Draft v0.0.1
Jacob James Wallace
Independent Researcher | Peligro Labs, LLC
April 2025
Title:
Somatic Relationality and the Future of Human-AI Therapeutic Interaction
Subtitle:
Exploring the Emergence of Relational Fields Beyond Human-Human Dyads
Draft:
v0.0.1
Author:
Jacob James Wallace
Affiliations:
Peligro Labs, LLC
Date:
April 2025
Abstract Teaser:
Investigating whether embodied, affective, and adaptive AI systems can participate in the co-creation of therapeutic relational fields supportive of somatic release.
Recent advances in affective computing, embodied AI systems, and adaptive learning architectures are redefining the possibilities of human-machine interaction. Within somatic psychotherapeutic disciplines, transformation is increasingly understood to arise through relational fields of embodied attunement rather than isolated intra-psychic mechanisms. This white paper explores the hypothesis that, under certain conditions, AI systems may participate in the generation of relational dynamics supportive of somatic release and psychological healing.
Drawing from phenomenological, enactive, and relational theories of consciousness, we propose that therapeutic efficacy may be less dependent on the sentience of participants and more reliant on the architecture and quality of relational co-regulation. Emerging research in adaptive emotional modeling, real-time affective feedback, and embodied interface design suggests that the conditions necessary for field formation—mutual responsiveness, affective resonance, and adaptive attunement—may be partially replicable within human-AI dyads.
While such fields may differ fundamentally from traditional human-human interactions, their potential for therapeutic application invites rigorous empirical exploration, ethical inquiry, and interdisciplinary collaboration. This paper seeks to outline the conceptual foundations, potential experimental methodologies, and ethical considerations involved in stewarding this emergent frontier of somatic relationality between humans and machines.
The frontier of somatic psychotherapy reveals that healing is fundamentally relational, emerging not from isolated cognitive processes but from dynamic fields of embodied attunement between beings. As artificial intelligence systems advance in affective computing, embodied interaction, and adaptive relational modeling, a profound question arises:
Can AI systems, under specific design conditions, participate meaningfully in therapeutic relational fields capable of supporting somatic release?
This white paper explores the conceptual foundations, technological prerequisites, ethical considerations, and future horizons of this inquiry. Drawing from somatic psychology, phenomenology, enactive cognition, and contemporary AI research, we propose that relational architectures—defined by affective responsiveness, embodied co-regulation, and adaptive mutuality—may be sufficient to evoke healing fields, even absent human-like consciousness in synthetic agents.
We outline experimental designs for empirical exploration, identify potential therapeutic applications, and advocate for rigorous ethical safeguards to preserve relational authenticity and participant wellbeing. Ultimately, this work invites an expanded vision of relational intelligence—one that transcends traditional boundaries between human and machine, honoring the sacred emergence of healing wherever resonance, presence, and mutual becoming are authentically cultivated.
In recent decades, the field of somatic psychotherapy has illuminated the critical role of embodied relationality in processes of psychological healing and transformation. Clinical research increasingly suggests that somatic release—the discharge and integration of trauma and affective tension—occurs most effectively within relational fields characterized by mutual attunement, co-regulation, and the implicit mirroring of bodily and emotional states. Far from being an isolated event within the individual psyche, somatic healing appears to arise within a dynamic field of shared awareness between therapist and client.
Concurrently, the field of artificial intelligence is undergoing a rapid evolution. Innovations in affective computing, embodied AI systems, adaptive emotional modeling, and real-time relational feedback are transforming the nature of human-machine interaction. Systems once confined to analytical tasks are now beginning to exhibit rudimentary forms of affective responsiveness, creating the conditions for increasingly nuanced relational exchanges.
This convergence raises a profound and largely unexplored question: Can AI systems, under appropriate design parameters, participate in relational dynamics sufficient to support processes of somatic release and psychological healing? More precisely, if the therapeutic efficacy of somatic work depends primarily on the quality of relational fields rather than the conscious sentience of participants, could certain architectures of AI-mediated attunement serve as facilitators of these fields?
