Anthony F. Beavers

Curriculum Vitae


Affiliated Faculty, Cognitive Science, Indiana University

afbeaver@iu.edu


Principal Investigator,  DAN Research Group



Research Interests

Philosophy of Artificial Intelligence, Philosophy of Cognitive Science, Philosophy of Information  and Information Technology, History of Philosophy, 

Phenomenology, Metaethics



Course Syllabus

Philosophical Foundations of the Cognitive and Information Sciences

Recent and Upcoming Academic Activity


In this talk, I will address one place where the need for multi-disciplinary paradigmatic work seems particularly necessary; this concerns how network idealizations, loosely adopted from neuroscience and applied to artificial intelligence with mixed success, affect questions concerning cognition and experience. Specifically, I will suggest that common idealizations create their own impasse on the way to understanding experience and, further, that re-arranging basic suppositions may help to clear that path. The result will suggest a phenomenology of experience that follows associationist, rather than transcendental, lines. Making the needed moves, however, may mean having to change (or reinterpret) paradigms in two or more disciplines. Given current scientific practice, under what conditions could such a thing be allowed to happen?

A different idealization is possible. Perhaps weighted and thresholded connections are implementational details incidentally implicated in network success. If indeed the gating of information flow is doing the critical work, we may fairly wonder about the possibility of continuous-flow networks that eliminate conventional weights in favor of dynamic changes to the wiring schematic by adding and removing connections as needed between partially connected layers. In these talks, I will explore this idealization with a review of my near thirty-year research program involving Dynamic Associative Networks (DANs) and directed graphs.

Early studies have revealed interesting properties that demand additional study now as current and possibly problematic assumptions about network-based artificial intelligence have us bounding into the future without a careful study of all the options. To start, DANs engage in one shot learning, they are fully transparent and explainable, and they exhibit rudimentary metacognitive possibilities. Furthermore, because learning occurs by changing the wiring schematic rather than by setting weights, they face no problems with gradient-descent learning. DANs have been used in several micro-world experiments involving object identification and classification, visual shape recognition, anticipation of directionality of moving objects in a visual field, association across simulated sense modalities, primary sequential memory, rudimentary natural language processing, and recall by way of content-addressable memory. They have also been used in the stochastic context of NFL prediction.

Chiefly, they are based on two fundamental unifying principles, simple signaling in small, but overlapping network clusters and signal transduction. My goal in these talks is to examine these unifying principles with two goals in mind: to challenge several conventional foundational principles in network computing and to unify the various areas of network science into a coherent whole for exploitation in artificial intelligence systems. Having surveyed an array of low level intelligent affordances these simple networks get from these two principles, I will finish these presentations by sketching future directions for this line of research.

These presentations will be offered as two parts. The first (11/20/2024 from 4:30 to 6:00 pm Eastern) will take us from simple signaling to recognition, classification, and generalization. The second (12/4/2024 from 4:30 to 6:00 pm Eastern) will explore content-addressable memory, pattern completion, prediction, and metacognition.

The reason this matters to us today is that even though science has jettisoned any form of Cartesian dualism, it nonetheless often preserves a Cartesian notion of some interior private, mental space, though now physically realized and modified to allow an escape into the world through the body. This, I will submit, is not likely a picture Descartes would have endorsed if he had LLMs before him: the three matters above are thus shown to be forced by a specific model of cognition, a physicalized version of Descartes, now undone by current technology, thus signaling that we are at an important moment in the history of philosophical and psychological systems.  

To be clear, under no circumstances will I argue that LLMs are minded. The issue is best understood along these lines: If LLMs pass Descartes' test, then more than just dualism is jetisoned. The model of self as contained in a "cabinet of consciousness" is also jetisoned. Several important consequences follow.