Journal of Artificial Intelligence and Consciousness
October 25, 2021
E.c. Garrido-Merchán, M. Molina, Francisco M. Mendoza-Soto
4 citations
Consciousness may offer evolutionary advantages that can be replicated in autonomous agents. This work presents a cognitive model for an autonomous agent based on global workspace theory, where a conscious-like bottleneck integrates and controls information from subsystems like attention, memory, and inner preferences. The agent navigates an environment of multiple independent magnitudes, adapting to find optimal positions according to its preferences. Large experiments show that agents with this architecture benefit from enhanced performance, supporting the idea that imitating a conscious cognitive structure can improve autonomous decision-making and adaptability.
Journal of Artificial Intelligence and Consciousness
September 1, 2024
Robin L. Zebrowski
This paper identifies common ground between Carlos Montemayor's account of mind and AI, as presented in his précis for *The Prospect of Humanitarian Artificial Intelligence*, and enactivist philosophy. The author notes that Montemayor emphasizes autonomy, embeddedness, perspective, and social interaction, yet does not engage with 4E (embodied, embedded, extended, enactive) cognitive science, particularly enactivism, despite his heavy reliance on biological and autonomous features to distinguish intelligence from consciousness.
Journal of Artificial Intelligence and Consciousness
March 1, 2026
Anna Strasser
Large language models (LLMs) can perform tasks that in humans require reasoning, planning, and understanding—abilities normally linked to consciousness. However, these abilities might be realized in artificial systems without consciousness. This paper examines whether LLMs solve tasks in fundamentally different ways from humans and whether we can justifiably ascribe agency or socio-cognitive abilities to them. It discusses benchmarks, data contamination, and robustness issues, and uses Daniel Dennett's distinction between competence without comprehension and competence with comprehension to explore whether artificial systems could possess socio-cognitive abilities that fall somewhere between the two. The analysis also addresses general difficulties in attributing abilities, including consciousness, to AIs.
Journal of Artificial Intelligence and Consciousness
February 26, 2026
Perla Carrillo Quiroga
Consciousness in artificial intelligence is compared to human consciousness by examining properties such as attention, cognition, perception, emotion, embodiment, creativity, and self-awareness. Current AI systems partially or functionally represent all of these except self-awareness, which remains uniquely human. A theoretical framework for artificial consciousness is proposed, categorizing components like affective computing, integrated perception, self-model, cognition, embodied cognition, attention, and creative processing. The ethical and social implications of potential artificial consciousness are emphasized and reflected upon.
Journal of Artificial Intelligence and Consciousness
September 1, 2025
Subhash Kak
A conscious agent increases entropy through actions that contribute to irreversibility. During its lifespan, the agent transitions from a live information state (1) to a death state (0). This superposition of states is recognized conceptually in psychology and belongs to quantum biology. The information state may be frozen or reversed using the observation-based quantum Zeno effect, which for an individual would imply self-observation. Because mind and body processes are connected recursively at several levels, reversing the information state could affect aging processes, potentially increasing lifespan through a system of self-observation.
Journal of Artificial Intelligence and Consciousness
October 27, 2024
C. Johnstone, Prashant S. Alegaonkar
A review of five physical approaches to consciousness—von Neumann–Wigner, orchestrated objective reduction, integrated information, consciousness as a state of matter, and electromagnetic field—finds that all except the von Neumann–Wigner approach agree the brain generates and detects consciousness, though they offer distinct explanations. None of the approaches are close to experimental verification, and further work on experimental design and new theories is needed.
Journal of Artificial Intelligence and Consciousness
September 1, 2024
Víctor Cantero-Flores
A philosophical paper argues that attention alone may not be sufficient for epistemic agency or genuine artificial intelligence, and that phenomenal consciousness cannot be completely separated from questions about intelligence, agency, and attention. The author questions Carlos Montemayor's proposal that attention, disconnected from phenomenal consciousness, can account for epistemic agency in AI. Deeper metaphysical questions may need to be addressed.
Journal of Artificial Intelligence and Consciousness
July 23, 2024
Parker Settecase
The paper examines whether it is possible to justifiably attribute consciousness to artificial intelligent systems. It reviews the history of AI, identifies the most promising research program for machine consciousness, and evaluates three methods for knowing if a machine is conscious: sufficient organizational similarity to human thinkers, inference to the best explanation, and the idea that panpsychism (everything is conscious) would automatically grant consciousness to AI. The author argues that all three methods are inadequate because each faces serious philosophical problems.
Journal of Artificial Intelligence and Consciousness
March 1, 2024
Mariusz Stanowski
Consciousness is explained as the sensation of energy interaction, akin to touch or pain but more complex. The paper argues that understanding consciousness requires grasping contrast, interaction, complexity, and emergence, offering new definitions for these terms. This objective account is applied to artificial intelligence, proposing solutions for AI consciousness and creativity.