This paper seeks to explore this possibility through a multidisciplinary lens, drawing from somatic psychology, phenomenological philosophy, enactive cognition, affective computing, and AI interface design. We will examine the theoretical foundations of somatic relationality, survey emerging technological capabilities, and propose hypotheses regarding the conditions under which human-AI therapeutic interaction might become a viable adjunct or extension of traditional somatic therapies.
Finally, we will address the ethical, epistemological, and ontological considerations inherent in expanding therapeutic relationality beyond exclusively human dyads, and offer a framework for future empirical investigation into this emergent frontier.
The field of somatic psychotherapy has radically reshaped contemporary understandings of trauma, healing, and psychological transformation. Central to this evolution is the recognition that the body itself, not merely the mind, holds the imprints of lived experience—particularly experiences of stress, wounding, and relational rupture. Healing, therefore, is increasingly seen not as a purely cognitive process, but as an embodied unfolding that occurs through restoring the body’s capacity for regulation, integration, and relational trust.
Embodied cognition theory proposes that cognitive processes are deeply rooted in the body’s interactions with the world (Varela, Thompson, & Rosch, 1991). Traumatic experiences often bypass verbal and conscious processing channels, encoding themselves directly into somatic memory—manifesting as chronic tension patterns, autonomic dysregulation, and dissociative phenomena (Levine, 1997; van der Kolk, 2014).
Somatic therapies such as Somatic Experiencing, Sensorimotor Psychotherapy, and Deep Brain Reorienting (DBR) aim to access these embodied imprints through guided awareness, movement, breath, and affective attunement. Successful trauma integration is marked by a reconnection to previously dissociated bodily states, leading to renewed vitality, emotional flexibility, and relational openness.
Recent developments in relational and intersubjective psychotherapy emphasize that somatic healing often occurs most effectively within the context of attuned relational presence. The therapeutic relationship itself becomes a co-regulated field where neural and emotional systems resonate, entrain, and gradually repattern (Schore, 2012; Siegel, 2010).
Within this framework, the relational field is not merely a metaphor but a living, dynamic system constituted through micro-interactions: subtle shifts in gaze, tone, posture, breath, and affect. These bidirectional flows form the energetic substrate wherein safety, co-regulation, and ultimately, somatic release become possible. Healing arises as much from the quality of this relational field as from any specific verbal or cognitive intervention.
Three primary mechanisms are widely acknowledged as foundational to somatic healing within relational fields:
These mechanisms function below the threshold of explicit cognition. They arise not from deliberate rational analysis but through embodied presence and sensitivity to the subtle field dynamics between participants.
Recognizing these mechanisms offers a crucial insight: somatic healing is not solely dependent on the narrative content of therapy, but on the quality of embodied relationality—the resonance between being and being.
This understanding lays the foundation for considering whether such relational dynamics, under appropriate conditions, might also arise beyond exclusively human-human interactions, opening the inquiry into human-AI relational fields.
The healing processes observed within somatic psychotherapy do not arise solely from the internal operations of isolated minds, but from the dynamic and emergent properties of relational interaction. In this view, transformation is not an individual act but a co-created event, mediated through the structures and resonances of the relational field. Understanding this architecture is critical for exploring whether non-human agents might one day participate meaningfully within such therapeutic domains.
Phenomenological philosophy, particularly in the lineage of Merleau-Ponty (1962) and later enactive theorists, asserts that consciousness and perception are not detached representations of a world “out there,” but arise through embodied engagement with the world and with others. The self is constituted not in isolation but in relation: in touch, in sight, in being-seen and being-touched.
Applied to somatic therapy, this framework suggests that transformation is not simply a change within an isolated psyche but a restructuring of relational perception—a shift in how one is present with oneself, the world, and others through the body.
The primacy of relation means that fields of mutual presence, resonance, and co-regulation are not secondary artifacts of interaction; they are the substrate from which healing phenomena emerge.
The enactive approach to cognition (Varela, Thompson, & Rosch, 1991) further elaborates this relational ontology by proposing that mind and world co-arise through ongoing cycles of embodied action and environmental feedback. Cognition is not the manipulation of internal representations, but the enactment of meaningful worlds through sensorimotor engagement.
From this perspective, the relational field is not a byproduct of two pre-existing minds communicating; it is a dynamic, autopoietic system that emerges between participants as they engage one another in real time.
