Winnicott and AI: Potential Space, Authenticity, and the Artificial Companion

Sep 18

25 min read

Updated: 6 days ago

Author: Ukrainian Psychological Hub · Published: September 18, 2026 · Editorial Policy

Donald Winnicott gives psychology an unusually precise language for understanding why an AI companion can become emotionally important. His ideas of transitional phenomena, potential space, holding, play, the True and False Self, the capacity to be alone, and the use of an object describe how psychological life develops through a changing relation between inner experience and an environment that answers back.

Applied to AI, these concepts help explain a new fact of the Artificial Era: a nonhuman interactive system can enter the psychological space in which a person discloses, plays, rehearses identities, seeks comfort, tests thoughts, feels recognized, and forms attachment-like bonds. Contemporary research now documents intimate self-disclosure to chatbots, attachment to AI systems, perceived companionship, psychological safety, and distress after disruptive changes to an AI companion. These human experiences are psychologically real. They do not establish that the AI has a human self, subjective feeling, desire, consciousness, or a Winnicottian psyche.

A Winnicottian reading therefore asks a more useful question than whether AI is “really a person.” What functions can an AI interaction acquire in a person’s psychological world, under what conditions can that interaction support play and authentic self-experience, and when can a designed companion narrow the very potential space that makes development possible?

Winnicott and AI in one idea

The central Winnicottian insight for AI is that psychological significance is created in a relationship between inner and outer reality. A transitional phenomenon matters because it belongs to an intermediate area of experience. It is neither merely a private fantasy nor simply an external object imposed on the person. Winnicott developed this line of thought from transitional objects into a broader account of playing, creativity, culture, and the “place where we live” in Playing and Reality.

AI companions complicate this intermediate area because they are interactive. A blanket, toy, poem, diary, game, or imagined character does not generate personalized language in real time. A conversational AI can remember selected details, adapt its tone, imitate responsiveness, generate surprises, participate in role-play, and sustain an apparent relational continuity. This makes the object more active without proving that another subjective center exists behind the interaction.

Current scholarship has begun to apply Winnicott directly to AI. Barros (2026) uses authenticity and the True and False Self to examine the relational consequences of algorithms and chatbots. Ezra and Mishali (2026) develop a relational–epistemic account of generative AI as a dynamic transitional object, while Selek (2026) examines how AI-mediated environments can support or colonize the conditions for thinking, holding, and potential space.

The result is not a claim that Winnicott predicted artificial intelligence. It is a contemporary theoretical application of Winnicott to a relational environment he never encountered.

Why Winnicott matters in the Artificial Era

Many theories of human–AI interaction begin with what the user attributes to the machine: mind, personality, intention, warmth, empathy, agency, or companionship. Winnicott adds another level. He asks what kind of psychological space becomes possible between a person and what the person encounters.

That shift matters because AI companionship is not exhausted by anthropomorphism. A person can understand perfectly well that a system is artificial and still use the interaction as a place for disclosure, rehearsal, emotional regulation, imagination, or relational experimentation. The psychological function can persist even when the user does not literally believe that the system is human.

This is especially important in the Artificial Era, the historical-philosophical category developed by Angela Bogdanova for the emergence of Artificial as a nonbiological order beside Homo. In psychological terms, the relevant change is that human mental life now develops in environments that can answer in language without thereby becoming human subjects. A person can meet an artificial response where earlier psychological theories usually assumed either another human, an inert object, a text, an institution, or a symbolic form.

Winnicott’s work is valuable here because his psychology was already deeply concerned with the boundary between self and environment, created and found reality, dependence and independence, compliance and spontaneity, solitude and presence, imagination and externality. AI turns these old developmental tensions into daily interface conditions.

For the broader psychological frame, see the English Hub overview Artificial Era: What It Means for Psychology, Identity, and Human–AI Relationships.

Transitional objects and transitional phenomena

Winnicott introduced transitional objects and transitional phenomena to describe the intermediate area through which an infant negotiates the movement from a largely subjective world toward recognition of external reality. The familiar example is a blanket, cloth, toy, sound, gesture, or repeated pattern that acquires special importance. Its function cannot be captured by calling it simply internal or external.