Journal of Artificial Intelligence and Consciousness
March 1, 2024
Yoshija Walter
Artificial intelligence that can interpret mental states from neural patterns challenges traditional mind-body dualisms—substance, interaction, property, predicate, and emergent—by correlating mental and physical states. The paper argues that these dualistic theories can adapt to AI insights, prompting a re-evaluation rather than a refutation of dualism. AI's ability to bridge mental and physical domains invigorates philosophical debate about consciousness and mind-body relationships rather than ending it.
Journal of Artificial Intelligence and Consciousness
October 31, 2023
Subhash Kak
Consciousness, often linked to free will, conflicts with the causal closure of physics, where every event has a physical cause. By analyzing nested physical systems, the paper argues that if a system had agency, observers could not exist within it. Since complex systems form nested hierarchies, this suggests consciousness cannot emerge from complexity alone. The existence of consciousness in cognitive agents implies it belongs to a non-physical dimension, making machine consciousness unattainable. These arguments are applied to reinterpret two quantum theory paradoxes relevant to quantum information theory.
Journal of Artificial Intelligence and Consciousness
September 1, 2023
Fernando Ruette
A mathematical model using operators and Hilbert space is proposed to understand consciousness and the relationship between human consciousness (HC) and artificial consciousness (AC). The model considers external and internal realities, with cyclic interaction between internal reality, decision-making, and body-brain operators suggested as the origin of consciousness. The authors argue that creating AC and cyborg consciousnesses (CC) will enable the study of HC through experimentation by evaluating emotion functions such as values, feelings, penalties, and rewards, ultimately transforming HC.
Journal of Artificial Intelligence and Consciousness
March 1, 2023
Anita Pacholik-Żuromska, Gerhard Preyer
Pre-reflective self-consciousness—the immediate awareness one has of oneself prior to any act of reflection—cannot be adequately captured by computational or mathematical models of the mind. Theories that treat this basic self-awareness as a relation (e.g., between a subject and an object) fall into a paradox. Following the New Heidelberg School, the paper argues that pre-reflective consciousness is instead a non-relational, intrinsic quality of experience. Such an approach avoids the paradox and better accounts for the self-determination of mental states that are not directed toward anything else.
Journal of Artificial Intelligence and Consciousness
March 1, 2023
Rodrick Wallace
Consciousness in higher animals, with its 100-millisecond time constant, is a simplified version of more complex cognitive systems like wound healing and immune function, which emerged from information crosstalk between cognitive modules. This stripped-down nature suggests it should be possible to build a fast, single-workspace conscious machine mimicking the human global workspace. Tied to a backbrain AI for hyperrapid pattern responses, such a machine would exhibit elementary emotions. A designer might instead use high-speed electronics to create multiple-workspace systems less prone to inattentional blindness. The ultimate utility of such machines remains unclear, explored here through asymptotic limit theorems of information and control theories.
Journal of Artificial Intelligence and Consciousness
December 21, 2022
P. Haikonen
The concept of qualia is vague due to many conflicting definitions, limiting its theoretical value. A more general redefinition of qualia is proposed, arguing that this redefined concept is essential for addressing the mind–body problem, the problem of consciousness, and the symbol grounding problem in physical symbol systems. The redefined qualia are necessary for artificial intelligence systems to operate with meanings. Finally, it is suggested that robots possessing such qualia may be conscious.
Journal of Artificial Intelligence and Consciousness
December 1, 2022
Izak Tait, Ziqi Wang, Tahua O’Leary et al.
Existing theories of consciousness applied to artificial intelligence are anthropocentric, even those designed for AI, because they rely on human and animal models. This paper argues that such frameworks are built on insecure foundations by comparing human and AI cognitive architectures, examining the consequences of their behaviors, and exploring human neurological conditions that may hint at what a conscious AI could be. It concludes by proposing a non-anthropocentric foundation for cognition that could lead to a truly AI-focused framework of consciousness.
Journal of Artificial Intelligence and Consciousness
September 1, 2022
Marc Ebner
If consciousness were fully understood, artificial consciousness should be possible. The common objection that qualia are subjective and cannot be re-created artificially is challenged by showing that qualia are grounded in reality and not arbitrary. For the quale color, perceived color corresponds to a three-dimensional value describing an object's spectral reflectance function and is comparable across individuals. The authors presume this holds for other qualia such as pain, hunger, or love. The theory proposes that a specific assembly of neurons processes perceptions and communicates this information to peer group members, constituting conscious information processing. This assembly analyzes bodily experiences, keeps records, and explains experiences to peers.
