Cover Image

From indicators to biology: the calibration problem in artificial consciousness

Fuente: arXiv

Saved in:

Bibliographic Details
Main Author:	Koch, Florentin
Format:	Preprint
Published:	2026
Subjects:	Artificial Intelligence Neurons and Cognition
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

What does a system modify when it modifies itself?
by: Koch, Florentin
Published: (2026)

Is artificial consciousness achievable? Lessons from the human brain
by: Farisco, Michele, et al.
Published: (2024)

Preliminaries to artificial consciousness: a multidimensional heuristic approach
by: Evers, K., et al.
Published: (2024)

Is GPT-4 conscious?
by: Tait, Izak, et al.
Published: (2024)

Do psychic cells generate consciousness?
by: Suzuki, Mototaka, et al.
Published: (2025)

Consciousness defined: requirements for biological and artificial general intelligence
by: McKenzie, Craig I.
Published: (2024)

Informational non-reductionist theory of consciousness that providing maximum accuracy of reality prediction
by: Vityaev, E. E.
Published: (2023)

The age of spiritual machines: Language quietus induces synthetic altered states of consciousness in artificial intelligence
by: Skipper, Jeremy I, et al.
Published: (2024)

A systematic approach to answering the easy problems of consciousness based on an executable cognitive system
by: Zhang, Qi
Published: (2026)

Some things to know about achieving artificial general intelligence
by: Roitblat, Herbert
Published: (2025)

Semantic representations emerge in biologically inspired ensembles of cross-supervising neural networks
by: Urbach, Roy, et al.
Published: (2025)

What biology can, and cannot, tell us about conscious AI
by: Klatzmann, Ulysse, et al.
Published: (2026)

Digital twin brain: a bridge between biological intelligence and artificial intelligence
by: Xiong, Hui, et al.
Published: (2023)

Quantum information theoretic approach to the hard problem of consciousness
by: Georgiev, Danko D.
Published: (2025)

From generative AI to the brain: five takeaways
by: Gros, Claudius
Published: (2025)

Better artificial intelligence does not mean better models of biology
by: Linsley, Drew, et al.
Published: (2025)

From Prediction to Understanding: Will AI Foundation Models Transform Brain Science?
by: Serre, Thomas, et al.
Published: (2025)

From task structures to world models: What do LLMs know?
by: Yildirim, Ilker, et al.
Published: (2023)

From Clever Hans to Scientific Discovery: Interpreting EEG Foundational Transformers with LRP
by: Bexten, Justus Meyer zu, et al.
Published: (2026)

From Theory of Mind to Theory of Environment: Counterfactual Simulation of Latent Environmental Dynamics
by: Uchiyama, Ryutaro
Published: (2026)

Multilevel Interpretability Of Artificial Neural Networks: Leveraging Framework And Methods From Neuroscience
by: He, Zhonghao, et al.
Published: (2024)

Simultaneity of consciousness with physical reality: the key that unlocks the mind-matter problem
by: Sanfey, John
Published: (2023)

From Priors to Predictions: Explaining and Visualizing Human Reasoning in a Graph Neural Network Framework
by: Do, Quan, et al.
Published: (2025)

Towards Neurocognitive-Inspired Intelligence: From AI's Structural Mimicry to Human-Like Functional Cognition
by: Golilarz, Noorbakhsh Amiri, et al.
Published: (2025)

From DDMs to DNNs: Using process data and models of decision-making to improve human-AI interactions
by: Gopnarayan, Mrugsen Nagsen, et al.
Published: (2023)

From Electrode to Global Brain: Integrating Multi- and Cross-Scale Brain Connections and Interactions Under Cross-Subject and Within-Subject Scenarios
by: Zhige, Chen, et al.
Published: (2024)

A Novel Approach to Image EEG Sleep Data for Improving Quality of Life in Patients Suffering From Brain Injuries Using DreamDiffusion
by: Fahim, David, et al.
Published: (2024)

Digging into CTM's consciousness: A possible mechanism for CTM generating self-conscious
by: Cui, Shaoyang, et al.
Published: (2024)

Binding threshold units with artificial oscillatory neurons
by: Fanaskov, Vladimir, et al.
Published: (2025)

Dual-Laws Model for a theory of artificial consciousness
by: Ohmura, Yoshiyuki, et al.
Published: (2026)

A generic model of consciousness
by: Hadley, Mark J.
Published: (2024)

The inner screen model of consciousness: applying the free energy principle directly to the study of conscious experience
by: Ramstead, Maxwell J. D., et al.
Published: (2023)

On the use of associative memory in Hopfield networks designed to solve propositional satisfiability problems
by: Weber, Natalya, et al.
Published: (2023)

Overcoming classic challenges for artificial neural networks by providing incentives and practice
by: Irie, Kazuki, et al.
Published: (2024)

On the utility of toy models for theories of consciousness
by: Albantakis, Larissa
Published: (2025)

The assumptions that restrain us from understanding consciousness
by: Aru, Jaan
Published: (2025)

Fusion Learning from Dynamic Functional Connectivity: Combining the Amplitude and Phase of fMRI Signals to Identify Brain Disorders
by: Hu, Jinlong, et al.
Published: (2026)

Why the Unfinished Keeps Returning: Canxianization and the Dynamics of Conscious Priority
by: Cai, Hengjin, et al.
Published: (2026)

Features have life history. And we should care
by: Stecher, Philipp, et al.
Published: (2026)

Retina gap junctions support the robust perception by warping neural representational geometries along the visual hierarchy
by: Yue, Yang, et al.
Published: (2026)