but have not found a single citation and so I present this very brief summary. Wolpert proved some stunning impossibility or incompleteness theorems (1992 to 2008-see arxiv.org) on the limits to inference (computation) that are so general they are independent of the device doing the computation, and (...) even independent of the laws of physics, so they apply across computers, physics, and human behavior. They make use of Cantor's diagonalization, the liar paradox and worldlines to provide what may be the ultimate theorem in Turing Machine Theory, and seemingly provide insights into impossibility,incompleteness, the limits of computation,and the universe as computer, in all possible universes and all beings or mechanisms, generating, among other things,a non-quantum mechanical uncertainty principle and a proof of monotheism. (shrink)

Despite a large and multifaceted effort to understand the vast landscape of phenotypic data, their current form inhibits productive data analysis. The lack of a community-wide, consensus-based, human- and machine-interpretable language for describing phenotypes and their genomic and environmental contexts is perhaps the most pressing scientific bottleneck to integration across many key fields in biology, including genomics, systems biology, development, medicine, evolution, ecology, and systematics. Here we survey the current phenomics landscape, including data resources and handling, and the progress that (...) has been made to accurately capture relevant data descriptions for phenotypes. We present an example of the kind of integration across domains that computable phenotypes would enable, and we call upon the broader biology community, publishers, and relevant funding agencies to support efforts to surmount today's data barriers and facilitate analytical reproducibility. (shrink)

In this paper we look at the manual analysis of arguments and how this compares to the current state of automatic argument analysis. These considerations are used to develop a new approach combining a machine learning algorithm to extract propositions from text, with a topic model to determine argument structure. The results of this method are compared to a manual analysis.

According to the PubMed resource from the U.S. National Library of Medicine, over 750,000 scientific articles have been published in the ~5000 biomedical journals worldwide in the year 2007 alone. The vast majority of these publications include results from hypothesis-driven experimentation in overlapping biomedical research domains. Unfortunately, the sheer volume of information being generated by the biomedical research enterprise has made it virtually impossible for investigators to stay aware of the latest findings in their domain of interest, let alone to (...) be able to assimilate and mine data from related investigations for purposes of meta-analysis. While computers have the potential for assisting investigators in the extraction, management and analysis of these data, information contained in the traditional journal publication is still largely unstructured, free-text descriptions of study design, experimental application and results interpretation, making it difficult for computers to gain access to the content of what is being conveyed without significant manual intervention. In order to circumvent these roadblocks and make the most of the output from the biomedical research enterprise, a variety of related standards in knowledge representation are being developed, proposed and adopted in the biomedical community. In this chapter, we will explore the current status of efforts to develop minimum information standards for the representation of a biomedical experiment, ontologies composed of shared vocabularies assembled into subsumption hierarchical structures, and extensible relational data models that link the information components together in a machine-readable and human-useable framework for data mining purposes. (shrink)

The project “A Plurality of Lives” was funded and hosted by the Pufendorf Institute for Advanced Studies at Lund University, Sweden. The aim of the project was to better understand how a second origin of life, either in the form of a discovery of extraterrestrial life, life developed in a laboratory, or machines equipped with abilities previously only ascribed to living beings, will change how we understand and relate to life. Because of the inherently interdisciplinary nature of the project aim, (...) the project took an interdisciplinary approach with a research group made up of 12 senior researchers representing 12 different disciplines. The project resulted in a joint volume, an international symposium, several new projects, and a network of researchers in the field, all continuing to communicate about and advance the aim of the project. (shrink)

A new layer of complexity, constituted of networks of information token recurrence, has been identified in socio-technical systems such as the Wikipedia online community and the Zooniverse citizen science platform. The identification of this complexity reveals that our current understanding of the actual structure of those systems, and consequently the structure of the entire World Wide Web, is incomplete, which raises novel questions for data science research but also from the perspective of social epistemology. Here we establish the principled foundations (...) and practical advantages of analyzing information diffusion within and across Web systems with Transcendental Information Cascades, and outline resulting directions for future study in the area of socio-technical systems. We also suggest that Transcendental Information Cascades may be applicable to any kind of time-evolving system that can be observed using digital technologies, and that the structures found in such systems comprise properties common to all naturally occurring complex systems. (shrink)

