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5590.227643
This paper explores the connection between the feelings that arise in grief and two kinds of “grief tech” that we use to regulate these feelings: music and AI-driven chatbots. “Grief tech” covers a broad range of practices, rituals, and artefacts that shape how we experience and express our grief. Music and AI might seem to have little in common with one another. However, I argue that both afford something not all forms of grief tech do – collaborative possibilities for world-making – and therefore can help the bereaved reconstruct “habits of intimacy” lost when a loved one dies. This (re)constructive impact is part of their world-making potency. And it is a crucial part of grief work. In this way, both music and AI potentially have a deep effect on our emotions, agency, and self-regulative capacities. This is why both are particularly powerful forms of grief tech.
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51402.227849
The fields of social neuroscience and neuroeconomics have experienced rapid growth over the past decade, yet little research has focused on issues related to midlife or older age. In light of the profound demographic changes occurring in our society, this is an important research gap. The past century witnessed a near doubling of life expectancy, and it is projected that in <50 years, there will be close to 90 million Americans aged 65 years (Federal Interagency Forum on Aging-Related Statistics, 2010). We are on the brink of profound demographic changes both in the USA and the world at large (see: http://www.prb.org/Articles/2011/agingpopulationclocks.aspx).
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74381.22786
Assume naturalism and suppose that digital electronic systems can be significantly conscious. Suppose Alice is a deterministic significantly conscious digital electronic system. Imagine we duplicated Alice to make another such system, Bob, and fed them both the same inputs. …
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239896.227867
This chapter examines the history of philosophy of psychology and philosophy of psychiatry as subfields of philosophy of science that emerged in the late twentieth and early twenty-first century. The chapter also surveys related literatures that developed in psychology and psychiatry. Philosophy of psychology (or philosophy of cognitive science) has been a well-established subfield of philosophy of mind since the 1990s and 2000s. This field of philosophy of psychology is narrowly focused on issues in cognitive psychology and cognitive science. Compared to the thriving subfield of philosophy of cognitive science, there has been a lack of corresponding interest among philosophers of science in broader methodological questions about different paradigms and fields of study in psychology. These broader methodological questions about psychology have been addressed in the field of theoretical psychology, which is a subfield of psychology that materialized in the 1980s and 1990s. Philosophy of psychiatry emerged as a subfield of philosophy of science in the mid-2000s. Compared to philosophy of psychology, the philosophy of psychiatry literature in philosophy of science engaged with issues examined in an older and more interdisciplinary tradition of philosophy of psychiatry that developed after the 1960s. The participation of philosophers of science in the literature on theoretical psychology, by contrast, has been limited.
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297587.227875
The Good Regulator Theorem and the Internal Model Principle are sometimes cited as mathematical proofs that an agent needs an internal model of the world in order to have an optimal policy. However, these principles rely on a definition of “internal model” that is far too permissive, applying even to cases of systems that do not use an internal model. As a result, these principles do not provide evidence (let alone a proof) that internal models are necessary. The paper also diagnoses what is missing in the GRT and IMP definitions of internal model, which is that models need to make predictions that represent variables in the target system (and these representations need to be usable by an agent so as to guide behavior).
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413184.227882
In the 1960s, the demonstration of interference effects using two laser-beams raised the question: can two photons interfere? Its plausibility contested Dirac’s dictum, “Interference between two different photons never occurs”. Disagreements about this conflict led to a controversy. This paper will chart the controversy’s contour and show that it evolved over two phases. Subsequently, I investigate the reasons for its perpetuation. The controversy was initiated and fuelled by several misinterpretations of the dictum. I also argue that Dirac’s dictum is not applicable to two photon interference as they belong to different contexts of interference. Recognising this resolves the controversy.
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528529.227889
The field of Artificial Intelligence (AI) safety evaluations aims to test AI behavior for problematic capabilities like deception. However, some scientists have cautioned against the use of behavior to infer general cognitive abilities because of the human tendency to overattribute cognition to everything. They recommend the adoption of a heuristic to avoid these errors that states behavior provides no evidence for cognitive capabilities unless there is some theoretical feature present to justify that inference.
