Elucidation of the Concept of Consciousness from the Theory of Non-Human Communication Agents
- URL: http://arxiv.org/abs/2502.03508v1
- Date: Wed, 05 Feb 2025 13:58:23 GMT
- Title: Elucidation of the Concept of Consciousness from the Theory of Non-Human Communication Agents
- Authors: Julian Tagnin,
- Abstract summary: This article focuses on elucidating the concept of consciousness from a relational and post-phenomenological theory of non-human communication agents (ANHC)
Building on interactions with non-human cognitive agents, among other factors, the explainability of sociotechnical systems challenges the common sense of modern philosophy and science.
The aim is to contribute to a necessary discussion for designing new frameworks of understanding that pave the way toward an ethical and pragmatic approach to addressing contemporary challenges in the design, regulation, and interaction with ANHC.
- Score: 0.0
- License:
- Abstract: This article focuses on elucidating the concept of consciousness from a relational and post-phenomenological theory of non-human communication agents (ANHC). Specifically, we explore the contributions of Thomas Metzinger s Self Model Theory, Katherine Hayles conceptualizations of non-conscious cognitive processes centered on knowledge processing phenomena shared between biological and technical systems and Lenore and Manuel Blum s theoretical perspective on computation, which defines consciousness as an emergent phenomenon of complex computational systems, arising from the appropriate organization of their inorganic materiality. Building on interactions with non-human cognitive agents, among other factors, the explainability of sociotechnical systems challenges the humanistic common sense of modern philosophy and science. This critical integration of various approaches ultimately questions other concepts associated with consciousness, such as autonomy, freedom, and mutual responsibility. The aim is to contribute to a necessary discussion for designing new frameworks of understanding that pave the way toward an ethical and pragmatic approach to addressing contemporary challenges in the design, regulation, and interaction with ANHC. Such frameworks, in turn, enable a more inclusive and relational understanding of agency in an interconnected world.
Related papers
- A Conceptual Framework for Integrating Awareness into Relational Quantum Dynamics (RQD) [0.0]
We propose a conceptual framework that integrates awareness into Quantum Dynamics (RQD)
We operationalize awareness as the realization of a quantum event-quantified by measures such as the integrated information metric ($Phi$) from Integrated Information Theory (IIT)
A toy model is presented in which a simple observer-system is recast in terms of information exchange updating, illustrating how an interaction can give rise to an awareness update.
arXiv Detail & Related papers (2025-02-17T16:51:06Z) - Human-like conceptual representations emerge from language prediction [72.5875173689788]
We investigated the emergence of human-like conceptual representations within large language models (LLMs)
We found that LLMs were able to infer concepts from definitional descriptions and construct representation spaces that converge towards a shared, context-independent structure.
Our work supports the view that LLMs serve as valuable tools for understanding complex human cognition and paves the way for better alignment between artificial and human intelligence.
arXiv Detail & Related papers (2025-01-21T23:54:17Z) - What Machine Learning Tells Us About the Mathematical Structure of Concepts [0.0]
The study highlights how each framework provides a distinct mathematical perspective for modeling concepts.
This work emphasizes the importance of interdisciplinary dialogue, aiming to enrich our understanding of the complex relationship between human cognition and artificial intelligence.
arXiv Detail & Related papers (2024-08-28T03:30:22Z) - Preliminaries to artificial consciousness: a multidimensional heuristic approach [0.0]
The pursuit of artificial consciousness requires conceptual clarity to navigate its theoretical and empirical challenges.
This paper introduces a composite, multilevel, and multidimensional model of consciousness as a framework to guide research in this field.
arXiv Detail & Related papers (2024-03-29T13:47:47Z) - A Neuro-mimetic Realization of the Common Model of Cognition via Hebbian
Learning and Free Energy Minimization [55.11642177631929]
Large neural generative models are capable of synthesizing semantically rich passages of text or producing complex images.
We discuss the COGnitive Neural GENerative system, such an architecture that casts the Common Model of Cognition.
arXiv Detail & Related papers (2023-10-14T23:28:48Z) - Mind the Gap! Bridging Explainable Artificial Intelligence and Human Understanding with Luhmann's Functional Theory of Communication [5.742215677251865]
We apply social systems theory to highlight challenges in explainable artificial intelligence.
We aim to reinvigorate the technical research in the direction of interactive and iterative explainers.
arXiv Detail & Related papers (2023-02-07T13:31:02Z) - Kernel Based Cognitive Architecture for Autonomous Agents [91.3755431537592]
This paper considers an evolutionary approach to creating a cognitive functionality.
We consider a cognitive architecture which ensures the evolution of the agent on the basis of Symbol Emergence Problem solution.
arXiv Detail & Related papers (2022-07-02T12:41:32Z) - Acquiring and Modelling Abstract Commonsense Knowledge via Conceptualization [49.00409552570441]
We study the role of conceptualization in commonsense reasoning, and formulate a framework to replicate human conceptual induction.
We apply the framework to ATOMIC, a large-scale human-annotated CKG, aided by the taxonomy Probase.
arXiv Detail & Related papers (2022-06-03T12:24:49Z) - Active Inference in Robotics and Artificial Agents: Survey and
Challenges [51.29077770446286]
We review the state-of-the-art theory and implementations of active inference for state-estimation, control, planning and learning.
We showcase relevant experiments that illustrate its potential in terms of adaptation, generalization and robustness.
arXiv Detail & Related papers (2021-12-03T12:10:26Z) - The Evolution of Concept-Acquisition based on Developmental Psychology [4.416484585765028]
A conceptual system with rich connotation is key to improving the performance of knowledge-based artificial intelligence systems.
Finding a new method to represent concepts and construct a conceptual system will greatly improve the performance of many intelligent systems.
Developmental psychology carefully observes the process of concept acquisition in humans at the behavioral level.
arXiv Detail & Related papers (2020-11-26T01:57:24Z) - Neuro-symbolic Architectures for Context Understanding [59.899606495602406]
We propose the use of hybrid AI methodology as a framework for combining the strengths of data-driven and knowledge-driven approaches.
Specifically, we inherit the concept of neuro-symbolism as a way of using knowledge-bases to guide the learning progress of deep neural networks.
arXiv Detail & Related papers (2020-03-09T15:04:07Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.