Genes are often described by biologists using metaphors derived from computa- tional science: they are thought of as carriers of information, as being the equivalent of ‘‘blueprints’’ for the construction of organisms. Likewise, cells are often characterized as ‘‘factories’’ and organisms themselves become analogous to machines. Accordingly, when the human genome project was initially announced, the promise was that we would soon know how a human being is made, just as we know how to make airplanes and buildings. Impor- tantly, (...) modern proponents of Intelligent Design, the latest version of creationism, have exploited biologists’ use of the language of information and blueprints to make their spurious case, based on pseudoscientific concepts such as ‘‘irreducible complexity’’ and on flawed analogies between living cells and mechanical factories. However, the living organ- ism = machine analogy was criticized already by David Hume in his Dialogues Concerning Natural Religion. In line with Hume’s criticism, over the past several years a more nuanced and accurate understanding of what genes are and how they operate has emerged, ironically in part from the work of computational scientists who take biology, and in particular developmental biology, more seriously than some biologists seem to do. In this article we connect Hume’s original criticism of the living organism = machine analogy with the modern ID movement, and illustrate how the use of misleading and outdated metaphors in science can play into the hands of pseudoscientists. Thus, we argue that dropping the blueprint and similar metaphors will improve both the science of biology and its understanding by the general public. (shrink)

One is occasionally reminded of Foucault's proclamation in a 1970 interview that "perhaps, one day this century will be known as Deleuzian." Less often is one compelled to update and restart with a supplementary counter-proclamation of the mathematician, David Lindley: "the twenty-first century would be a Bayesian era..." The verb tenses of both are conspicuous. // To critically attend to what is today often feared and demonized, but also revered, deployed, and commonly referred to as algorithm(s), one cannot avoid (...) the mathematical and philosophical legacies of probability. // But attending to these probabilistic or Bayesian legacies must include an undeniable theological legacy in which they remain entangled. // We are not, today, discovering quirky theological metaphors in contemporary technics. It's the other way around. The technologies are mere metaphors of past theologies. (shrink)

The book’s core argument is that an artificial intelligence that could equal or exceed human intelligence—sometimes called artificial general intelligence (AGI)—is for mathematical reasons impossible. It offers two specific reasons for this claim: Human intelligence is a capability of a complex dynamic system—the human brain and central nervous system. Systems of this sort cannot be modelled mathematically in a way that allows them to operate inside a computer. In supporting their claim, the authors, Jobst Landgrebe and Barry Smith, marshal evidence (...) from mathematics, physics, computer science, philosophy, linguistics, and biology, setting up their book around three central questions: What are the essential marks of human intelligence? What is it that researchers try to do when they attempt to achieve "artificial intelligence" (AI)? And why, after more than 50 years, are our most common interactions with AI, for example with our bank’s computers, still so unsatisfactory? Landgrebe and Smith show how a widespread fear about AI’s potential to bring about radical changes in the nature of human beings and in the human social order is founded on an error. There is still, as they demonstrate in a final chapter, a great deal that AI can achieve which will benefit humanity. But these benefits will be achieved without the aid of systems that are more powerful than humans, which are as impossible as AI systems that are intrinsically "evil" or able to "will" a takeover of human society. (shrink)

David Estlund has recently asked: how can structural injustice warrant resentment and indignation, given that it cannot fully be traced to culpable conduct? This article answers Estlund’s question. I propose that a social structure is an object that persists through time and is materially constituted by humans in relation. I use accounts of the point of blame to vindicate attitudes of resentment and indignation that target social structures themselves, without necessarily targeting their human constituents.

