Weekly QuEST Discussion Topics, 30 Sept

QuEST – 30 Sept 2022

This week at QuEST, we have invited Dr. Andrew Budson to discuss his recent theory: Consciousness as a Memory System. While it might feel like we are experiencing the present moment through perception of incoming information, maybe our experiences are instead better explained by the operation of the memory system that Dr. Budson describes in his theory. For those of us who aren’t well read on different memory systems, you might want to start with his New England Journal of Medicine review article (Budson and Price, 2005); the consciousness paper will be easier to read after that (Budson, Richman, Kensinger, 2022 in press).

The fields of neuroscience and artificial intelligence have a deep collaborative history, from the development of artificial neural networks up through one recent example from our colleagues at Google demonstrating human-level control through deep reinforcement learning in Atari games by implementing principles of the very memory system we are discussing this week. It is the QuEST contention that a better understanding of biological brain mechanisms (like the medial temporal lobe-dependent memory system) will play a vital role in building intelligent machines, and our conversations with Dr. Budson over the coming weeks will hopefully bring us at least one step closer to that goal.

consciousness-as-a-memory-system-2022-kensingerDownload

2005-nejmDownload

Weekly QuEST Discussion Topics, 23 Sept

QuEST 23 Sept 2020

This week will be a BYOQ discussion – Bring Your Own Question.  The price of admission to the meeting is either a question you want the group to respond to with their opinions / answers OR the question that you personally are focused on with respect to Consciousness. 

Cap

Weekly QuEST Discussion Topics, 16 Sept

This week’s QuEST will feature Drs. Ken Gish and Kevin Zish to discuss:

Bias in Facial Recognition Technology

We will discuss two sources of bias in current facial recognition technology, namely hardware and AI training data. Mitigation strategies will be outlined with a focus on test and evaluation.

Suggested PopSci pre-reading: https://www.nbcnews.com/tech/tech-news/no-quick-fix-openais-dalle-2-illustrated-challenges-bias-ai-rcna39918

Weekly QuEST Discussion Topics, 9 Sept

This week Kevin / Cap will provide some introductory material on “An Integrated World Modeling Theory (IWMT) of Consciousness: Combining Integrated Information and Global Neuronal Workspace Theories With the Free Energy Principle and Active Inference Framework; Toward Solving the Hard Problem and Characterizing Agentic Causation” work by Adam Safron* Indiana University, Bloomington, IN, United States. The idea is to prepare QuEST participants to be prepared for some upcoming lectures by Adam Safron to the QuEST meetings. 

Frontiers in Artificial Intelligence | www.frontiersin.org 1 June 2020 |Volume 3 | Article 30

The Free Energy Principle and Active Inference Framework (FEP-AI) begins with the understanding that persisting systems must regulate environmental exchanges and prevent entropic accumulation. In FEP-AI, minds and brains are predictive controllers for autonomous systems, where action-driven perception is realized as probabilistic inference. Integrated Information Theory (IIT) begins with considering the preconditions for a system to intrinsically exist, as well as axioms regarding the nature of consciousness. IIT has produced controversy because of its surprising entailments: quasi-panpsychism; subjectivity without referents or dynamics; and the possibility of fully-intelligent-yet-unconscious brain simulations. Here, I describe how these controversies might be resolved by integrating IIT with FEP-AI, where integrated information only entails consciousness for systems with perspectival reference frames capable of generating models with spatial, temporal, and causal coherence for self and world. Without that connection with external reality, systems could have arbitrarily high amounts of integrated information, but nonetheless would not entail subjective experience. I further describe how an integration of these frameworks may contribute to their evolution as unified systems theories and models of emergent causation. Then, inspired by both Global Neuronal Workspace Theory (GNWT) and the Harmonic Brain Modes framework, I describe how streams of consciousness may emerge as an evolving generation of sensorimotor predictions, with the precise composition of experiences depending on the integration abilities of synchronous complexes as self-organizing harmonic modes (SOHMs). These integrating dynamics may be particularly likely to occur via richly connected subnetworks affording body-centric sources of phenomenal binding and executive control. Along these connectivity backbones, SOHMs are proposed to implement turbo coding via loopy message-passing over predictive (autoencoding) networks, thus generating maximum a posteriori estimates as coherent vectors governing neural evolution, with alpha frequencies generating basic awareness, and cross-frequency phase-coupling within theta frequencies for access consciousness and volitional control. These dynamic cores of integrated information also function as global workspaces, centered on posterior cortices, but capable of being entrained with frontal cortices and interoceptive hierarchies, thus affording agentic causation. Integrated World Modeling Theory (IWMT) represents a synthetic approach to understanding minds that reveals compatibility between leading theories of consciousness, thus enabling inferential synergy.