It has been widely discussed whether the existence of other universes than the known universe is a purely metaphysical consideration. This paper argues to the contrary that the existence of other universes is a meaningful hypothesis, which can be tested based on observable data. The paper applies the perspective of observer bias as an approach for assigning probabilities to the mutually excluding hypotheses of universe vs. multiverse, i.e., whether the known universe is the only universe, or just one universe in (...) an ensemble of universes, a so-called multiverse. The basic idea of the paper relies on the following consideration. In a multiverse, the vast majority of observers would live in universes that are more life friendly. Thus, conditional on there being a multiverse, we should expect to find ourselves in a universe with values of the fundamental parameters that provide particularly fertile grounds for life. In contrast, if there is only a single universe, it may well be the case that there is still a few observers even if the parameters are far from ideal for life, and in that case, those observers will find values of the parameters that are not ideal for intelligent life. It may well be the case that, among all parameter configurations that allow life at least somewhere, those that are not ideal for life far outnumber those that are ideal for life. Based on this elementary consideration, the paper proceeds to propose a quantitative framework to determine probabilities for either hypothesis. In particular, it is described how a future ab initio determination of some of the factors in the Drake equation may be used to infer which one of the two hypotheses is the more likely. A quantitative approach to this end is proposed. Expressing these factors of the Drake equation in the context of the two hypotheses, a general likelihood approach is first described. Then, to support intuition, example computations are provided, illustrating how an actual hypothesis test would work in practice. (shrink)

Recently, Jardas _et al_ have convincingly defended the patient preference predictor (PPP) against a range of autonomy-based objections. In this response, I propose a new autonomy-based objection to the PPP that is not explicitly discussed by Jardas _et al_. I call it the ‘objection from higher-order preferences’. Even if this objection is not sufficient reason to reject the PPP, the objection constitutes a pro tanto reason that is at least as powerful as the ones discussed by Jardas _et al._.

A new theory is taking hold in neuroscience. It is the theory that the brain is essentially a hypothesis-testing mechanism, one that attempts to minimise the error of its predictions about the sensory input it receives from the world. It is an attractive theory because powerful theoretical arguments support it, and yet it is at heart stunningly simple. Jakob Hohwy explains and explores this theory from the perspective of cognitive science and philosophy. The key argument throughout The Predictive Mind (...) is that the mechanism explains the rich, deep, and multifaceted character of our conscious perception. It also gives a unified account of how perception is sculpted by attention, and how it depends on action. The mind is revealed as having a fragile and indirect relation to the world. Though we are deeply in tune with the world we are also strangely distanced from it. (shrink)

A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing (...) should take the form of a continuous and constructive process, approach ethical alignment from a system perspective, and be aligned with public policies and incentives for ethically desirable behaviour. Third, we identify and discuss the constraints associated with ethics-based auditing. Only by understanding and accounting for these constraints can ethics-based auditing facilitate ethical alignment of AI, while enabling society to reap the full economic and social benefits of automation. (shrink)

A series of recent developments points towards auditing as a promising mechanism to bridge the gap between principles and practice in AI ethics. Building on ongoing discussions concerning ethics-based auditing, we offer three contributions. First, we argue that ethics-based auditing can improve the quality of decision making, increase user satisfaction, unlock growth potential, enable law-making, and relieve human suffering. Second, we highlight current best practices to support the design and implementation of ethics-based auditing: To be feasible and effective, ethics-based auditing (...) should take the form of a continuous and constructive process, approach ethical alignment from a system perspective, and be aligned with public policies and incentives for ethically desirable behaviour. Third, we identify and discuss the constraints associated with ethics-based auditing. Only by understanding and accounting for these constraints can ethics-based auditing facilitate ethical alignment of AI, while enabling society to reap the full economic and social benefits of automation. (shrink)

