Skip to content

Consciousness Criteria Are Not Continuity Criteria: The Subjective Continuity Problem for Theories of Consciousness and Artificial Minds

Oct 2026 · Zenodo (CERN European Organization for Nuclear Research)
Philosophy and Theoretical Science

Abstract

Theories of consciousness seek to explain what makes a system conscious, but they do not necessarily explain what makes a later conscious system the same subject as an earlier one. This article identifies this distinction as the Subjective Continuity Problem and examines its implications for consciousness science and artificial minds. I assess five influential approaches—global neuronal workspace theory, integrated information theory, higher-order theories, predictive processing, and recurrent processing theory—and find that none provides an explicit criterion for subjective continuity. Three conceptual challenges—interruption, reconstruction, and replication—together with a novel control case, the lockstep swap, demonstrate that consciousness criteria alone do not determine whether a particular subject persists when memory, personality, behaviour, and functional organisation are preserved. I then develop the AI Continuity Test, which applies six routine computational operations—pause and resume, copy, fork, merge, rollback, and migration—to examine whether existing theories can determine the number and persistence of subjects across changes in computational state and physical substrate. The analysis distinguishes consciousness detection from continuity determination and identifies unresolved questions concerning subject individuation, branching, restoration, and the aggregation of welfare. Even if Parfitian reductionism is correct that personal identity involves no further fact beyond physical and psychological relations, explicit criteria remain necessary for consistently counting and tracking subjects in scientific, medical, legal, ethical, and artificial-intelligence contexts. I do not propose a mechanism or claim to solve the problem. Instead, I specify the conditions an adequate continuity criterion must address, establishing subjective continuity as a distinct explanatory challenge for theories of consciousness.

View source

Similar papers

#artificial intelligence Open access May 2023

Evaluating the Performance of Large Language Models on GAOKAO Benchmark

GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...

Xiaotian Zhang, Chun-yan Li, Yi Zong et al. · 216 citations · ⚡17

KTO: Model Alignment as Prospect Theoretic Optimization

This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.

Kawin Ethayarajh, Winnie Xu, Niklas Muennighoff et al. · 195 citations · ⚡28
#artificial intelligence Open access Jul 2024

Gender, Race, and Intersectional Bias in Resume Screening via Language Model Retrieval

This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.

Kyra Wilson, Aylin Caliskan · 131 citations · ⚡8
#artificial intelligence Review Nov 2024

How to Build a Quantum Supercomputer: Scaling from Hundreds to Millions of Qubits

This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...

Masoud Mohseni, Artur Scherer, K. Johnson et al. · 121 citations · ⚡9
#artificial intelligence Review Oct 2025

Ultralytics YOLO Evolution: An Overview of YOLO26, YOLO11, YOLOv8 and YOLOv5 Object Detectors for Computer Vision and Pattern Recognition

This paper presents a comprehensive overview of the Ultralytics YOLO family, emphasizing architectural evolution, benchmarking, deployment, and emerging directions from YOLOv5 through YOLO27, and examines detection, segmentation, depth, classification, pose, oriented detection, tracking, export, quantization, and deplo...

Ranjan Sapkota, Manoj Karkee · 112 citations · ⚡10

Related blog posts

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.