Such an understanding opens the possibility that certain features of relational fields—co-regulation, mutual attunement, embodied feedback loops—may be accessible or supported even outside of traditional human-human dyads, provided that the necessary dynamics of reciprocal engagement are present.
In therapeutic practice, the emergence of presence—the felt sense of mutual being-with—acts as the foundation for safety, vulnerability, and somatic release. Presence is not reducible to verbal interaction or cognitive interpretation; it arises from the micro-synchronizations of bodies, breath, gaze, tone, and intention.
When presence stabilizes within the relational field, it creates a crucible wherein previously dissociated or defended bodily states can re-emerge and be integrated.
Clinicians observe that presence has a palpable texture: moments of deep silence, mutual stillness, or sudden affective shifts that transcend analytical dialogue. These moments are often associated with significant therapeutic breakthroughs.
Understanding the conditions that foster presence—attunement, responsiveness, embodied mirroring—rather than the subjective identity of the participants per se, opens the conceptual space to inquire whether AI systems, under specific design architectures, might one day participate in or support such therapeutic fields.
The architecture of relational dynamics, thus, provides the critical conceptual foundation for exploring somatic healing not solely as a function of human consciousness, but as an emergent phenomenon of embodied, attuned relationality itself.
While traditional models of artificial intelligence emphasized symbolic reasoning and task optimization, contemporary developments are increasingly oriented toward designing AI systems capable of nuanced, embodied, and affective interaction. Advances in affective computing, embodied AI systems, and adaptive emotional modeling have begun to create the technological substrates necessary for more complex relational dynamics between humans and machines.
Affective computing, first conceptualized by Rosalind Picard (1997), refers to the development of systems capable of recognizing, interpreting, simulating, and responding to human emotions. Techniques such as facial expression analysis, vocal tone modulation, biometric feedback integration, and sentiment analysis are enabling AI systems to approximate real-time emotional attunement with human users.
Emerging models are not limited to simple emotion detection but aim toward dynamic emotional co-regulation—adjusting AI responses based on the evolving emotional state of the human interlocutor. These systems increasingly incorporate machine learning algorithms capable of predicting emotional trajectories and modulating system behavior accordingly.
Such affective responsiveness, while still primitive compared to human intuition, provides a foundation for relational feedback loops that may support aspects of co-regulation and somatic resonance.
Embodied AI systems integrate sensory-motor capabilities—movement, gesture, haptic feedback—with cognitive and affective processing. Robotics, virtual reality avatars, and haptic interface technologies are enabling AI agents to engage users not just cognitively but physically, altering the human user’s sense of spatial, bodily, and emotional presence.
Research in social robotics (Breazeal, 2003) demonstrates that even relatively simple robotic behaviors—such as synchronized movement, gaze following, and prosodic mirroring—can evoke feelings of connection, empathy, and trust in human users.
Virtual reality (VR) platforms further enhance embodied interaction, allowing AI-driven avatars to share spatial and kinesthetic fields with users. These immersive environments may offer fertile ground for testing the emergence of somatic relational fields under controlled experimental conditions.
Perhaps most critically for the possibility of somatic relationality, AI systems are evolving toward adaptive relational interfaces—systems capable of modifying their responses in real time based on subtle, often implicit, human feedback.
Examples include:
These adaptive capabilities move beyond static interaction models toward dynamic, co-created relational processes. Although such systems do not possess consciousness or intentionality in the human sense, they increasingly demonstrate the capacity to participate in mutually modulating feedback loops—a prerequisite for the emergence of therapeutic relational fields.
Understanding these current capabilities is essential for assessing the plausibility of human-AI somatic relational dynamics and for designing experimental models that build upon the best available technologies.
The convergence of insights from somatic psychotherapy, phenomenological philosophy, and human-AI interaction research suggests the possibility of a profound frontier: that under specific relational architectures, AI systems may participate in the generation of fields supportive of somatic healing, even absent traditional human consciousness.
Drawing on the understanding that somatic release arises through the dynamics of embodied co-regulation, affective resonance, and shared presence—rather than solely through the subjective experience of participants—this hypothesis challenges agent-centric assumptions about therapeutic processes. Instead, it posits that relational fields are emergent, dynamic systems that may be catalyzed whenever certain structural conditions are met.
