Neurophilosophy, Philosophy of Neuroscience, and Philosophy of Artificial Intelligence: The Problem of Distinguishing

Neurophilosophy is understood as different areas of philosophy, for example, the philosophy of neuroscience, the philosophy of artificial intelligence, or eliminative materialism. This excessive interpretation of the term is due to the fact that the understanding of the subject area of this discipline is still incomplete. For example, one of the earliest definitions of neurophilosophy given by P.S. Churchland stated reduction of psychology to neurosciences. In modern views, the idea of neurophilosophy as an attempt to justify eliminative materialism is outdated and does not correspond to reality. The article analyzes the terms “philosophy of neuroscience,” “neurophilosophy,” and “philosophy of artificial intelligence” and also offers a variant of their differentiation. The authors focus on the common and different features, using the example of G.M. Edelman's theory of consciousness and the concept of connectionism for weak artificial intelligence. It is concluded that integral use of the term “neurophilosophy” should be abandoned. As a result, the term “neurophilosophy” should be understood as a direction in philosophy of the early 21st century, applying neuroscientific concepts to solve traditional philosophical problems, while the philosophy of specific neurosciences can be considered primarily as a field in the philosophy of science that formulates and solves problems of specific neurosciences as well as of the entire neuroscientific direction. The philosophy of artificial intelligence is an area in philosophy that answers the question of what non-biological intelligence is and what makes it possible; in other words, it is a philosophical and methodological basis for the study of non-biological intelligence. In the formation of neurosciences and their scientific and philosophical basis, we are still at the first methodological stage of the analysis and differentiation of hypotheses. After some time, there will emerge a philosophy of neuroscience, as the basis of all existing neuroscientific theories, and then this term will acquire greater significance.

The Nature of Information, Semantics, and Effectiveness for Artificial Intelligence and Cognition

This manuscript puts forward claims to help address foundational gaps in understanding Cognition and Artificial General Intelligence (AGI), including the nature of Emergence, Semantics, and Information. This includes criteria for assessing true understanding in AI models. How symbolic reasoning conceptualizes phenomena is described. Without a subsymbolic perceptual level to generate concepts, there is no symbol grounding. Grounding requires dynamics outside of its own symbolization. Grounding forms the set of symbols used at the conceptual level. It is claimed that this role explains Semantics. This approach naturally leads to established research on Conceptual Spaces and has implications for Semantic Vector Spaces learned via Neural Embedding methods. It also has implications for Information Theories. A claim is made that Semantic Processes form Shannon-like microstates and macrostates, while Effective Processes constrain Semantic Processes. Unlike existing Semantic Information Theories, Semantic Processes are pre-informational. The claims provide perspective on the Mind. It is natural to conflate percepts with the modified version necessarily created when conceptualizing through explication. The ‘Hard Problem of Consciousness’ is related to this Percept/Concept distinction. Concepts are always subject to Eliminative Materialism. The nonconceptual properties of Percepts cannot be eliminated. Intrinsic are Extrinsic Emergence are distinguished. It is common to assume extrinsic emergent properties are intrinsic to the systems evoking them. This presents a challenge for proving intrinsic emergence in AI. However, criteria are proposed for claiming a theoretical system intrinsically processes information and grounds symbols. By leveraging the functional properties of Grounding, the criteria can be considered for actual systems.

How to Think about the Debate over the Reality of Beliefs

The aim of this paper is to propose a new conceptualization of the distinction between realism and anti-realism about beliefs that is based on the division between natural and non-natural properties, as defined by Lewis. It will be argued that although the traditional form of anti-realism about beliefs, namely eliminative materialism, has failed (as it led to unacceptable consequences), there is a possibility to reformulate the division in question. The background assumption of the proposal is the framework of deflationism about truth and existence: it will be assumed that beliefs can be said to exist and their attributions can said to be true. The aim is to show that even when we buy into such assumptions we can meaningfully distinguish between the realist and anti-realist approach to belief. According to the proposal, the paradigmatic anti-realist view on beliefs should be seen as a conjunction of three claims: that belief attributions do not track objective similarities, that beliefs are not causally active, and that there is no viable way of naturalizing content. It will be shown that seeing the debate in the proposed way has important advantages as it allows the issue of belief realism to be made non-trivial and tractable, and it introduces theoretical unity into contemporary metaphysics of beliefs.

Eliminativní materialismus, lidová psychologie a jazyk myšlení

The article provides an analysis of Paul and Patricia Churchland’s eliminative materialism. I will distinguish two lines of argument in their eliminativism: one seeking to eliminate folk psychology and the second criticising Jerry Fodor’s language of thought hypothesis. Then I will closely examine the second line of argument, and show that it represents the main motive of Churchland’s work since the end of 1980s and demonstrate why the success of the argument against the language of thought hypothesis does not constitute a reason for the elimination of folk psychology. Finally, I will examine the consequences of this approach for the role of folk psychology in the study of mind and show that the weakened eliminativist position still fulfils the original aim of Churchland’s program.

Nothing But a Pack of Neurons

Seemingly separate from the concerns raised by either hard determinism or epiphenomenalism are the concerns raised by physicalistic reductionism. The separate worries for responsibility spawned by physicalism stem from the neuroscience claim that at bottom we are just mechanisms, physical machines. The claim seems to belittle our most cherished attributes like our creativity, our capacity to love, our responsible agency. To be “nothing but a pack of neurons” seemingly is to be less than the image we had of ourselves. The chapter examines the meaning of reductionism in the sciences generally, and of mind to brain more specifically. A variety of metaphysical views (of the relation of mind to brain) are examined, each of which raises this distinctive challenge of physicalism despite the differences between them. A view often called “reductionist” but which in fact is not—eliminative materialism—is also distinguished. The chapter then sifts the evidence thus far produced by neuroscience that some form of mind-brain reductionism is true, and assays the extent to which such reductionism actually challenges responsibility.