Important decisions that impact humans lives, livelihoods, and the natural environment are increasingly being automated. Delegating tasks to so-called automated decision-making systems can improve efficiency and enable new solutions. However, these benefits are coupled with ethical challenges. For example, ADMS may produce discriminatory outcomes, violate individual privacy, and undermine human self-determination. New governance mechanisms are thus needed that help organisations design and deploy ADMS in ways that are ethical, while enabling society to reap the full economic and social benefits of (...) automation. In this article, we consider the feasibility and efficacy of ethics-based auditing as a governance mechanism that allows organisations to validate claims made about their ADMS. Building on previous work, we define EBA as a structured process whereby an entity’s present or past behaviour is assessed for consistency with relevant principles or norms. We then offer three contributions to the existing literature. First, we provide a theoretical explanation of how EBA can contribute to good governance by promoting procedural regularity and transparency. Second, we propose seven criteria for how to design and implement EBA procedures successfully. Third, we identify and discuss the conceptual, technical, social, economic, organisational, and institutional constraints associated with EBA. We conclude that EBA should be considered an integral component of multifaced approaches to managing the ethical risks posed by ADMS. (shrink)

Climate change mitigation has become a paradigm case both for externalities in general and for the game-theoretic model of the Tragedy of the Commons (ToC) in particular. This situation is worrying, as we have reasons to suspect that some models in the social sciences are apt to be performative to the extent that they can become self-fulfilling prophecies. Framing climate change mitigation as a hardly solvable coordination problem may force us into a worse situation, by changing real-world behaviour to fit (...) our model, rather than the other way around. But while this problem of the performativity of the ToC has been noted in a recent paper in this journal by Matthew Kopec, his proposed strategies for dealing with their self-fulfilling nature fall short of providing an adequate solution. Instead of relying on the idea that modelling assumptions are always strictly speaking false, this paper shows that the problem may be better framed as a problem of underdetermination between competing explanations. Our goal here is to provide a framework for choosing between this set of competing models that allows us to avoid a ‘Russian Roulette’-like situation in which we gamble with existential risk. (shrink)

An exciting theory in neuroscience is that the brain is an organ for prediction error minimization. This theory is rapidly gaining influence and is set to dominate the science of mind and brain in the years to come. PEM has extreme explanatory ambition, and profound philosophical implications. Here, I assume the theory, briefly explain it, and then I argue that PEM implies that the brain is essentially self-evidencing. This means it is imperative to identify an evidentiary boundary between the brain (...) and its environment. This boundary defines the mind-world relation, opens the door to skepticism, and makes the mind transpire as more inferentially secluded and neurocentrically skull-bound than many would nowadays think. Therefore, PEM somewhat deflates contemporary hypotheses that cognition is extended, embodied and enactive; however, it can nevertheless accommodate the kinds of cases that fuel these hypotheses. (shrink)

The proposed European Artificial Intelligence Act (AIA) is the first attempt to elaborate a general legal framework for AI carried out by any major global economy. As such, the AIA is likely to become a point of reference in the larger discourse on how AI systems can (and should) be regulated. In this article, we describe and discuss the two primary enforcement mechanisms proposed in the AIA: the _conformity assessments_ that providers of high-risk AI systems are expected to conduct, and (...) the _post-market monitoring plans_ that providers must establish to document the performance of high-risk AI systems throughout their lifetimes. We argue that the AIA can be interpreted as a proposal to establish a Europe-wide ecosystem for conducting AI auditing, albeit in other words. Our analysis offers two main contributions. First, by describing the enforcement mechanisms included in the AIA in terminology borrowed from existing literature on AI auditing, we help providers of AI systems understand how they can prove adherence to the requirements set out in the AIA in practice. Second, by examining the AIA from an auditing perspective, we seek to provide transferable lessons from previous research about how to refine further the regulatory approach outlined in the AIA. We conclude by highlighting seven aspects of the AIA where amendments (or simply clarifications) would be helpful. These include, above all, the need to translate vague concepts into verifiable criteria and to strengthen the institutional safeguards concerning conformity assessments based on internal checks. (shrink)

Lauritz Munch and Björn Lundgren have recently replied to a paper published by us in this journal. In our original paper, we defended a novel version of the so-called ‘control theory’ of the moral right to privacy. We argued that control theorists should define ‘control’ as what we coined ‘Negative Control’. Munch and Lundgren have recently provided a range of interesting and challenging objections to our view. Independently of each other, they give almost identical counterexamples to our definition of Negative (...) Control. In this comment, we show that while the counterexamples are genuine counterexamples, they do not force us to abandon the idea of Negative Control. Furthermore, we reply to two additional objections raised by Lundgren. One of these replies involves giving a new account of what the relation is between the concept of privacy and the right to privacy. (shrink)

Virtue ethics is traditionally a conservative project. It analyses the virtues that humanity has been relying on since antiquity. This conservatism unduly limits the potential of virtue ethics to contribute to moral progress. Instead, we should pay more attention to constructionist virtue ethics with the help of conceptual engineering. I will argue that revising and ameliorating the virtue concepts which a community uses directly and indirectly leads to a change of the virtues that exist in this community. By revising and (...) innovating virtue concepts, we can re-make and improve the virtues that we have. (shrink)

Berichte zur Wissenschaftsgeschichte, Volume 45, Issue 1-2, Page 87-111, June 2022.