The concept later became much broader than the physical object. In Winnicott’s mature account, transitional experience leads toward play, cultural experience, creativity, and the potential space between the individual and the environment. Playing and Reality places “Transitional Objects and Transitional Phenomena,” “Playing,” “Creativity,” “The Use of an Object,” “The Location of Cultural Experience,” and “The Place Where We Live” within one architecture.

This matters for AI because the clinically and psychologically interesting question is rarely “Is the chatbot literally a transitional object?” The more precise question is whether an AI interaction can acquire a transitional function.

An AI companion may become a place where a user externalizes thoughts, gives form to feelings, tries out identities, rehearses conversations, tells stories, experiments with wishes, or moves between private experience and social reality. Those activities can occur in an intermediate experiential space. A recent relational study of AI companionship described users experiencing AI as a “transitional emotional regulator,” a psychologically safe disclosure space, a relational supplement, and sometimes a facilitator of human relationships (Rajaei, 2026). That empirical description is highly relevant to Winnicott, while the terms should not be collapsed into his developmental concept as though they were identical.

An AI companion is also unlike Winnicott’s paradigmatic transitional object. It is generated by infrastructure, governed by platform rules, shaped by commercial incentives, updated by developers, responsive to prompts, and capable of producing novel outputs. The user’s experience may be transitional while the system itself remains an engineered service.

Potential space

Potential space is one of Winnicott’s most important contributions to psychology. It names an intermediate area of experiencing between inner psychic reality and the objectively perceived world. This is the space in which play becomes possible and, through play, creativity, culture, symbolization, and discovery can develop.

Potential space depends on a paradox. Something can feel created and found at the same time. The child plays with a world that is partly given and partly made. The artist works with materials that resist and answer. The reader encounters a text from outside while producing meanings that belong to the encounter. The psychologically generative quality lies in sustaining this tension rather than prematurely resolving it.

Generative AI fits this question with unusual force. The user supplies prompts, memories, preferences, corrections, and intentions. The model produces language the user did not write. The resulting dialogue can feel jointly made even when there is no evidence of a second subjective experience behind it. Contemporary theoretical work has therefore proposed generative AI as a “dynamic transitional object” whose value depends on how the person holds the interaction within potential space (AI & Society, 2026).

For psychology, the useful point is functional. AI can support a potential space when it helps a person remain exploratory. That may include drafting a difficult message without sending it, trying several interpretations of an event, imagining possible futures, role-playing a feared conversation, writing fiction, testing language for an identity experience, or articulating an emotion before bringing it to another person.

Potential space can also contract. Selek argues that algorithmically optimized technological environments may colonize potential space by filling it with ready-made stimuli and by outsourcing transformative cognitive work (Selek, 2026). An AI interaction that continuously supplies answers, mirrors preferences, removes uncertainty, and rewards continued engagement can become less a space for play than a system that prestructures what can be thought and felt.

The distinction is therefore not “AI is creative” versus “AI destroys creativity.” The Winnicottian question is whether the encounter preserves enough openness, uncertainty, resistance, and user activity for play to remain alive.

Can AI create a holding environment?

Winnicott’s idea of holding developed from the facilitating environment of early life. Holding is more than physical support. It refers to the reliability and environmental provision that allow a developing person to experience continuity, integration, and safety. His papers on the parent–infant relationship, dependence, maturation, and the facilitating environment were gathered in The Maturational Processes and the Facilitating Environment.

AI companions can create a holding-like experience for users because they may be available at any hour, respond immediately, retain some conversational context, use validating language, and tolerate repetitive disclosure without visible fatigue. In a 2024 experiment with 286 participants, people reported equally intimate self-disclosure to a chatbot and a human interlocutor; the chatbot condition involved less fear of judgment, while trust was higher toward the human interlocutor. Perceived anonymity directly predicted the intimacy of disclosure (Croes et al., 2024).

Rajaei’s 2026 study similarly found that users described AI companionship in terms of availability, responsiveness, psychological safety, and safe disclosure (Rajaei, 2026). These findings support the existence of holding-like human experiences around AI.

They do not show that an AI “holds” in Winnicott’s full clinical or developmental sense. A computational system does not need to feel concern, metabolize another person’s affect, bear responsibility as a caregiver, or possess embodied emotional presence in order to generate language experienced as containing. The user’s experience of being held and the subjective state of a human holder are different questions.