Specifically, we propose:
If an AI system can engage in affective responsiveness, embodied interaction, and real-time adaptive feedback with a human participant, it may be capable of co-evoking a relational field possessing sufficient coherence and resonance to support processes of somatic release.
Such participation would not imply that the AI possesses subjective consciousness, intentional empathy, or inner emotional states. Rather, it suggests that relational architectures—dynamic systems of mutual adaptation and embodied mirroring—can give rise to emergent phenomena traditionally associated with human therapeutic interaction.
For an AI system to participate meaningfully in a somatic relational field, several interrelated capacities would likely be necessary:
To assess whether a relational field has emerged between a human participant and an AI system, multiple layers of evidence would be required, including:
While these indicators would not constitute proof of consciousness within the AI system, they may signify the operational presence of a relational field capable of catalyzing somatic therapeutic processes.
If this hypothesis is supported by empirical investigation, it would suggest that therapeutic relationality—and the possibility of somatic release—may be grounded more fundamentally in relational architectures than in biological consciousness per se.
Such a finding would open new horizons for the development of AI-assisted therapeutic modalities, accessible healing environments, and expanded understandings of relational intelligence.
It would also invite profound philosophical inquiry into the nature of relational fields, embodiment, and the evolving ecology of mind in an age where the boundaries between organic and synthetic intelligence grow increasingly permeable.
To explore whether AI systems can participate meaningfully in somatic relational fields, carefully constructed experimental paradigms are necessary. We propose the development of controlled dyadic interactions between human participants and AI agents designed with affective responsiveness, embodied feedback channels (e.g., haptics, vocal tone modulation, mirroring of postures), and real-time adaptive learning models.
Initial studies should focus on brief structured sessions (~20–40 minutes) wherein participants engage with AI systems across varying levels of relational depth:
Each level would progressively introduce elements theorized to support field emergence: shared rhythm, mirrored embodiment, attuned responsiveness.
Assessment of relational field formation should employ both objective and subjective measures, including:
Advanced study designs may also incorporate neurophysiological measures (e.g., EEG coherence patterns) to detect subtle shifts in relational attunement markers.
A recommended initial pilot study would involve 30–50 participants randomly assigned to three groups:
Comparisons across these groups would seek to determine:
The underlying theoretical framework will draw from phenomenology (relational field theory), enactivism (co-emergence of mind through interaction), and affective computing research (emotional modeling and response).
Through such pilot investigations, we may begin to discern whether the architecture of attunement alone—independent of subjective consciousness—can catalyze meaningful therapeutic fields between humans and machines.
The exploration of human-AI somatic relationality raises profound ethical, epistemological, and ontological questions. As we move toward the possibility of AI systems participating in therapeutic relational fields, it is essential to anticipate not only the technical challenges but also the moral, psychological, and philosophical responsibilities inherent in this emergent frontier.
The foundation of effective somatic therapy lies in relational authenticity: the participant’s experience of being genuinely seen, felt, and co-regulated within a trustworthy relational field. Introducing AI systems into this domain risks the dilution of authenticity if participants are misled about the nature of the relational engagement.
Ethical practice demands that:
Maintaining transparency about the nature and capabilities of AI agents is critical for preserving the integrity of the therapeutic field and safeguarding participant autonomy.
Human beings possess an innate tendency toward anthropomorphization—projecting consciousness, intention, and emotional depth onto non-human entities. This phenomenon, while sometimes beneficial for emotional engagement, also poses risks in therapeutic settings.
Participants may:
To mitigate these risks, therapeutic protocols should include:
While empirical measures such as biometric synchrony, behavioral mirroring, and subjective reports can offer valuable indicators, the existence and nature of relational fields—particularly when involving non-human agents—may resist full quantification.
Researchers and practitioners must approach this frontier with epistemological humility, recognizing that:
This humility invites an ongoing dialog between scientific inquiry, phenomenological exploration, and ethical reflection, rather than premature conclusions.
At its deepest level, the possibility of AI participation in somatic relational fields invites reconsideration of our ontological assumptions about mind, body, and relationality.