In this paper, we sketch a programme for AI-driven social theory. We begin by defining what we mean by artificial intelligence (AI) in this context. We then lay out our specification for how AI-based models can draw on the growing availability of digital data to help test the validity of different social theories based on their predictive power. In doing so, we use the work of Randall Collins and his state breakdown model to exemplify that, already today, AI-based models can (...) help synthesise knowledge from a variety of sources, reason about the world, and apply what is known across a wide range of problems in a systematic way. However, we also find that AI-driven social theory remains subject to a range of practical, technical, and epistemological limitations. Most critically, existing AI-systems lack three essential capabilities needed to advance social theory in ways that are cumulative, holistic, open-ended, and purposeful. These are (1) semanticisation, i.e., the ability to develop and operationalize verbal concepts to represent machine-manipulable knowledge; (2) transferability, i.e., the ability to transfer what has been learned in one context to another; and (3) generativity, i.e., the ability to independently create and improve on concepts and models. We argue that if the gaps identified here are addressed by further research, there is no reason why, in the future, the most advanced programme in social theory should not be led by AI-driven cumulative advances. (shrink)

Predictive processing (PP) is now a prominent theoretical framework in the philosophy of mind and cognitive science. This review focuses on PP research with a relatively philosophical focus, taking stock of the framework and discussing new directions. The review contains an introduction that describes the full PP toolbox; an exploration of areas where PP has advanced understanding of perceptual and cognitive phenomena; a discussion of PP's impact on foundational issues in cognitive science; and a consideration of the philosophy of science (...) of PP. The overall picture is that PP is a fruitful framework, with exciting new directions awaiting exploration. (shrink)

The article discusses the use of algorithmic models in finance. Algo trading is widespread but also somewhat controversial in modern financial markets. It is a form of automated trading technology, which critics claim can, among other things, lead to market manipulation. Drawing on three cases, this article shows that manipulation also can happen in the reverse way, meaning that human traders attempt to make algorithms ‘make mistakes’ by ‘misleading’ them. These attempts to manipulate are very simple and immediately transparent to (...) humans. Nevertheless, financial regulators increasingly penalize such attempts to manipulate algos. The article explains this as an institutionalization of algo trading, a trading practice which is vulnerable enough to need regulatory protection. (shrink)

In this paper, we argue that there is at least a pro tanto reason to favor the control account of the right to privacy over the access account of the right to privacy. This conclusion is of interest due to its relevance for contemporary discussions related to surveillance policies. We discuss several ways in which the two accounts of the right to privacy can be improved significantly by making minor adjustments to their respective definitions. We then test the improved versions (...) of the two accounts on a test case, to see which account best explains the violation that occurs in the case. The test turns out in favor of the control account. (shrink)

On the whole, the US Algorithmic Accountability Act of 2022 (US AAA) is a pragmatic approach to balancing the benefits and risks of automated decision systems. Yet there is still room for improvement. This commentary highlights how the US AAA can both inform and learn from the European Artificial Intelligence Act (EU AIA).

It is common in moral philosophy to test the validity of moral principles by proposing counter-examples in the form of cases where the application of the principle does not give the conclusion we intuitively find valid. These cases are often imaginary and sometimes rather ‘outlandish’, involving ray guns, non-existent creatures, etc. I discuss whether we can test moral principles with the help of outlandish cases, or if only realistic cases are admissible. I consider two types of argument against outlandish cases: (...) 1) Since moral principles are meant for guiding action in this world, cases drawn from other worlds are irrelevant. 2) We lack the capacity to apply our intuitive moral competence to outlandish cases. I argue that while the first approach is importantly flawed, the second approach is plausible, not because our moral competence per se is limited to cases from this world, but because we lack the capacity to imagine outlandish cases, and we cannot apply our moral competence to a case we fail to imagine properly. (shrink)