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701750.227895
This paper integrates type functionalism with the Kairetic account to develop context-specific models for explaining mental states, particularly pain, across different species and systems. By employing context-dependent mapping fc, we ensure cohesive causal explanations while accommodating multiple realizations of mental states. The framework identifies context subsets Ci and maps them to similarity subspaces Si, capturing the unique physiological, biochemical, and computational mechanisms underlying pain in different entities such as humans, octopi, and AI systems. This approach highlights the importance of causal relations in defining mental states and preserves their functional roles across diverse contexts. Furthermore, the paper incorporates elements of token functionalism by recognizing species-specific realizations of mental states. By acknowledging the unique representations of mental states within different species and systems, the framework provides a nuanced understanding of how similar functional roles can be fulfilled by diverse physical substrates. This synthesis of type and token functionalism enhances our explanatory power and coherence in addressing the complex nature of mental states. The resulting framework offers a robust tool for analyzing and understanding mental phenomena, with significant implications for cognitive science, philosophy of mind, and artificial intelligence. By maintaining the functional roles of mental states while accommodating their multiple realizations, this approach not only advances theoretical understanding but also opens new avenues for practical applications in cross-species empathy, AI ethics, and the development of context-aware cognitive models.
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708340.227901
A common assumption in discussions of abilities is that phobias restrict an agent's abilities. Arachnophobics, for example, can't pick up spiders. I wonder if this is true, if we're talking about the pure 'can' of ability. …
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816875.227907
This paper analyses the phenomenology and epistemology of chatbots such as ChatGPT and Bard. The computational architecture underpinning these chatbots are large language models (LLMs), which are generative artificial intelligence (AI) systems trained on a massive dataset of text extracted from the Web. We conceptualise these LLMs as multifunctional computational cognitive artifacts, used for various cognitive tasks such as translating, summarizing, answering questions, information-seeking, and much more. Phenomenologically, LLMs can be experienced as a “quasi-other”; when that happens, users anthropomorphise them. For most users, current LLMs are black boxes, i.e., for the most part, they lack data transparency and algorithmic transparency. They can, however, be phenomenologically and informationally transparent, in which case there is an interactional flow. Anthropomorphising and interactional flow can, in some users, create an attitude of (unwarranted) trust towards the output LLMs generate. We conclude this paper by drawing on the epistemology of trust and testimony to examine the epistemic implications of these dimensions. Whilst LLMs generally generate accurate responses, we observe two epistemic pitfalls. Ideally, users should be able to match the level of trust that they place in LLMs to the degree that LLMs are trustworthy. However, both their data and algorithmic opacity and their phenomenological and informational transparency can make it difficult for users to calibrate their trust correctly. The effects of these limitations are twofold: users may adopt unwarranted attitudes of trust towards the outputs of LLMs (which is particularly problematic when LLMs hallucinate), and the trustworthiness of LLMs may be undermined.
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932698.227913
Recent advances in stem cell-derived human brain organoids and microelectrode array (MEA) technology raise profound questions about the potential for these systems to give rise to sentience. Brain organoids are 3D tissue constructs that recapitulate key aspects of brain development and function, while MEAs enable bidirectional communication with neuronal cultures. As brain organoids become more sophisticated and integrated with MEAs, the question arises: Could such a system support not only intelligent computation, but subjective experience? This paper explores the philosophical implications of this thought experiment, considering scenarios in which brain organoids exhibit signs of sensory awareness, distress, preference, and other hallmarks of sentience. It examines the ethical quandaries that would arise if compelling evidence of sentience were found in brain organoids, such as the moral status of these entities and the permissibility of different types of research. The paper also explores how the phenomenon of organoid sentience might shed light on the nature of consciousness and the plausibility of artificial sentience. While acknowledging the speculative nature of these reflections, the paper argues that the possibility of sentient brain organoids deserves serious consideration given the rapid pace of advances in this field. Grappling with these questions proactively could help set important ethical boundaries for future research and highlight critical avenues of scientific and philosophical inquiry. The thought experiment of sentient brain organoids thus serves as a valuable lens for examining deep issues at the intersection of neuroscience, ethics, and the philosophy of mind.