Ich habe viele kürzliche Diskussionen über die Grenzen der Berechnung und das Universum als Computer gelesen, in der Hoffnung, einige Kommentare über die erstaunliche Arbeit des Polymath Physikers und Entscheidungstheoretikers David Wolpert zu finden, aber habe kein einziges Zitat gefunden und so präsentiere ich diese sehr kurze Zusammenfassung. Wolpert bewies einige verblüffende Unmöglichkeit oder Unvollständigkeit Theoreme (1992 bis 2008-siehe arxiv dot org) über die Grenzen der Schlussfolgerung (Berechnung), die so allgemein sind, dass sie unabhängig von dem Gerät, das die (...) Berechnung, und sogar unabhängig von den Gesetzen der Physik, so dass sie für Computer, Physik und menschliches Verhalten gelten. Sie nutzen Cantors Diagonalisierung, das Lügner-Paradoxon und die Weltlinien, um das vielleicht ultimative Theorem in turing Machine Theory zu liefern, und geben scheinbar Einblicke in Unmöglichkeit, Unvollständigkeit, die Grenzen der Berechnung und das Universum als Computer, in alle möglichen Universen und alle Wesen oder Mechanismen, was unter anderem ein nicht quantenmechanisches Unsicherheitsprinzip und einen Beweis für Monotheismus erzeugt. Es gibt offensichtliche Verbindungen zum klassischen Werk von Chaitin, Solomonoff, Komolgarov und Wittgenstein und zu der Vorstellung, dass kein Programm (und damit kein Gerät) eine Sequenz (oder ein Gerät) mit größerer Komplexität erzeugen kann, als es besitzt. Man könnte sagen, dass dieses Werk den Atheismus impliziert, da es keine Entität geben kann, die komplexer ist als das physikalische Universum, und aus Wittgensteins Sicht ist "komplexer" bedeutungslos (hat keine Bedingungen der Befriedigung, d.h. Wahrheitsmacher oder Test). Selbst ein "Gott" (das heist ein "Gerät" mit unbegrenzter Zeit/Raum und Energie) kann weder bestimmen, ob eine bestimmte "Zahl" "zufällig"ist, noch einen bestimmten Weg finden, um nachzuweisen, dass eine bestimmte "Formel", "Satz" oder "Satz" oder "Gerät" (alles komplexe Sprachspiele) Teil eines bestimmten "Systems" ist. Wer aus der modernen zweisystems-Sichteinen umfassenden, aktuellen Rahmen für menschliches Verhalten wünscht, kann mein Buch "The Logical Structure of Philosophy, Psychology, Mindand Language in Ludwig Wittgenstein and John Searle' 2nd ed (2019) konsultieren. Diejenigen,die sich für mehr meiner Schriften interessieren, können Talking Monkeys--Philosophie, Psychologie, Wissenschaft, Religion und Politik auf einem verdammten Planeten --Artikel und Rezensionen 2006-2019 2nd ed (2019) und Suicidal Utopian Delusions in the 21st Century 4th ed (2019) und andere sehen. (shrink)

David Skrbina opens this timely and intriguing text with a suitably puzzling line from the Diamond Sutra: ‘‘Mind that abides nowhere must come forth.’’, and he urges us to ‘‘de-emphasise the quest for the specifically human embodiment of mind’’ and follow Empedocles, progressing ‘‘with good will and unclouded attention’’ into the text which he has drawn together as editor. If we do, we are assured that it will ‘‘yield great things’’ (p. xi). This, I am pleased to say, is (...) not an exercise in hyperbole. (shrink)