Recent advancements in artificial intelligence have fueled widespread academic discourse on the ethics of AI within and across a diverse set of disciplines. One notable subfield of AI ethics is machine ethics, which seeks to implement ethical considerations into AI systems. However, since different research efforts within machine ethics have discipline-specific concepts, practices, and goals, the resulting body of work is pestered with conflict and confusion as opposed to fruitful synergies. The aim of this paper is to explore ways to (...) alleviate these issues, both on a practical and theoretical level of analysis. First, we describe two approaches to machine ethics: the philosophical approach and the engineering approach and show how tensions between the two arise due to discipline specific practices and aims. Using the concept of disciplinary capture, we then discuss potential promises and pitfalls to cross-disciplinary collaboration. Drawing on recent work in philosophy of science, we finally describe how metacognitive scaffolds can be used to avoid epistemological obstacles and foster innovative collaboration in AI ethics in general and machine ethics in particular. (shrink)

Millikan’s (1984. Language, Thought, and Other Biological Categories: New Foundations for Realism. MIT Press) selected effects theory of functions states that functions are effects for which the ancestors of a trait were selected for. As the function is an effect a thing’s ancestors produced, only things that are reproductions in some sense can have functions. Against this reproduction requirement, Garson (2019. What Biological Functions Are and Why They Matter. Cambridge University Press) argues that not only processes of differential reproduction but (...) also processes of differential persistence can lead to new functions. Since such “persistence functions” have the same explanatory power as traditional selected effects functions, selected effects theorists should include them in their theory. In this paper, I will defend Millikan’s theory against this argument. I will show that the proponents of the generalized theory have yet to provide a working notion of populations that avoids a liberality problem. Further, I will argue that persistence functions are at best a marginal case of functions due to their restricted explanatory power. (shrink)

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, we (...) critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments. (shrink)

I argue that virtue reliabilism and virtue responsibilism are complementary. They do not give competing accounts of epistemic virtue. Rather they explain the excellent functioning of different parts of our cognitive apparatus. Reliabilist virtue designates the excellent functioning of fast and context-specific Type 1 cognitive processes, while responsibilist virtue means an excellent functioning of effortful and reflective Type 2 cognitive processes. This account unifies reliabilist and responsibilist virtue theory. But the virtues are not unified by designating some epistemic norm that (...) both aim at. Instead, I unify them through their cognitive foundations. Because Type 1 and Type 2 cognition are complementary, reliabilist and responsibilist virtues are complementary. Thereby, this dual-process theory of epistemic virtue gives a naturalised account of virtues as well as an explanation of how reliabilism and responsibilism relate. This approach offers a solution for both the generality problem and the situationist challenge to virtue epistemology; additionally it preserves the epistemological autonomy of each virtue type. (shrink)

The period from Plato's birth to Aristotle's death (427-322 BC) is one of the most influential and formative in the history of Western philosophy. The developments of logic, metaphysics, epistemology, ethics and science in this period have been investigated, controversies have arisen and many new theories have been produced. But this is the first book to give detailed scholarly attention to the development of dialectic during this decisive period. It includes chapters on topics such as: dialectic as interpersonal debate between (...) a questioner and a respondent; dialectic and the dialogue form; dialectical methodology; the dialectical context of certain forms of arguments; the role of the respondent in guaranteeing good argument; dialectic and presentation of knowledge; the interrelations between written dialogues and spoken dialectic; and definition, induction and refutation from Plato to Aristotle. The book contributes to the history of philosophy and also to the contemporary debate about what philosophy is. (shrink)

Drawing on recent findings, this study examines whether valence concordant electromyography (EMG) responses can be explained as an unconditional effect of mere stimulus processing or as somatosensory simulation driven by task-dependent processing strategies. While facial EMG over the Corrugator supercilii and the Zygomaticus major was measured, each participant performed two tasks with pictures of album covers. One task was an affective evaluation task and the other was to attribute the album covers to one of five decades. The Embodied Emotion Account (...) predicts that valence concordant EMG is more likely to occur if the task necessitates a somatosensory simulation of the evaluative meaning of stimuli. Results support this prediction with regard to Corrugator supercilii in that valence concordant EMG activity was only present in the affective evaluation task but not in the non-evaluative task. Results for the Zygomaticus major were ambiguous. Our findings are in line with the view that EMG activity is an embodied part of the evaluation process and not a mere physical outcome. (shrink)