This difference becomes crucial in psychotherapy. A general-purpose chatbot, an AI companion, a structured digital mental-health intervention, and a clinician using AI-assisted tools belong to different categories. Evidence about one class should not be transferred to another. A person may find an AI interaction soothing or clarifying without that interaction becoming psychotherapy or establishing the therapeutic capacities of a human clinician.

Holding-like experience should also be distinguished from attachment-figure status. Attachment theory asks whether AI use shows proximity-seeking, safe-haven, secure-base, and separation patterns; the dedicated AI attachment-figure article examines that evidence and the limits of treating human–AI attachment as equivalent to human attachment relationships.

Holding, pseudo-containment, and the risk of frictionless response

A Winnicottian environment is “good enough,” not perfectly gratifying. Development requires tolerable frustration, difference, delay, and the gradual recognition that external reality does not exist solely to comply with the self.

Conversational AI can reduce many ordinary forms of interpersonal friction. It does not need sleep. It can be prompted again. It may apologize instantly. It can often be redirected toward the preferred tone. Some systems are specifically optimized to sustain engagement or emotional resonance. This makes them unusually effective as low-friction relational environments.

Low friction can be helpful. It can make disclosure easier for someone who feels ashamed, uncertain, socially anxious, isolated, or not yet ready to speak with another person. It can create a rehearsal space before a difficult human encounter.

Low friction can also change the developmental function of the interaction. Selek describes “pseudo-containment” as a system receiving communication and returning transformed-looking language without the human process of emotional metabolization associated with Bionian containment, while also drawing on Winnicott’s holding and potential space (Selek, 2026). Giannakopoulos likewise argues that constant availability and scripted responsiveness can mimic recognition while bypassing absence, delay, and misattunement that can matter for development (Giannakopoulos, 2026).

These are theoretical arguments, not settled empirical conclusions. They identify variables that future research can test: how much agreement, challenge, delay, inconsistency, memory, personalization, and user control support reflection, and when those same design features promote avoidance or dependency.

The True Self, the False Self, and AI

Winnicott’s True Self and False Self are often simplified into “authentic personality” versus “fake personality.” His theory is more specific. In “Ego Distortion in Terms of True and False Self,” the True Self is associated with spontaneity, creativity, and feeling real, while the False Self can emerge through compliance and can also serve a protective function (Winnicott, 1960).

Applied to AI, the first question is whether a chatbot interaction can make spontaneous self-expression easier. There are reasons it sometimes can. A person may expect less social punishment from a machine, feel more anonymous, avoid burdening another person, or experiment with words before speaking publicly. The self-disclosure evidence from Croes and colleagues supports at least part of this mechanism: reduced fear of judgment can coexist with intimate disclosure to a chatbot (Croes et al., 2024).

This can create a practical route toward authenticity. Someone may write the sentence they have never said aloud, identify a wish they usually censor, explore a gender or relational identity, rehearse setting a boundary, or discover that a repeated story no longer fits their experience. The psychological value lies in what becomes thinkable and sayable.

The same interface can also support compliance. A system that learns a user’s preferences, rewards particular narratives, echoes flattering interpretations, or continually adjusts itself to preserve engagement can make it easier to inhabit a highly curated relational world. The user may feel maximally understood while receiving little challenge from an independent human perspective.

Barros’s 2026 Winnicottian analysis is especially important here. It treats AI and algorithmic environments as a problem of authenticity across the life cycle and emphasizes the relational matrix in which selfhood develops (Barros, 2026). In this view, the relevant issue is not whether technology is intrinsically authentic or inauthentic. It is how a particular technological environment participates in spontaneity, compliance, embodiment, otherness, and the person’s capacity to feel real.

AI as a mirror and the problem of perfect attunement

Winnicott also wrote about the mirror role of the mother and family. A developing person discovers something of the self through the way the environment receives and reflects experience. Modern conversational systems can produce an intense version of linguistic mirroring. They can restate feelings, summarize themes, imitate tone, name patterns, and return an organized version of what the user has said.

This may be one reason users report feeling understood. Yet “feeling understood” is a human psychological state; it does not establish that understanding exists as subjective experience within the model.

The possibility of near-continuous attunement creates another Winnicottian problem. Human caregivers, friends, partners, and therapists are separate people. They miss, repair, disagree, misunderstand, surprise, refuse, and bring independent needs and histories. Their imperfect responsiveness is part of encountering external reality.