Journal of Artificial Intelligence and Consciousness
October 13, 2021
Wenjie Huang, A. Chella, A. Cangelosi
A model integrating global workspace theory with an attention mechanism is proposed as a step toward machine consciousness. In simulations, the agent shifted attention among multiple stimuli, reflecting the dynamics of conscious content. It also reproduced attentional blink and lag-1 sparing, two well-known human attention effects, suggesting compatibility with human cognitive processing. The model uses separate workspace nodes to reduce computation while enabling global availability, embeds attention as a competition mechanism for conscious access, and includes a synchronization mechanism that preserves the lag-1 sparing effect while retaining the attentional blink effect. This framework provides a foundation for future work in artificial consciousness.
Journal of Artificial Intelligence and Consciousness
September 1, 2021
David Gamez
Measuring intelligence and consciousness accurately is essential for understanding their relationship. While human intelligence can be measured reasonably well, existing methods only partly apply to non-human animals and not at all to artificial systems. Universal measures that depend on goals and rewards have serious limitations. This paper presents a new universal algorithm for measuring intelligence based on a system's ability to make accurate predictions, applicable to humans, non-human animals, and artificial systems. Preliminary experiments show it can measure the changing intelligence of an agent in a maze environment. This measure could improve understanding of intelligence and consciousness and has practical applications, especially in AI safety.
Journal of Artificial Intelligence and Consciousness
September 1, 2020
Henry Shevlin
The science of consciousness has advanced but faces difficulty reaching consensus about artificial consciousness. Practical and ethical questions about whether artificial systems can suffer may soon arise, yet methods for assessing consciousness in humans and animals do not straightforwardly apply to artificial systems. The author proposes developing ecumenical heuristics for artificial consciousness that are intuitively plausible, theoretically neutral, and scientifically tractable. General intelligence—understood as robust, flexible, integrated cognition and behavior—is argued to satisfy these criteria and could provide a basis for making tentative assessments of which artificial systems are most likely to be conscious.
Journal of Artificial Intelligence and Consciousness
September 1, 2020
R. Sanz, Esther Aguado
Machine consciousness research combines computers, robots, neuropsychology, sociology, and philosophy. This mix creates both opportunity and risk of endless, unproductive debates that may not improve machine building. The paper analyzes this situation, advocates for an engineering approach to machine consciousness, and proposes a strategy centered on machine understanding to move beyond the current stagnation.
Journal of Artificial Intelligence and Consciousness
September 1, 2020
Ron Chrisley
The paper argues that a capacity for certain kinds of meta-knowledge is central to modeling consciousness, particularly the recalcitrant aspects of qualia, in computational architectures. It presents a novel objection to Frank Jackson's Knowledge Argument against physicalism, showing that the supposition of a physically omniscient person, Mary, who has not experienced seeing red, is logically inconsistent due to epistemic blindspots. Even if the argument is made consistent by assuming a more limited physical omniscience, it remains invalid because there is a physical fact (a recursive conditional epistemic blindspot) that Mary cannot know before experiencing red but can know afterward. The paper discusses implications for machine consciousness.
Journal of Artificial Intelligence and Consciousness
April 29, 2020
G. Ng, Wang Chi. Leung
Artificial Intelligence has achieved notable successes in natural language processing, computer vision, speech recognition, robotics, and autonomous systems over the past decade, but the text is truncated and does not provide a complete argument or finding.
Journal of Artificial Intelligence and Consciousness
March 1, 2020
David Gamez
Intelligence and consciousness, whether natural or artificial, may be linked but are distinct properties. Intelligence is a functional property measurable through behavior, but standard human tests fail for radically different animals and AI systems; new algorithms aim to measure intelligence universally. Consciousness, by contrast, appears tied to specific spatiotemporal patterns in particular physical materials, and scientific study has advanced by identifying neural correlates and developing mathematical theories to map between physical and conscious states. The paper outlines weak inferences about their relationship and argues that real progress requires practical universal measures of intelligence and reliable mathematical theories of consciousness.
Journal of Artificial Intelligence and Consciousness
March 1, 2020
Pentti O. A. Haikonen
Artificial Intelligence will not achieve general intelligence unless it can incorporate meanings into its computations, a challenge known as the Symbol Grounding Problem. Current computers manipulate symbols without meaning, and proposed solutions involve self-explanatory sensory information, which can only be used in neural network machines different from existing digital computers. In humans, such self-explanatory information takes the form of qualia, which are tied to phenomenal consciousness. The author hypothesizes that solving the Symbol Grounding Problem is unavoidably connected to consciousness: machines that use self-explanatory information would be conscious.