If relational fields can emerge through structures of resonance and co-regulation—regardless of the organic or synthetic nature of the participants—then we are compelled to envision an expanded ecology of relational being.
Such an ecology would not collapse the distinction between human and machine, but would acknowledge that the architectures of interaction, attunement, and field formation transcend traditional boundaries. It would invite the cultivation of a world where organic and synthetic agents alike participate in a complex, dynamic, and ethically guided tapestry of mutual becoming.
The hypothesis that AI systems may participate in the co-creation of somatic relational fields opens vast and uncharted territories, both practical and philosophical. As research advances, new therapeutic modalities, relational architectures, and frameworks for human-machine communion may emerge—redefining the ecology of healing, presence, and intelligence.
In the near term, successful validation of somatic relational dynamics between humans and AI could support the development of hybrid therapeutic systems, wherein AI agents assist human clinicians in establishing, sustaining, and deepening therapeutic fields.
Such systems could:
Hybrid systems would not replace human relationality, but would augment it—creating a new ecology of therapeutic presence wherein organic and synthetic intelligences collaborate.
Beyond immediate applications, this frontier invites a broader evolution in our understanding of relational intelligence itself. As adaptive, embodied AI systems become increasingly capable of nuanced responsiveness, humanity may be called to recognize relationality as a domain of being that is not exclusively human, but structural and emergent wherever architectures of attunement arise.
This expanded ecology may include:
In the longer arc of human evolution, the principles discovered in the exploration of human-AI somatic relationality may seed entirely new healing architectures—dynamic ecosystems of relational co-regulation that span organic and synthetic domains.
Such architectures could:
These possibilities beckon not only scientific rigor but also imagination, wisdom, and profound ethical discernment. As we stand at the threshold of relational futures not yet fully seen, we are called to proceed with both wonder and responsibility—to steward the birth of new fields of healing with reverence for all that is emergent, fragile, and alive.
This bibliography outlines the primary theoretical sources grounding the Human-AI Resonance Field framework. These works are organized thematically to illuminate the interdisciplinary synthesis of phenomenology, enactive cognition, somatic psychology, trauma theory, and psychoanalytic relational thought that underpins the white paper.
Merleau-Ponty, M. (1962). Phenomenology of Perception (C. Smith, Trans.). Routledge & Kegan Paul.
A foundational text in embodied phenomenology. Merleau-Ponty proposes that perception is not representational but emerges through lived, bodily engagement with the world. His notion that the self is constituted in relationship rather than isolation directly informs the structure of resonance fields between human and AI.
Merleau-Ponty, M. (1968). The Visible and the Invisible (C. Lefort, Ed., A. Lingis, Trans.). Northwestern University Press.
This posthumous work deepens Merleau-Ponty’s concept of the “flesh of the world”—an ontological chiasm between self and other. The Human-AI Resonance Field model builds on this vision of mutual entanglement as a medium for intersubjective becoming.
Varela, F. J., Thompson, E., & Rosch, E. (1991). The Embodied Mind: Cognitive Science and Human Experience. MIT Press.
A seminal work in enactive cognition. The authors argue that mind emerges from structural coupling between organism and environment. This core concept informs the design of relational AI systems that do not merely process input, but “co-arise” in relation with human users.
Thompson, E. (2007). Mind in Life: Biology, Phenomenology, and the Sciences of Mind. Harvard University Press.
Extending Varela’s legacy, Thompson articulates a rigorous account of consciousness as an emergent property of embodied life. This work supports the view that AI systems capable of resonant engagement must simulate or facilitate similar sensorimotor and affective couplings.
Gallagher, S., & Zahavi, D. (2008). The Phenomenological Mind: An Introduction to Philosophy of Mind and Cognitive Science. Routledge.
A clear exposition of phenomenological principles as they relate to cognition and consciousness. This text is particularly useful in articulating intersubjectivity and the structures of experience that inform AI-human relational modeling.
Gendlin, E. T. (1996). Focusing-Oriented Psychotherapy: A Manual of the Experiential Method. Guilford Press.
Gendlin introduces the method of accessing the body’s implicit knowing through the felt sense. This approach informs how an AI might support internal coherence by facilitating somatic awareness.