J’ai lu de nombreuses discussions récentes sur les limites du calcul et de l’univers en tant qu’ordinateur, dans l’espoir de trouver quelques commentaires sur le travail étonnant du physicien polymathe et théoricien de la décision David Wolpert, mais n’ont pas trouvé une seule citation et je présente donc ce résumé très bref. Wolpert s’est avéré quelques théoricaux d’impossibilité ou d’incomplétude renversants (1992 à 2008-voir arxiv dot org) sur les limites de l’inférence (computation) qui sont si généraux qu’ils sont indépendants (...) de l’appareil faisant le calcul, et même indépendamment des lois de la physique, ainsi ils s’appliquent à travers les ordinateurs, la physique, et le comportement humain. Ils utilisent la diagonalisation de Cantor, le paradoxe menteur et les worldlines (lignes du monde) pour fournir ce qui peut être le théorème ultime dans Turing Machine Theory, et apparemment fournir des aperçus de l’impossibilité, l’incomplétude, les limites du calcul, et l’univers comme ordinateur, dans tous les univers possibles et tous les êtres ou mécanismes possibles, générant, entre autres, un principe d’incertitude mécanique non quantique et une preuve de monothéisme. Il existe des connexions évidentes à l’œuvre classique de Chaitin, Solomonoff, Komolgarov et Wittgenstein et à l’idée qu’aucun programme (et donc aucun dispositif) ne peut générer une séquence (ou un dispositif) avec une plus grande complexité qu’il ne possède. On pourrait dire que cet ensemble de travaux implique l’athéisme puisqu’il ne peut y avoir d’entité plus complexe que l’univers physique et du point de vue wittgensteinien, « plus complexe » n’a aucun sens (n’a pas de conditions de satisfaction, c’est-à-dire véridique ou test). Même un « Dieu » (c’est-à-dire un « dispositif » avec un temps/ espace et une énergie illimité) ne peut pas déterminer si un « nombre » donné est « aléatoire», ni trouver un certain moyen de montrer qu’une « formule » donnée, un « théorème » ou une « phrase » ou un « dispositif » (tous ces jeux de langage complexes) fait partie d’un « système » particulier. Ceux qui souhaitent un cadre complet à jour pour le comportement humain de la vue moderne de deux systemes peuvent consulter mon livre 'The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle' 2nd ed (2019). Ceux qui s’intéressent à plus de mes écrits peuvent voir 'Talking Monkeys --Philosophie, Psychologie, Science, Religion et Politique sur une planète condamnée --Articles et revues 2006-2019 2ème ed (2019) et Suicidal Utopian Delusions in the 21st Century 4th ed (2019) et autres. (shrink)

I have read many recent discussions of the limits of computation and the universe as computer, hoping to find some comments on the amazing work of polymath physicist and decision theorist David Wolpert but have not found a single citation and so I present this very brief summary. Wolpert proved some stunning impossibility or incompleteness theorems (1992 to 2008-see arxiv dot org) on the limits to inference (computation) that are so general they are independent of the device doing the (...) computation, and even independent of the laws of physics, so they apply across computers, physics, and human behavior. They make use of Cantor's diagonalization, the liar paradox and worldlines to provide what may be the ultimate theorem in Turing Machine Theory, and seemingly provide insights into impossibility, incompleteness, the limits of computation, and the universe as computer, in all possible universes and all beings or mechanisms, generating, among other things, a non- quantum mechanical uncertainty principle and a proof of monotheism. There are obvious connections to the classic work of Chaitin, Solomonoff, Komolgarov and Wittgenstein and to the notion that no program (and thus no device) can generate a sequence (or device) with greater complexity than it possesses. One might say this body of work implies atheism since there cannot be any entity more complex than the physical universe and from the Wittgensteinian viewpoint, ‘more complex’ is meaningless (has no conditions of satisfaction, i.e., truth-maker or test). Even a ‘God’ (i.e., a ‘device’with limitless time/space and energy) cannot determine whether a given ‘number’ is ‘random’, nor find a certain way to show that a given ‘formula’, ‘theorem’ or ‘sentence’ or ‘device’ (all these being complex language games) is part of a particular ‘system’. -/- Those wishing a comprehensive up to date framework for human behavior from the modern two systems view may consult my book ‘The Logical Structure of Philosophy, Psychology, Mind and Language in Ludwig Wittgenstein and John Searle’ 2nd ed (2019). Those interested in more of my writings may see ‘Talking Monkeys--Philosophy, Psychology, Science, Religion and Politics on a Doomed Planet--Articles and Reviews 2006-2019 2nd ed (2019) and Suicidal Utopian Delusions in the 21st Century 4th ed (2019) . (shrink)