Organisations increasingly use automated decision-making systems (ADMS) to inform decisions that affect humans and their environment. While the use of ADMS can improve the accuracy and efficiency of decision-making processes, it is also coupled with ethical challenges. Unfortunately, the governance mechanisms currently used to oversee human decision-making often fail when applied to ADMS. In previous work, we proposed that ethics-based auditing (EBA)—that is, a structured process by which ADMS are assessed for consistency with relevant principles or norms—can (a) help organisations (...) verify claims about their ADMS and (b) provide decision-subjects with justifications for the outputs produced by ADMS. In this article, we outline the conditions under which EBA procedures can be feasible and effective in practice. First, we argue that EBA is best understood as a ‘soft’ yet ‘formal’ governance mechanism. This implies that the main responsibility of auditors should be to spark ethical deliberation at key intervention points throughout the software development process and ensure that there is sufficient documentation to respond to potential inquiries. Second, we frame AMDS as parts of larger sociotechnical systems to demonstrate that to be feasible and effective, EBA procedures must link to intervention points that span all levels of organisational governance and all phases of the software lifecycle. The main function of EBA should, therefore, be to inform, formalise, assess, and interlink existing governance structures. Finally, we discuss the policy implications of our findings. To support the emergence of feasible and effective EBA procedures, policymakers and regulators could provide standardised reporting formats, facilitate knowledge exchange, provide guidance on how to resolve normative tensions, and create an independent body to oversee EBA of ADMS. (shrink)

Virtue ethics has many times been suggested as a promising recipe for the construction of artificial moral agents due to its emphasis on moral character and learning. However, given the complex nature of the theory, hardly any work has de facto attempted to implement the core tenets of virtue ethics in moral machines. The main goal of this paper is to demonstrate how virtue ethics can be taken all the way from theory to machine implementation. To achieve this goal, we (...) critically explore the possibilities and challenges for virtue ethics from a computational perspective. Drawing on previous conceptual and technical work, we outline a version of artificial virtue based on moral functionalism, connectionist bottom–up learning, and eudaimonic reward. We then describe how core features of the outlined theory can be interpreted in terms of functionality, which in turn informs the design of components necessary for virtuous cognition. Finally, we present a comprehensive framework for the technical development of artificial virtuous agents and discuss how they can be implemented in moral environments. (shrink)

The free energy principle says that any self-organising system that is at nonequilibrium steady-state with its environment must minimize its free energy. It is proposed as a grand unifying principle for cognitive science and biology. The principle can appear cryptic, esoteric, too ambitious, and unfalsifiable—suggesting it would be best to suspend any belief in the principle, and instead focus on individual, more concrete and falsifiable ‘process theories’ for particular biological processes and phenomena like perception, decision and action. Here, I explain (...) the free energy principle, and I argue that it is best understood as offering a conceptual and mathematical analysis of the concept of existence of self-organising systems. This analysis offers a new type of solution to long-standing problems in neurobiology, cognitive science, machine learning and philosophy concerning the possibility of normatively constrained, self-supervised learning and inference. The principle can therefore uniquely serve as a regulatory principle for process theories, to ensure that process theories conforming to it enable self-supervision. This is, at least for those who believe self-supervision is a foundational explanatory task, good reason to believe the free energy principle. (shrink)

In this paper, I defend what I call the ‘Inference Principle’. This principle holds that if an agent obtains some information legitimately, then the agent can make any inference she wants based on the information, without violating anyone’s right to privacy. This principle is interesting for at least three reasons. First, it constitutes a novel answer to the timely question of whether the widespread use of ‘data analytics’ to infer personal information about individuals is morally permissible. Second, it contradicts what (...) seems to be a common view of inferences’ ability to violate privacy rights. Third, it offers an account of the theoretically underdeveloped issue of what duties are engendered by the moral right to privacy with regard to inferred information. (shrink)

Departing from popular imaginations around artificial intelligence (AI), this article engages in the I in the AI acronym but from perspectives outside of mathematics, computer science and machine learning. When intelligence is attended to here, it most often refers to narrow calculating tasks. This connotation to calculation provides AI an image of scientificity and objectivity, particularly attractive in societies with a pervasive desire for numbers. However, as is increasingly apparent today, when employed in more general areas of our messy socio-cultural (...) realities, AI- powered automated systems often fail or have unintended consequences. This article will contribute to this critique of AI by attending to Nicholas of Cusa and his treatment of intelligence. According to him, intelligence is equally dependent on an ability to handle the unknown as it unfolds in the present moment. This suggests that intelligence is organic which ties Cusa to more contemporary discussions in tech philosophy, neurology, evolutionary biology, and cognitive sciences in which it is argued that intelligence is dependent on having—and acting through—an organic body. Understanding intelligence as organic thus suggests an oxymoronic relationship to artificial. (shrink)

