Consciousness and the Experience of Systems

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• Lead Author:
• Gary Smith

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Acknowledgement

This article reflects established knowledge from systems science and systems engineering, organized and collated for the SEBoK. Drafting support was provided by OpenAI’s ChatGPT, with all content reviewed and finalized by the lead author, who retains full responsibility.

Framing and Definitions

This article is part of the "Nature of Systems" knowledge area. Experience and consciousness are foundational concepts in the Fit dimension, complementing the Form-oriented concepts of identity, togetherness, behavior, and dynamics, and the Function-oriented concepts of cycles, phases, purpose, and capabilities. These two concepts describe how systems participate in and make sense of their environments.

• Experience is how a system encounters, senses, and responds to its environment. All systems experience the world to some degree, but complexity increases the richness and nuance of this encounter.
• Consciousness is the integration of experience into awareness. It ranges from basic responsiveness in physical systems to reflective, intentional cognition in higher-order systems.

These concepts reflect the shift from describing systems mechanistically to understanding them as participants in a relational, evolving whole.

"Living systems are cognitive systems, and living as a process is a process of cognition." — (Maturana & Varela 1980)

"Anticipatory systems contain models of themselves and their environment, enabling them to act in present terms for future states." — (Rosen 1985)

"All conscious systems share the capacity to integrate information across a whole, though in differing degrees." — (Tononi 2004)

"Consciousness can be understood at multiple levels, with richer forms emerging with greater systemic complexity." — (Jonkisz 2016)

Position in the Fit–Form–Function Framework:.

Experience and consciousness are the apex Fit concepts. They govern how systems interpret qualities, ascribe value, and evolve in relation to their context.

Introduction: Why Experience and Consciousness Matter

Experience and consciousness clarify how systems live in, sense, and adapt to their context. While typically associated with human cognition, these concepts generalize to all systems as properties that scale with complexity.

• Physical systems experience interaction through forces and energy exchanges.
• Biological systems sense, perceive, and adapt.
• Social systems create shared meaning, culture, and governance.
• Engineered systems increasingly require attention to user experience, AI autonomy, and situational awareness.

These concepts help bridge:

• Qualities (how well a system performs)
• Value (why it matters in a context)
• Experience (how systems encounter context)
• Consciousness (how systems interpret and act on this encounter)

Understanding experience and consciousness allows engineers to design systems that support trust, ethical behavior, and long-term sustainability.

Frameworks Addressing Experience and Consciousness

A variety of traditions offer perspectives on how systems experience and integrate awareness.

Philosophical Traditions

• Phenomenology (Husserl, Merleau-Ponty 1931): focuses on lived experience as the foundation of meaning.
• Mind-body problem & qualia: address whether consciousness is reducible or emergent.
• subjective experience: (Chalmers 1996) consciousness poses a "hard problem" of .

Neuroscience and Cognitive Science

• Integrated Information Theory (IIT) (Tononi 2004, 2012): consciousness correlates with the degree of integrated information (Phi).
• Global Workspace Theory (Baars 1988): models consciousness as information broadcast across subsystems.
• Predictive Processing (Friston 2010): consciousness emerges from prediction-error minimization.

Systems Science

• Autopoiesis (Maturana & Varela 1980): living systems produce and regulate themselves; cognition is intrinsic.
• Anticipatory Systems (Rosen 1985): consciousness is modeled as the ability to simulate future outcomes.
• Relational Holon (Blockley, Smith 2025): integrates system, context, and reflection.
• Levels of consciousness: (Jonkisz 2015): presents a graded model of consciousness across system complexity.

Engineering and Applied Frameworks

• HSI and UX Design: ensure that human users experience systems meaningfully and safely.
• Autonomy levels (e.g., SAE J3016): imply degrees of system situational awareness.
• AI systems: simulate perceptual and reflective capabilities without full consciousness.

Integrative Perspectives

Experience and consciousness are deeply interconnected:

• Experience is the encounter with environment.
• Consciousness is the integration and interpretation of that experience.

Their systemic coherence arises from:

• Complementarity: One grounds the other; both are needed.
• Scaling: All systems experience; more complex systems develop reflective awareness.
• Holonic integration: Systems exist within wholes, and consciousness links individual and collective perspectives.

In the relational holon model (Blockey, Smith 2025):

• Experience corresponds to engagement at the system-context boundary.
• Consciousness arises in the reflective and orienting quadrants.
• The cycle of praxis connects sensory input, integration, interpretation, and action.

This model bridges:

• Natural systems (perception, survival)
• Social systems (shared meaning, culture)
• Engineered systems (human interaction, AI autonomy)

Archetypes of Experience and Consciousness

These archetypes clarify how systems participate in context, and how richer systems perceive and integrate meaning.