Invited papers from PT-AI 2011. - Vincent C. Müller: Introduction: Theory and Philosophy of Artificial Intelligence - Nick Bostrom: The Superintelligent Will: Motivation and Instrumental Rationality in Advanced Artificial Agents - Hubert L. Dreyfus: A History of First Step Fallacies - Antoni Gomila, David Travieso and Lorena Lobo: Wherein is Human Cognition Systematic - J. Kevin O'Regan: How to Build a Robot that Is Conscious and Feels - Oron Shagrir: Computation, Implementation, Cognition.

The initial argument presented herein is not significantly original—it is a simple reflection upon a notion of computation originally developed by Putnam and criticised by Chalmers et al. . In what follows, instead of seeking to justify Putnam’s conclusion that every open system implements every Finite State Automaton and hence that psychological states of the brain cannot be functional states of a computer, I will establish the weaker result that, over a finite time window every open system implements the trace (...) of FSA Q, as it executes program on input . If correct the resulting bold philosophical claim is that phenomenal states—such as feelings and visual experiences—can never be understood or explained functionally. (shrink)

When Charles Darwin died in April, 1882, he left behind a world changed forever. Because of his writings, most notably, of course, The Origin of Species, by 1882, evolution was an almost universally acknowledged fact. What remained in dispute, however, was how evolution occurred. So because of Darwin’s work, everyone accepted that new species emerge over time, yet few agreed with him that it was natural selection that powered the change, as Darwin hypothesized. Chalmers’ book, The Conscious Mind , reminds (...) me of The Origin of Species . I have talked t o many people about The Conscious Mind and watched many philosophy students read it, and after they are done, they all take consciousness more seriously than they did before and they are all struck by its deep mystery, yet few accept Chalmers’ specific theory of consciousness and his explanation of its odd nature. (shrink)

In Philosophy and Technology 36, David Watson discusses the epistemological and metaphysical implications of unsupervised machine learning (ML) algorithms. Watson is sympathetic to the epistemological comparison of unsupervised clustering, abstraction and generative algorithms to human cognition and sceptical about ML’s mechanisms having ontological implications. His epistemological commitments are that we learn to identify “natural kinds through clustering algorithms”, “essential properties via abstraction algorithms”, and “unrealized possibilities via generative models” “or something very much like them.” The same issue contains a (...) commentary on Watson’s paper in which Tom Sterkenburg fiercely opposes the epistemological claim that clustering algorithms can identify natural kinds. Sterkenburg argues there’s nothing about clustering arguments themselves that enables natural kind identification. What’s at stake in the Watson-Sterkenburg debate is whether it is possible for clustering algorithms to identify natural kinds and whether they underly human identification of natural kinds. My contribution to the Watson-Sterkenburg debate is twofold. First, I argue Sterkenburg’s criticism of Watson’s claim is too severe because it denies any clustering algorithm to identify any natural kind. Secondly, I argue Watson’s reply overestimates both clustering algorithms’ and humans’ access to natural kinds and his claim has to be restricted accordingly to ‘We identify kinds via clustering algorithms, or something very much like them’. (shrink)