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936582.227919
I show really be done with Integrated Information Theory (IIT), in Aaronson’s simplified formulation, but I noticed a rather interesting difficult. In my previous post on the subject, I noticed that a double grid system where there are two grids stacked on top of one another, with the bottom grid consisting of inputs and the upper grid of outputs, and each upper value being the logical OR of the (up to) five neighboring input values will be conscious according to IIT if all the values are zero and the grid is large enough. …
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990411.227925
In this paper I return to Hubert Dreyfus’ old but influential critique of artificial intelligence, redirecting it towards contemporary predictive processing models of the mind (PP). I focus on Dreyfus’ arguments about the “frame problem” for artificial cognitive systems, and his contrasting account of embodied human skills and expertise. The frame problem presents as a prima facie problem for practical work in AI and robotics, but also for computational views of the mind in general, including for PP. Indeed, some of the issues it presents seem more acute for PP, insofar as it seeks to unify all cognition and intelligence, and aims to do so without admitting any cognitive processes or mechanisms outside of the scope of the theory. I contend, however, that there is an unresolved problem for PP concerning whether it can both explain all cognition and intelligent behavior as minimizing prediction error with just the core formal elements of the PP toolbox, and also adequately comprehend (or explain away) some of the apparent cognitive differences between biological and prediction-based artificial intelligence, notably in regard to establishing relevance and flexible context-switching, precisely the features of interest to Dreyfus’ work on embodied indexicality, habits/skills, and abductive inference. I address several influential philosophical versions of PP, including the work of Jakob Hohwy and Andy Clark, as well as more enactive-oriented interpretations of active inference coming from a broadly Fristonian perspective.
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1134159.227931
I hope this is my last post for a while on Integrated Information Theory (IIT), in Aaronson’s simplified formulation. One of the fun and well-known facts is that if you have an impractically large square two-dimensional grid of interconnected logic gates (presumably with some constant time-delay in each gate between inputs and outputs to prevent race conditions) in a fixed point (i.e., nothing is changing), the result can still have a degree of integrated information proportional to the square root of the number of gates. …
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1205898.227937
Recent research indicates gender differences in the impact of stress on decision behavior, but little is known about the brain mechanisms involved in these gender-specific stress effects. The current study used functional magnetic resonance imaging (fMRI) to determine whether induced stress resulted in gender-specific patterns of brain activation during a decision task involving monetary reward. Specifically, we manipulated physiological stress levels using a cold pressor task, prior to a risky decision making task. Healthy men (n ¼ 24, 12 stressed) and women (n ¼ 23, 11 stressed) completed the decision task after either cold pressor stress or a control task during the period of cortisol response to the cold pressor. Gender differences in behavior were present in stressed participants but not controls, such that stress led to greater reward collection and faster decision speed in males but less reward collection and slower decision speed in females. A gender-by-stress interaction was observed for the dorsal striatum and anterior insula. With cold stress, activation in these regions was increased in males but decreased in females. The findings of this study indicate that the impact of stress on reward-related decision processing differs depending on gender.
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1221504.227943
Stephen Yablo’s notion of proportionality, despite controversies surrounding it, has played a significant role in philosophical discussions of mental causation and of high-level causation more generally. In particular, it is invoked in James Woodward’s interventionist account of high-level causation and explanation, and is implicit in a novel approach to constructing variables for causal modeling in the machine learning literature, known as causal feature learning (CFL). In this article, we articulate an account of proportionality inspired by both Yablo’s account of proportionality and the CFL account of variable construction. The resulting account has at least three merits. First, it illuminates an important feature of the notion of proportionality, when it is adapted to a probabilistic and interventionist framework. The feature is that at the center of the notion of proportionality lies the concept of “determinate intervention effects.” Second, it makes manifest a virtue of (common types of) high-level causal/explanatory statements over low-level ones, when relevant intervention effects are determinate. Third, it overcomes a limitation of the CFL framework and thereby also addresses a challenge to interventionist accounts of high-level causation.
