Why Is Anything Conscious?
- URL: http://arxiv.org/abs/2409.14545v2
- Date: Sat, 2 Nov 2024 23:09:58 GMT
- Title: Why Is Anything Conscious?
- Authors: Michael Timothy Bennett, Sean Welsh, Anna Ciaunica,
- Abstract summary: We provide a mathematical formalism describing how biological systems self-organise to hierarchically interpret unlabelled sensory information.
We claim that access consciousness at the human level is impossible without the ability to hierarchically model i) the self, ii) the world/others andiii) the self as modelled by others.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: We tackle the hard problem of consciousness taking the naturally selected, self-organising, embodied organism as our starting point. We provide a mathematical formalism describing how biological systems self-organise to hierarchically interpret unlabelled sensory information according to valence and specific needs. Such interpretations imply behavioural policies which can only be differentiated from each other by the qualitative aspect of information processing. Selection pressures favour systems that can intervene in the world to achieve homeostatic and reproductive goals. Quality is a property arising in such systems to link cause to affect to motivate real world interventions. This produces a range of qualitative classifiers (interoceptive and exteroceptive) that motivate specific actions and determine priorities and preferences. Building upon the seminal distinction between access and phenomenal consciousness, our radical claim here is that phenomenal consciousness without access consciousness is likely very common, but the reverse is implausible. To put it provocatively: death grounds meaning, and Nature does not like zombies. We formally describe the multilayered architecture of self-organisation from rocks to Einstein, illustrating how our argument applies in the real world. We claim that access consciousness at the human level is impossible without the ability to hierarchically model i) the self, ii) the world/others and iii) the self as modelled by others. Phenomenal consciousness is therefore required for human-level functionality. Our proposal lays the foundations of a formal science of consciousness, deeply connected with natural selection rather than abstract thinking, closer to human fact than zombie fiction.
Related papers
- Consciousness defined: requirements for biological and artificial general intelligence [0.0]
Critically, consciousness is the apparatus that provides the ability to make decisions, but it is not defined by the decision itself.
requirements for consciousness include: at least some capability for perception, a memory for the storage of such perceptual information.
We can objectively determine consciousness in any conceivable agent, such as non-human animals and artificially intelligent systems.
arXiv Detail & Related papers (2024-06-03T14:20:56Z) - Can a Machine be Conscious? Towards Universal Criteria for Machine Consciousness [0.0]
Many concerns have been voiced about the ramifications of creating an artificial conscious entity.
This is compounded by a marked lack of consensus around what constitutes consciousness.
We propose five criteria for determining whether a machine is conscious.
arXiv Detail & Related papers (2024-04-19T18:38:22Z) - Is artificial consciousness achievable? Lessons from the human brain [0.0]
We analyse the question of developing artificial consciousness from an evolutionary perspective.
We take the evolution of the human brain and its relation with consciousness as a reference model.
We propose to clearly specify what is common and what differs in AI conscious processing from full human conscious experience.
arXiv Detail & Related papers (2024-04-18T12:59:44Z) - Artificial consciousness. Some logical and conceptual preliminaries [0.0]
We argue for the necessity of using dimensions and profiles of consciousness for a balanced discussion about their possible instantiation or realisation in artificial systems.
Our primary goal in this paper is to review the main theoretical questions that arise in the domain of artificial consciousness.
arXiv Detail & Related papers (2024-03-29T13:47:47Z) - COKE: A Cognitive Knowledge Graph for Machine Theory of Mind [87.14703659509502]
Theory of mind (ToM) refers to humans' ability to understand and infer the desires, beliefs, and intentions of others.
COKE is the first cognitive knowledge graph for machine theory of mind.
arXiv Detail & Related papers (2023-05-09T12:36:58Z) - Learning Goal-based Movement via Motivational-based Models in Cognitive
Mobile Robots [58.720142291102135]
Humans have needs motivating their behavior according to intensity and context.
We also create preferences associated with each action's perceived pleasure, which is susceptible to changes over time.
This makes decision-making more complex, requiring learning to balance needs and preferences according to the context.
arXiv Detail & Related papers (2023-02-20T04:52:24Z) - Sources of Richness and Ineffability for Phenomenally Conscious States [57.8137804587998]
We provide an information theoretic dynamical systems perspective on the richness and ineffability of consciousness.
In our framework, the richness of conscious experience corresponds to the amount of information in a conscious state.
While our model may not settle all questions relating to the explanatory gap, it makes progress toward a fully physicalist explanation.
arXiv Detail & Related papers (2023-02-13T14:41:04Z) - AGENT: A Benchmark for Core Psychological Reasoning [60.35621718321559]
Intuitive psychology is the ability to reason about hidden mental variables that drive observable actions.
Despite recent interest in machine agents that reason about other agents, it is not clear if such agents learn or hold the core psychology principles that drive human reasoning.
We present a benchmark consisting of procedurally generated 3D animations, AGENT, structured around four scenarios.
arXiv Detail & Related papers (2021-02-24T14:58:23Z) - What we are is more than what we do [0.0]
Complex behavior becomes meaningless if it is not performed by a conscious being.
The dissociation between "being" and "doing" is most salient in artificial general intelligence.
arXiv Detail & Related papers (2021-01-21T19:26:15Z) - Inductive Biases for Deep Learning of Higher-Level Cognition [108.89281493851358]
A fascinating hypothesis is that human and animal intelligence could be explained by a few principles.
This work considers a larger list, focusing on those which concern mostly higher-level and sequential conscious processing.
The objective of clarifying these particular principles is that they could potentially help us build AI systems benefiting from humans' abilities.
arXiv Detail & Related papers (2020-11-30T18:29:25Z) - Machine Common Sense [77.34726150561087]
Machine common sense remains a broad, potentially unbounded problem in artificial intelligence (AI)
This article deals with the aspects of modeling commonsense reasoning focusing on such domain as interpersonal interactions.
arXiv Detail & Related papers (2020-06-15T13:59:47Z)
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.