Does the metaphysical dog wag its formal tail? The free-energy principle and philosophical debates about life, mind, and matter.

According to Bruineberg and colleagues, philosophical arguments on life, mind, and matter that are based on the free-energy principle (FEP) (1) essentially draw on the Markov blanket construct and (2) tend to assume that strong metaphysical claims can be justified on the basis of metaphysically innocuous formal assumptions provided by FEP. I argue against both (1) and (2).

AI ethics in computational psychiatry: From the neuroscience of consciousness to the ethics of consciousness.

Methods used in artificial intelligence (AI) overlap with methods used in computational psychiatry (CP). Hence, considerations from AI ethics are also relevant to ethical discussions of CP. Ethical issues include, among others, fairness and data ownership and protection. Apart from this, morally relevant issues also include potential transformative effects of applications of AI-for instance, with respect to how we conceive of autonomy and privacy. Similarly, successful applications of CP may have transformative effects on how we categorise and classify mental disorders and mental health. Since many mental disorders go along with disturbed conscious experiences, it is desirable that successful applications of CP improve our understanding of disorders involving disruptions in conscious experience. Here, we discuss prospects and pitfalls of transformative effects that CP may have on our understanding of mental disorders. In particular, we examine the concern that even successful applications of CP may fail to take all aspects of disordered conscious experiences into account.

[From the Ethics of AI to the Ethics of Consciousness: Ethical Aspects of Computational Psychiatry]. / Von der KI-Ethik zur Bewusstseinsethik: Ethische Aspekte der Computational Psychiatry.

OBJECTIVE: Identifying ethical problems arising from AI research and Computational Psychiatry for psychiatric research and practice. METHODS: Conceptual analysis and discussion of ethically relevant projects within Computational Psychiatry. RESULTS: Computational Psychiatry promises a contribution to improving diagnostics and therapy (prediction). Ethical problems include dealing with data protection, consequences for our self-image, as well as the risk of biologization and the neglect of conscious experience. CONCLUSION: It is necessary to consider possible applications of AI and Computational Psychiatry now in order to create the conditions for responsible use in the future. This requires a basic understanding of how AI applications work and of the associated ethical problems.

Sentience and the Origins of Consciousness: From Cartesian Duality to Markovian Monism.

This essay addresses Cartesian duality and how its implicit dialectic might be repaired using physics and information theory. Our agenda is to describe a key distinction in the physical sciences that may provide a foundation for the distinction between mind and matter, and between sentient and intentional systems. From this perspective, it becomes tenable to talk about the physics of sentience and 'forces' that underwrite our beliefs (in the sense of probability distributions represented by our internal states), which may ground our mental states and consciousness. We will refer to this view as Markovian monism, which entails two claims: (1) fundamentally, there is only one type of thing and only one type of irreducible property (hence monism). (2) All systems possessing a Markov blanket have properties that are relevant for understanding the mind and consciousness: if such systems have mental properties, then they have them partly by virtue of possessing a Markov blanket (hence Markovian). Markovian monism rests upon the information geometry of random dynamic systems. In brief, the information geometry induced in any system-whose internal states can be distinguished from external states-must acquire a dual aspect. This dual aspect concerns the (intrinsic) information geometry of the probabilistic evolution of internal states and a separate (extrinsic) information geometry of probabilistic beliefs about external states that are parameterised by internal states. We call these intrinsic (i.e., mechanical, or state-based) and extrinsic (i.e., Markovian, or belief-based) information geometries, respectively. Although these mathematical notions may sound complicated, they are fairly straightforward to handle, and may offer a means through which to frame the origins of consciousness.

The science of consciousness does not need another theory, it needs a minimal unifying model.

This article discusses a hypothesis recently put forward by Kanai et al., according to which information generation constitutes a functional basis of, and a sufficient condition for, consciousness. Information generation involves the ability to compress and subsequently decompress information, potentially after a temporal delay and adapted to current purposes. I will argue that information generation should not be regarded as a sufficient condition for consciousness, but could serve as what I will call a "minimal unifying model of consciousness." A minimal unifying model (MUM) specifies at least one necessary feature of consciousness, characterizes it in a determinable way, and shows that it is entailed by (many) existing theories of consciousness. Information generation fulfills these requirements. A MUM of consciousness is useful, because it unifies existing theories of consciousness by highlighting their common assumptions, while enabling further developments from which empirical predictions can be derived. Unlike existing theories (which probably contain at least some false assumptions), a MUM is thus likely to be an adequate model of consciousness, albeit at a relatively general level. Assumptions embodied in such a model are less informative than assumptions made by more specific theories and hence function more in the way of guiding principles. Still, they enable further refinements, in line with new empirical results and broader theoretical and evolutionary considerations. This also allows developing the model in ways that facilitate more specific claims and predictions.

Toward a Mature Science of Consciousness.

In Being No One, Metzinger (2004[2003]) introduces an approach to the scientific study of consciousness that draws on theories and results from different disciplines, targeted at multiple levels of analysis. Descriptions and assumptions formulated at, for instance, the phenomenological, representationalist, and neurobiological levels of analysis provide different perspectives on the same phenomenon, which can ultimately yield necessary and sufficient conditions for applying the concept of phenomenal representation. In this way, the "method of interdisciplinary constraint satisfaction (MICS)" (as it has been called by Weisberg, 2005) promotes our understanding of consciousness. However, even more than a decade after the first publication of Being No One, we still lack a mature science of consciousness. This paper makes the following meta-theoretical contribution: It analyzes the hurdles an approach such as MICS has yet to overcome and discusses to what extent existing approaches solve the problems left open by MICS. Furthermore, it argues that a unifying theory of different features of consciousness is required to reach a mature science of consciousness.