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1408206.22795
I’m still thinking about Integrated Information Theory (IIT), in Aaronson’s simplified formulation. Aaronson’s famous criticisms show pretty convincingly that IIT fails to correctly characterize consciousness: simple but large systems of unchanging logic gates end up having human-level consciousness on IIT. …
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1522980.227957
Philosophers are fond of wild hypotheticals: psychophysicists confined to black-and-white rooms, trolleys targeting victims with unnerving precision, magic rings that turn those who wear them invisible (and perhaps unjust). …
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1798556.227962
Structural representations are likely the most talked about representational posits in the contemporary debate over cognitive representations. Indeed, the debate surrounding them is so vast virtually every claim about them has been made. Some, for instance, claimed structural representations are di erent from indicators. Others argued they are the same. Some claimed structural representations mesh perfectly with mechanistic explanations, others argued they can’t in principle mash. Some claimed structural representations are central to predictive processing accounts of cognition, others rebuked predictive processing networks are blissfully structural representation free. And so forth. Here, I suggest this confusing state of a airs is due to the fact that the term “structural representations” is applied to a number of distinct conceptions of representations. In this paper, I distinguish four such conceptions, argue that these four conceptions are actually distinct, and then show that such a fourfold distinction can be used to clarify some of the most pressing questions concerning structural representations and their role in cognitive theorizing, making these questions more easily answerable.
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1798683.227969
We give a new and elementary construction of primitive positive decomposition of higher arity relations into binary relations on finite domains. Such decompositions come up in applications to constraint satisfaction problems, clone theory and relational databases. The construction exploits functional completeness of 2-input functions in many-valued logic by interpreting relations as graphs of partially defined multivalued ‘functions’. The ‘functions’ are then composed from ordinary functions in the usual sense. The construction is computationally effective and relies on well-developed methods of functional decomposition, but reduces relations only to ternary relations. An additional construction then decomposes ternary into binary relations, also effectively, by converting certain disjunctions into existential quantifications. The result gives a uniform proof of Peirce’s reduction thesis on finite domains, and shows that the graph of any Sheffer function composes all relations there.
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2370107.227975
A distinction is made between superpositional and non-superpositional quantum computers. The notion of quantum learning systems { quantum computers that modify themselves in order to improve their performance { is introduced. A particular non-superpositional quantum learning system, a quantum neurocomputer, is described: a conventional neural network implemented in a system which is a variation on the familiar two-slit apparatus from quantum physics. This is followed by a discussion of the advantages that quantum computers in general, and quantum neurocomputers in particular, might bring, not only to our search for more powerful computational systems, but also to our search for greater understanding of the brain, the mind, and quantum physics itself.
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2491050.227981
In this paper, I argue that no theory of consciousness can simultaneously respect four initially plausible metaphysical claims – namely, ‘first-person realism’, ‘non-solipsism’, ‘non-fragmentation’, and ‘one world’ – but that any three of the four claims are mutually consistent. So, theories of consciousness face a ‘quadrilemma’. Since it will be hard to achieve a consensus on which of the four claims to retain and which to give up, we arrive at a landscape of competing theories, all of which have pros and cons. I will briefly indicate which kinds of theories correspond to the four horns of the quadrilemma.
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2491080.227987
In this paper, I argue that current attempts at classifying life–mind continuity (LMC) feature several important ambiguities. We can resolve these ambiguities by distinguishing between the extensional, categorical, and systematic relationships that LMC might encompass. In section 1, I begin by introducing the notion of LMC and the theory behind it. In section 2, I show how different ideas of mind shape different approaches to continuity and how to achieve its aim. In section 3, I canvas various canonical formulations and classifications of LMC; I then demonstrate that they retain important ambiguities. Section 4 builds on this by arguing that we must conceive of the extensional and categorical aspects of continuity independently. In section 5, I show further that current literature has underexplored multiple systematic aspects of continuity. I then take a constructive approach in section 6 by providing a classification model for LMC based on extensional and categorical commitments. Here, I comment on aspects of the thesis omitted from the model but essential for a full classification and thorough comparison between various approaches to LMC. All of these arguments lay the foundation for more exhaustively classifying accounts of LMC.
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2721887.227993
Downward causation plays a central role in the debate around levels of mechanism. Both levels’ enthusiasts and skeptics reject it, arguing that it is incoherent to conceive of wholes causing the parts which constitute them. In this paper, I advance an argument from causal constraints against claims of the unintelligibility of constitutive downward causation, arguing that constitution relations neither exhaust the totality of relations that a proper whole is subject to, nor do they preclude another type of relation that a proper whole can have with respect to another proper whole.
