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Shea: Representation and Agency Realist Representational Explanations of Agency Should Require Some Unity of Purpose Nicholas Shea My paper is about what it takes for an AI system to be an agent. It is relevant to Sprevak and Fallon’s PhiMiSci Special Issue on Representation in the Neurosciences…

Mallory: Representation in LLMs Formats of representation in large language models Fintan Mallory Assuming that artificial neural networks (ANNs) can, through training, come to represent the data upon which they were trained, or more general features of that data, then two natural questions that…

Elber-Dorozko and Gouvêa: Ambiguity in the Concept of Representation ‘Neuronal representation’ is not a defective concept: Ambiguity as a sign of science in progress Lotem Elber-Dorozko and Devin Gouvêa The term “neural representation” is extremely popular in cognitive neuroscience. Scientists…

CFA: Biological Naturalism about Consciousness Hi Everyone, Be sure to check out the call for abstracts for a forthcoming conference on Biological Naturalism and Consciousness at UCLA! Details here: Call for Abstracts: Biological Naturalism about Consciousness November 5–6, 2026 · University of…

Aizawa: Evidence for Representation The Evidence for Representations Ken Aizawa It is commonly said that one reason to postulate mental representations is in order to explain behavior. I take this reasoning to be an instance of abductive reasoning, not to be identified with inference to the best…

Coelho Mollo and Millière: The Vector Grounding Problem Post on “The Vector Grounding Problem” for the Brains Blog Dimitri Coelho Mollo & Raphaël Millière We first preprinted “The Vector Grounding Problem” in April 2023, about four months after the release of ChatGPT. By that point, large language…

Mark Sprevak and Francis Fallon: Intro to the Symposium Representations are thought to be among the essential ingredients for explaining cognition. In cognitive psychology, behaviour and decision making are modelled in terms of computations performed over representations. In neuroscience,…

Gilbert Ryle 1900–1976 Mindcraft is a series of opinion posts on current issues in cognitive science by Brains Blog founder Gualtiero Piccinini. Do you agree? Disagree? Please contribute on the discussion board below! If you’d like to write a full-length response, please contact editor Dan…

Corey Maley: Structural and Analog Representation Corey J. Maley Department of Philosophy Cognition, Agency, and Intelligence Center Purdue University [email protected] coreymaley.net The thesis of this paper is simple: structural representation and analog representation turn out to be two names…

Brains and PhiMindSci: Joint Symposium on Representation We are very excited to introduce our next joint symposium with Philosophy of the Mind Sciences. This one highlights PhiMindSci's recent special issue on representation in neuroscience and AI. Tomorrow, we'll have an introductory post by Mark…

‘Neuronal representation’ is not a defective concept: Ambiguity as a sign of science in progress Lotem Elber-Dorozko and Devin Gouvêa The term “neural representation” is extremely popular in cognitive neuroscience. Scientists often claim to have discovered neural properties that represent environmental features, such as specific visual objects or specific sounds. At the same time, both philosophers and scientists seem increasingly dissatisfied with this term.

The Evidence for Representations Ken Aizawa It is commonly said that one reason to postulate mental representations is in order to explain behavior. I take this reasoning to be an instance of abductive reasoning, not to be identified with inference to the best explanation.[1] Empiricists have long been skeptical of abductive reasoning that is supposed to provide evidence for unobservable entities.

Hi Everyone, Be sure to check out the call for abstracts for a forthcoming conference on Biological Naturalism and Consciousness at UCLA! Details here: Call for Abstracts: Biological Naturalism about Consciousness November 5–6, 2026 · University of California, Los Angeles Can non-biological systems be conscious? If not, why not? These questions have taken on new weight as AI systems become increasingly sophisticated, not least because our answers bear on which entities might matter morally.

Realist Representational Explanations of Agency Should Require Some Unity of Purpose Nicholas Shea My paper is about what it takes for an AI system to be an agent. It is relevant to Sprevak and Fallon’s PhiMiSci Special Issue on Representation in the Neurosciences and AI because conditions on AI agency are often articulated in representational terms. Approaches to AI agency can be instrumentalist, for example when being an agent is understood in terms of representing goals and means to achieving goals, where representation is in turn understood to be a matter of displaying a certain pattern of behaviour.

Formats of representation in large language models Fintan Mallory Assuming that artificial neural networks (ANNs) can, through training, come to represent the data upon which they were trained, or more general features of that data, then two natural questions that arise are what are the vehicles of representation within the network and what is the format in which these vehicles are structured?

Post on “The Vector Grounding Problem” for the Brains Blog Dimitri Coelho Mollo & Raphaël Millière We first preprinted “The Vector Grounding Problem” in April 2023, about four months after the release of ChatGPT. By that point, large language models (LLMs) had started to capture the attention of philosophers, but there was still very little published work on the topic. The preprint languished on arXiv for longer than we initially planned, but it lived a life of its own and generated some interesting discussions.

Representations are thought to be among the essential ingredients for explaining cognition. In cognitive psychology, behaviour and decision making are modelled in terms of computations performed over representations. In neuroscience, responses of single cells, neural populations, and structural features are claimed to function as representations for the agent in question. In AI, what machines learn is often characterized in terms of the kinds of representations those machines acquire and how they manipulate them.

Mindcraft is a series of opinion posts on current issues in cognitive science by Brains Blog founder Gualtiero Piccinini. Do you agree? Disagree? Please contribute on the discussion board below! If you’d like to write a full-length response, please contact editor Dan Burnston. A guest post by Jack Copeland: 2026 is the 50th anniversary of Gilbert Ryle’s death. One of Britain’s most celebrated philosophers of mind, Ryle was elected Waynflete Professor of Metaphysical Philosophy at Oxford in 1944.

Corey J. Maley Department of Philosophy Cognition, Agency, and Intelligence Center Purdue University [email protected] coreymaley.net The thesis of this paper is simple: structural representation and analog representation turn out to be two names for the same kind of representation. This may seem implausible, given that typical examples of structural representation (e.g., maps) are much more complex than typical cases of analog representation (e.g., liquid thermometers).

We are very excited to introduce our next joint symposium with Philosophy of the Mind Sciences. This one highlights PhiMindSci's recent special issue on representation in neuroscience and AI. Tomorrow, we'll have an introductory post by Mark Sprevak that gives an overview of the special issue. Then we'll have posts on neuroscience the remaining days this week. Next week, we'll have AI-focused posts on Monday, Wednesday, and Friday.