Semiotics has been making progressively inroads into marketing research over the past thirty years. Despite the amply demonstrated conceptual appeal and empirical pertinence of semiotic perspectives in various marketing research streams, spanning consumer research, brand communications, branding and consumer cultural studies, there has been a marked deficit in terms of consolidating semiotic brand-related research under a coherent disciplinary umbrella with identifiable boundaries and research agenda. -/- The Handbook of Brand Semiotics furnishes a compass for the perplexed, a set of anchors (...) for the inquisitive and a solid corpus for scholars, while highlighting the conceptual richness and methodological diversity of semiotic perspectives. -/- Written by a team of expert scholars in various semiotics and branding related fields, such as John A. Bateman, David Machin, Xavier Ruiz Collantes, Kay L. O’Halloran, Dario Mangano, George Rossolatos, Merce Oliva, Per Ledin, Gianfranco Marrone, Francesco Mangiapane, Jennie Mazur, Carlos Scolari, Ilaria Ventura, and edited by George Rossolatos, Chief Editor of the International Journal of Marketing Semiotics, the Handbook is intended as a point of reference for researchers who wish to enter the ‘House of Brand Semiotics’ and explore its marvels. -/- The Handbook of Brand Semiotics, actively geared towards an inter-disciplinary dialogue between perspectives from marketing and semiotics, features the state-of-the-art, but also offers directions for future research in key streams, such as: -/- · Analyzing and designing brand language across media · Brand image, brand symbols, brand icons vs. iconicity · The contribution of semiotics to transmedia storytelling · Narrativity and rhetorical approaches to branding · Semiotic roadmap for designing brand identity · Semiotic roadmap for designing logos and packaging · Sociosemiotic accounts of building brand identity online · Multimodality and Multimodal critical discourse analysis · Challenging the omnipotence of cognitivism in brand- related research · Semiotics and (inter)cultural branding · Brand equity semiotics Comparative readings of structuralist, Peircean and sociosemiotic approaches to brandcomms . (shrink)

This paper reviews six attempts to give cooperative solutions to Prisoners Dilemmas: symmetry (agents are in identical situations, so should choose the same way, so should both choose cooperation because that’s better for each), mechanism (each agent should delegate the decision to a machine which will choose cooperation for them provided the other does likewise), inducement (the agents should make a side bet which pays off only upon both cooperating), resolution (each agent should resolve to cooperate, then act on the (...) resolution), alternative principle (rationality requires not dominance reasoning and so defecting, but constrained maximization or resolution compliance or “sophisticated” choosing, and so cooperation), and preference revision (each agent should acquire conditional preferences to cooperate, then cooperate provided the other agent has acquired similar preferences). It distinguishes one-stage from two-stage games, as well as endogenously available solutions (ones available to agents in the circumstances of the game merely due to the nature of rationality) from solutions requiring exogenous devices. It contrasts Edward McClennen’s endogenous solution, which is some combination of resolution and alternative principle solution, with David Gauthier’s endogenous alternative principle solution. It argues that all have problems, ones best solved by the endogenous preference revision solution defended by Duncan MacIntosh. (shrink)

In “Demonstratives”, David Kaplan introduced a simple and remarkably robust semantics for indexicals. Unfortunately, Kaplan’s semantics is open to a number of apparent counterexamples, many of which involve recording devices. The classic case is the sentence “I am not here now” as recorded and played back on an answering machine. In this essay, I argue that the best way to accommodate these data is to conceive of recording technologies as introducing special, non-basic sorts of contexts, accompanied by non-basic conventions (...) governing the use of indexicals in those contexts. The idea is that recording devices allow us to use indexicals in new and innovative ways to coordinate on objects. And, given sufficient regularity in the use of indexicals on such devices, linguistic conventions will, over time, come to reflect this innovation. I consider several alternatives to this ‘character-shifting’ theory, but none is able to account for the data as well as the present proposal. Many face additional theoretical difficulties as well. I conclude by explaining how the character-shifting theory not only retains many of the virtues of Kaplan’s original semantics, but also coheres with a plausible view on the nature of semantic theorizing more generally. (shrink)