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3225164.228003
Recently, there has been considerable interest in large language models: machine learning systems which produce human-like text and dialogue. Applications of these systems have been plagued by persistent inaccuracies in their output; these are often called “AI hallucinations”. We argue that these falsehoods, and the overall activity of large language models, is better understood as bullshit in the sense explored by Frankfurt (2005): the models are in an important way indifferent to the truth of their outputs. We distinguish two ways in which the models can be said to be bullshitters, and argue that they clearly meet at least one of these definitions. We further argue that describing AI misrepresentations as bullshit is both a more useful and more accurate way of predicting and discussing the behaviour of these systems.
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3299302.228011
In this paper, I identify a novel challenge to reasoning about human cognitive evolution. Theorists engaged in producing a causal history of uniquely human psychology often implicitly or explicitly take the perspective of imaginary hominins to reason about a plausible evolutionary sequence. I argue that such speculations only appear plausible because we have employed our evolved cognitive capacities to decide what the imaginary hominin would think or do. Further, I argue that we are likely to continue making this kind of mistake, and so we must continuously contend with it, even in our best approaches to human cognitive evolution.
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3326921.228017
The field of neuroscience and the development of artificial neural networks (ANNs) have mutually influenced each other, drawing from and contributing to many concepts initially developed in statistical mechanics. Notably, Hopfield networks and Boltzmann machines are versions of the Ising model, a model extensively studied in statistical mechanics for over a century. In the first part of this chapter, we provide an overview of the principles, models, and applications of ANNs, highlighting their connections to statistical mechanics and statistical learning theory. Artificial neural networks can be seen as high-dimensional mathematical functions, and understanding the geometric properties of their loss landscapes (i.e., the high-dimensional space on which one wishes to find extrema or saddles) can provide valuable insights into their optimization behavior, generalization abilities, and overall performance. Visualizing these functions can help us design better optimization methods and improve their generalization abilities. Thus, the second part of this chapter focuses on quantifying geometric properties and visualizing loss functions associated with deep ANNs.
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3818418.228022
This paper argues that the extended mind approach to cognition can be distinguished from its alternatives, such as embedded cognition and distributed cognition, not only in terms of metaphysics, but also in terms of epistemology. In other words, it cannot be understood in terms of a mere verbal redefinition of cognitive processing. This is because the extended mind approach differs in its theoretical virtues compared to competing approaches to cognition. The extended mind approach is thus evaluated in terms of its theoretical virtues, both essential to empirical adequacy and those that are ideal desiderata for scientific theories. While the extended mind approach may have similar internal consistency and empirical adequacy compared to other approaches, it may be more problematic in terms of its generality and simplicity as well as unificatory properties due to the cognitive bloat and the motley crew objections.
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3910221.228029
We’ve been hard at work here in Edinburgh. Kris Brown has created Julia code to implement the ‘stochastic C-set rewriting systems’ I described last time. I want to start explaining this code and also examples of how we use it. …
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3934068.228035
It has recently been remarked that the argument for physicalism from the causal closure of the physical is incomplete. It is only effective against mental causation manifested in the action of putative mental forces that lead to acceleration of particles in the nervous system. Based on consideration of anomalous, physically unaccounted-for correlations of neural events, I argue that irreducible mental causation whose nature is at least prima facie probabilistic is conceivable. The manifestation of such causation should be accompanied by a local violation of the Second Law of thermodynamics. I claim that mental causation can be viewed as the disposition of mental states to alter the state probability distribution within the nervous system, with no violation of the conservation laws. If confirmed by neurophysical research, it would indicate a kind of causal homogeneity of the world. Causation would manifest probabilistically in both quantum mechanical and psychophysical systems, and the dynamics of both would be determined by the temporal evolution of the corresponding system state function. Finally, I contend that a probabilistic account of mental causation can consistently explain the character of the selectional states that ensure uniformity of causal patterns, as well as the fact that different physical realizers of a mental property cause the same physical effects in different contexts.