Experience Archetypes	Description	Example Systems
Sensation	Direct encounter with stimuli	Sensors, immune cells, physical particles
Perception	Organizing and interpreting input	Animals, pattern recognition systems
Emotion/Affect	Valenced evaluation of experience	Human response, social trust mechanisms
Interaction	Reciprocal engagement with environment	Ecosystems, conversational agents

Consciousness Archetypes	Description	Example Systems
Awareness	Capacity to register and respond	Drivers, pilots, automated vehicles
Self-reflection	Awareness of internal state	Humans, adaptive monitoring tools
Intentionality	Goal-directed awareness	Strategic planners, autonomous agents
Collective consciousness	Shared awareness among agents	Cultures, swarm intelligence, organizations

Integrative Archetypes:

• Anticipatory capacity: (Rosen 1985)
• Autopoietic cognition: (Maturana, Varela 1980)
• Relational reflexivity: (Blockley, Smith 2025)

These demonstrate how experience and consciousness scale from system structure to meaningful participation.

Implications for Systems Engineering

Experience and consciousness may appear abstract, but they have direct implications for systems engineering. Engineers increasingly design systems that shape human experience, simulate conscious-like properties, or participate in collective decision processes. Addressing these concepts ensures that engineered systems remain fit for purpose, trustworthy, and sustainable.

Area	Implication
Human-System Integration	Design must account for human perception, trust, interpretation, and cognitive load.
Autonomy and AI	AI systems simulate conscious-like behavior (awareness, modeling, adaptation).
Ethical Design	Systems affect lived experience and require consideration of dignity, fairness, and responsibility.
Collective Systems	Organizational awareness and decision-making must align with shared meaning and goals.
Lifecycle Integration	Experience accumulates; consciousness-like properties must be embedded in adaptive feedback loops.

Systems engineering increasingly operates in domains where:

• User experience shapes effectiveness.
• Trust is essential for adoption.
• Autonomous systems interact with uncertain environments.

This makes experience and consciousness not optional curiosities, but core design and lifecycle concerns.

Summary

Experience and consciousness are the capstone concepts in the Fit dimension of systems. They represent how systems participate in, perceive, and integrate meaning from their environment.

Key insights:

• Experience is universal: all systems are affected by and interact with their environment. The richness of experience scales with complexity.
• Consciousness is the integration of experience into awareness. It includes responsiveness, anticipation, self-reflection, and intentionality.
• Archetypes of experience (sensation, perception, emotion, interaction) and consciousness (awareness, self-reflection, collective meaning) recur across physical, biological, social, and engineered systems.
• Integrative concepts such as anticipation, autopoietic cognition, and relational reflexivity demonstrate how experience and consciousness deepen system Fit.
• These properties underpin emerging concerns in AI, ethics, human–system integration, and systemic responsibility.

By clarifying experience and consciousness as properties of all systems, scaling with complexity from simple responsiveness to reflective awareness, we affirm that systems are participants in the greater whole. This recognition strengthens the bridge between systems science and systems engineering, ensuring that practice attends not only to technical performance but also to meaning, trust, and responsible participation in life’s unfolding system of systems.

References

Works Cited

Baars, B. J. (1988). A Cognitive Theory of Consciousness. Cambridge University Press.

Chalmers, D. J. (1996). The Conscious Mind: In Search of a Fundamental Theory. Oxford University Press.

Friston, K. (2010). "The Free-Energy Principle: A Unified Brain Theory?" Nature Reviews Neuroscience, 11, 127–138.

Husserl, E. (1931). Ideas: General Introduction to Pure Phenomenology. London: George Allen & Unwin.

Jonkisz, J. 2015. "Consciousness: Individuated Information in Action." Frontiers in Psychology, 6:1035. https://doi.org/10.3389/fpsyg.2015.01035

Blockley, D, Smith G. (2025). "Relational Holon: Systems Science and Information Theory in Engineering Practice and Beyond." Journal of Information Science. https://doi.org/10.1177/01655515251353192

Maturana, H. R., & Varela, F. J. (1980). Autopoiesis and Cognition: The Realization of the Living. D. Reidel Publishing.

Rosen, R. (1985). Anticipatory Systems: Philosophical, Mathematical and Methodological Foundations. Pergamon Press.

Tononi, G. (2004). "An Information Integration Theory of Consciousness." BMC Neuroscience, 5(1), 42. https://doi.org/10.1186/1471-2202-5-42

Tononi, G. (2012). Phi: A Voyage from the Brain to the Soul. Pantheon Books.

Primary References

Merleau-Ponty, M. (1945). Phenomenology of Perception. Gallimard.

Tononi, G., & Koch, C. (2015). "Consciousness: Here, There and Everywhere?" Philosophical Transactions of the Royal Society B, 370(1668), 20140167.

Baars, B. J., Franklin, S., & Ramsoy, T. Z. (2013). "Global Workspace Dynamics: Cortical Binding and Propagation Enables Conscious Contents." Frontiers in Psychology, 4, 200.

Varela, F., Thompson, E., & Rosch, E. (1991). The Embodied Mind: Cognitive Science and Human Experience. MIT Press.

Additional References

Wiener, N. (1948). Cybernetics: Or Control and Communication in the Animal and the Machine. MIT Press.

Ulrich, W. (1994). Critical Heuristics of Social Planning: A New Approach to Practical Philosophy. Wiley.

Damasio, A. (1999). The Feeling of What Happens: Body and Emotion in the Making of Consciousness. Harcourt Brace.

Dehaene, S. (2014). Consciousness and the Brain: Deciphering How the Brain Codes Our Thoughts. Viking.