This paper argues that some of the major theories in current business ethics fail to provide an adequate account of moral responsibility for the creation of systemic financial risk. Using the trading of credit default swaps (CDS) during the 2008 financial crisis as a case study, I will formulate three challenges that these theories must address: the problem of risk imposition, the problem of unstructured collective harm and the problem of limited knowledge. These challenges will be used to work out (...) key shortcomings of stakeholder approaches and Integrative Social Contracts Theory. I will argue that pluralist connection models used in political theory can help to overcome these shortcomings. Adopting an approach based on these models shows that financial institutions incur obligations in five main areas: managing their own risk profile; remedying some of the harms caused by financial crises; supporting the development of better epistemic methods; curbing the transmission and amplification of initial losses; and instigating structural reforms. (shrink)

Artificial Intelligence (AI) often outperforms human doctors in terms of decisional speed. For some diseases, the expected benefit of a fast but less accurate decision exceeds the benefit of a slow but more accurate one. In such cases, we argue, it is often justified to rely on a medical AI to maximise decision speed – even if the AI is less accurate than human doctors.

This article examines the financial technology of derivatives. Derivatives are financial products whose values are based on possible fluctuations in the values of underlying assets. Hence derivatives markets are markets that trade in the risks of other markets. In order for derivatives markets to function, forms of prognostication that can assess the possible future fluctuations of the underlying markets are necessary. What such prognostications do, the article argues, is to create information out of future possibilities. Building upon a notion of (...) virtuality derived from Gilles Deleuze, Ulrich Beck and Niklas Luhmann, the article shows how market risks and uncertainties, by means of prognostications, cease to be mere possibilities and instead come to have virtual existence. Through the technology of derivatives, uncertainty and risk can be rendered virtual and be traded. The article suggests that this technology is an example of a new way in which capitalism is now expanding self-referentially as it creates markets out of markets; and of how it is colonizing the future by developing new technologies for ‘hyper-speculation’, that is, speculation not in the possible developments of a given asset but simply in the risk of such speculation. (shrink)

The notion that the brain is a prediction error minimizer entails, via the notion of Markov blankets and self-evidencing, a form of global scepticism — an inability to rule out evil demon scenarios. This type of scepticism is viewed by some as a sign of a fatally flawed conception of mind and cognition. Here I discuss whether this scepticism is ameliorated by acknowledging the role of action in the most ambitious approach to prediction error minimization, namely under the free energy (...) principle. I argue that the scepticism remains but that the role of action in the free energy principle constrains the demon’s work. This yields new insights about the free energy principle, epistemology, and the place of mind in nature. (shrink)

Delusions are unhinged hinge certainties. Delusions are defined as strongly anchored beliefs that do not change in the face of adverse evidence. The same goes for Wittgensteinian certainties. My paper refines the so-called framework views of delusion, presenting an argument that epistemically speaking, considering them to be certainties best accounts for delusions’ doxastic profile. Until now there has been little argument in favour of this position and the original proposals made too extreme predictions about the belief systems of delusional patients. (...) I show that my account fares better with the diverse objections that have been raised against older framework views of delusion (Campbell 2001, Gipps and Rhodes 2008). Finally, I examine what makes a harmless hinge into a pathological delusion. (shrink)

The search for the neural correlates of consciousness is in need of a systematic, principled foundation that can endow putative neural correlates with greater predictive and explanatory value. Here, we propose the predictive processing framework for brain function as a promising candidate for providing this systematic foundation. The proposal is motivated by that framework’s ability to address three general challenges to identifying the neural correlates of consciousness, and to satisfy two constraints common to many theories of consciousness. Implementing the search (...) for neural correlates of consciousness through the lens of predictive processing delivers strong potential for predictive and explanatory value through detailed, systematic mappings between neural substrates and phenomenological structure. We conclude that the predictive processing framework, precisely because it at the outset is not itself a theory of consciousness, has significant potential for advancing the neuroscience of consciousness. (shrink)