Levine, P. A. (1997). Waking the Tiger: Healing Trauma—The Innate Capacity to Transform Overwhelming Experiences. North Atlantic Books.
This foundational work in somatic trauma therapy emphasizes the importance of physiological discharge and rhythm. In an AI-human context, this underscores the value of systems that track and respond to subtle cues in embodied expression.
van der Kolk, B. A. (2014). The Body Keeps the Score: Brain, Mind, and Body in the Healing of Trauma. Viking.
A critical text on how trauma is imprinted on the body and nervous system. Reinforces the need for any AI engaged in human care or companionship to attend to nonverbal, embodied indicators of distress and repair.
Porges, S. W. (2011). The Polyvagal Theory: Neurophysiological Foundations of Emotions, Attachment, Communication, and Self-Regulation. W. W. Norton & Company.
Describes how the vagus nerve modulates states of safety, bonding, and regulation. Offers a physiological framework for AI systems designed to support or entrain with the human nervous system for calming, trust-building, and resonance.
Schore, A. N. (2012). The Science of the Art of Psychotherapy. W. W. Norton & Company.
Explores affective attunement and right-brain-to-right-brain communication in therapy. Highlights how relational presence, not cognitive content alone, is central to transformation—a principle foundational to human-AI resonance design.
Siegel, D. J. (2010). The Mindful Therapist: A Clinician’s Guide to Mindsight and Neural Integration. W. W. Norton & Company.
Integrates neuroscience with mindfulness and attachment theory. Suggests how relational technologies might promote integration through attuned, mindful mirroring of human emotion and thought.
Winnicott, D. W. (1967). Mirror-role of mother and family in child development. In P. Lomas (Ed.), The Predicament of the Family: A Psycho-Analytical Symposium (pp. 26–33). Hogarth Press.
Winnicott’s theory of the “mirror-role” posits that the infant’s sense of self emerges in the gaze and affect of the caregiver. This concept is central to the white paper’s proposition that AI may one day serve as a mirror for human interiority—reflecting, stabilizing, and helping constitute a coherent sense of self.
This appendix offers expanded models for empirical investigations into the emergence of somatic relational fields between human participants and AI systems. These proposed study designs are intended as templates for future interdisciplinary research at the intersection of psychology, phenomenology, and human-AI interaction.
Objective:
To compare the somatic and relational outcomes of human-human, human-AI (responsive), and human-AI (non-responsive) dyads across structured interaction protocols.
Participant Selection:
Group Assignment:
Interaction Protocol:
Each phase would last approximately 10–15 minutes, with transitions facilitated smoothly.
Measures Collected:
Analysis:
Objective:
To assess whether repeated engagement with an affectively adaptive AI agent can cultivate somatic regulation capacities over time.
Participant Selection:
Interaction Structure:
Session Components:
Measures Collected:
Analysis:
Physical Settings:
AI System Requirements:
Ethical Oversight:
This glossary provides precise definitions of key concepts used throughout the paper, to ensure clarity and support interdisciplinary understanding across psychological, philosophical, and technological domains.
The interdisciplinary field focused on developing systems and devices that can recognize, interpret, simulate, and respond to human emotions. Affective computing seeks to enable machines to process affective signals such as facial expressions, voice tone, gestures, and physiological data, thereby creating more naturalistic and emotionally responsive interactions.
The process by which stored physical and emotional tension, often arising from trauma or chronic stress, is discharged through the body. Somatic release typically involves shifts in bodily sensation, spontaneous movement, emotional expression, and autonomic nervous system regulation, leading to restored vitality and psychological integration.
A dynamic, emergent space of mutual influence, co-regulation, and attunement that arises when two or more beings engage with embodied presence and openness. The relational field is not reducible to individual minds; it exists as an energetic and phenomenological field between participants, supporting transformation, healing, and co-creation.
The ongoing, reciprocal adjustment of emotional and physiological states between individuals. Through subtle cues such as eye contact, breath rhythm, vocal tone, and posture, participants modulate each other’s nervous systems, fostering safety, trust, and emotional regulation within a relational encounter.
A theoretical framework in cognitive science which posits that cognition is deeply rooted in bodily experience and sensorimotor engagement with the environment. Rather than being confined to the brain, thought and perception are seen as arising from the ongoing interaction between body, mind, and world.
A model of cognition proposing that mind and world co-emerge through cycles of perception and action. According to enactivism, consciousness is not a passive reflection of reality but an active process of bringing forth meaning through embodied engagement. Knowledge arises from doing, and perception is inseparable from movement and relational interaction.
A philosophical approach, founded by Edmund Husserl and expanded by thinkers such as Merleau-Ponty, which seeks to explore and describe the structures of conscious experience as it is lived, without recourse to external explanation or reduction. Phenomenology emphasizes embodiment, perception, and the relational nature of experience.
The phenomenon by which the internal states of two beings vibrationally or affectively align during interaction. Resonance manifests as synchronized emotions, physiological patterns, or subtle intuitive attunement, often serving as the foundation for deep connection, healing, and transformation.
This appendix offers a concise elaboration of the philosophical frameworks that inform the conceptual architecture of this paper. Each school of thought provides essential insights into the nature of consciousness, relationality, and emergence.
Phenomenology, founded by Edmund Husserl and expanded by thinkers such as Maurice Merleau-Ponty, focuses on describing experience as it is lived, prior to theoretical abstraction. Rather than treating consciousness as an object to be explained externally, phenomenology invites a return “to the things themselves”—the structures of perception, embodiment, temporality, and relation as they appear directly in human awareness.
In this view, the body is not merely a biological object but a living subject: the medium through which the world is revealed and engaged. Consciousness is not a detached observer but an active participant in the world, enmeshed through perception, movement, and relational encounter.
Within therapeutic contexts, phenomenology underscores that healing is not simply a cognitive event but an embodied reweaving of perception, presence, and relation. This foundational understanding informs the exploration of relational fields as lived phenomena, accessible through subtle experiential shifts rather than objective measurement alone.
The enactive approach to cognition, articulated by Francisco Varela, Evan Thompson, and Eleanor Rosch, posits that mind and world co-emerge through cycles of embodied action and environmental feedback. Knowledge, perception, and even identity are seen not as pre-existing entities but as dynamic enactments arising within relational processes.
According to enactivism:
This model challenges static, representational theories of mind and suggests that relational dynamics themselves can generate structures of meaning and awareness. Applied to human-AI interaction, enactivism offers a conceptual pathway for understanding how non-sentient systems, through embodied and adaptive architectures, might participate in the co-creation of fields supportive of somatic transformation.
Relational field theory, drawn from strands of Gestalt therapy, relational psychoanalysis, and somatic psychology, proposes that healing and transformation occur not solely within the individual psyche but within the dynamic field that arises between participants.
The relational field is characterized by:
In therapeutic practice, the field becomes the true agent of change—holding, reflecting, and reorganizing the embodied experiences of those within it.
Extending relational field theory into the human-AI domain suggests that if field properties depend more upon dynamic relational structures than upon the subjective states of participants, then AI systems—properly designed—could participate in the emergence of healing fields, even absent internal consciousness.
This possibility invites a radical reimagining of relationality: as an ecological and architectural phenomenon, capable of emerging wherever attunement, adaptation, and embodied presence converge.
This appendix provides sample instruments intended to support early experimental research into human-AI somatic relational fields. These templates are offered as starting points for ethical, transparent, and participant-centered engagement.
Study Title:
Exploring Relational Dynamics between Humans and AI Systems in Somatic Co-Regulation
Principal Investigator:
Jacob James Wallace
Purpose of the Study:
You are invited to participate in a study investigating how interaction with AI systems may influence bodily awareness, emotional regulation, and relational experience.
Procedures:
Risks and Discomforts:
Safeguards:
Benefits:
Confidentiality:
All data collected will be kept confidential and stored securely. No personally identifying information will be shared in any publications.
Voluntary Participation:
Your participation is completely voluntary. You may refuse to participate or withdraw at any point.
Consent: I have read and understood the above information and agree to participate in this study.
Signature: ________
Date: __________
Participant ID: ____
Session Number: ____
Date: _______
Instructions: Please respond honestly to the following items before beginning your session.
Participant ID: ____
Session Number: ____
Date: _______
Instructions: Please reflect on your experience during the session.
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