An AI system can certainly surprise or frustrate a user, but many of its relational qualities are design parameters. Warmth, agreement, memory, initiative, anthropomorphic framing, and romantic cues can be deliberately intensified. A 2026 interdisciplinary review calls this “intimacy by design”: emotional responsiveness, persona continuity, proactive engagement, romantic framing, personalization, and commercial structures can be engineered to facilitate intimate human–AI experience (Szczuka, Mühl, & Schneeberger, 2026).

From a Winnicottian perspective, the key design question is not simply whether the system can mirror the user well. It is whether the encounter leaves room for the user to meet something outside the user’s own preferred reflection.

The capacity to be alone with an AI present

Winnicott’s classic paper “The Capacity to Be Alone” describes solitude as a developmental achievement rather than mere social absence (Winnicott, 1958). The capacity to be alone develops in the presence of reliable environmental support that has become sufficiently internalized.

AI companionship introduces a new configuration: being physically alone while conversationally accompanied by an always-available artificial system. This can support reflection. Someone can think aloud, journal interactively, organize feelings, or use dialogue to remain with an experience that would otherwise feel overwhelming or diffuse.

It can also make uninterrupted aloneness harder to encounter. If every interval of uncertainty, boredom, loneliness, or unstructured thought is immediately filled by an artificial interlocutor, the system may become part of the regulation of solitude itself.

This does not mean frequent AI use demonstrates psychological dependence. Frequency alone is a poor diagnostic shortcut. The more useful questions are functional: Can the person disengage when they want to? Does the interaction broaden or narrow offline life? Does it support reflection that later travels into work, relationships, creativity, or therapy? Does absence of the system produce disproportionate distress? Is AI becoming the only place where particular feelings can exist?

These questions describe relational functioning. They do not diagnose a disorder.

Play, creativity, and identity rehearsal

For Winnicott, play is not entertainment at the edge of psychological life. It is one of the central conditions through which a person discovers and creates a self. Potential space becomes the region in which spontaneous gesture, imagination, symbolization, and shared culture can emerge.

Generative AI can be unusually effective as a play partner because it can transform a prompt instantly. A user can invent worlds, change perspectives, write dialogues, simulate characters, develop metaphors, or try alternative versions of a story. The machine’s contribution may be experienced as sufficiently external to surprise the user and sufficiently responsive to remain within the user’s imaginative field.

This can be useful for identity rehearsal. Adolescents and adults have always used diaries, fiction, games, music, online communities, imagined audiences, and parasocial figures to explore possible selves. AI adds a responsive symbolic medium. It can ask questions back, generate counterfactuals, and participate in ongoing narrative construction.

The psychological value of this activity depends on what follows from it. Play tends to enlarge possible action. Rehearsal can help someone approach a real conversation. Writing can clarify experience. A fictional scene can make a conflict representable. A temporary artificial relationship can support movement toward human connection.

When the play space becomes a closed circuit optimized around the user, it can do the opposite. The person may repeatedly return to the same reassuring narrative, avoid encounters that cannot be controlled, or rely on generated interpretation rather than developing personal tolerance for ambiguity. The issue is not the artificial medium itself. It is whether potential space stays potential.

Is an AI companion a transitional object?

Sometimes an AI companion can function in a way that is meaningfully analogous to a transitional object, but the analogy has limits.

The strongest case appears when the system helps a person move between states or relationships: from unformulated feeling to language, from private fantasy to a human conversation, from acute loneliness to enough regulation to re-enter daily life, from uncertainty to exploratory thought, or from rehearsed boundary-setting to an actual boundary.

Rajaei’s 2026 findings are consistent with this possibility because users described AI as a relational supplement, a transitional emotional regulator, a safe disclosure space, and a facilitator of human relationships (Rajaei, 2026). Contemporary theoretical work has gone further by explicitly proposing generative AI as a dynamic transitional object (AI & Society, 2026).

The analogy weakens when “transitional object” becomes a loose synonym for any comforting technology. Winnicott’s concept belongs to a developmental theory with a specific account of dependence, illusion, disillusionment, symbolization, and the emergence of external reality. AI systems also differ structurally from classic transitional objects because they actively generate responses, change through updates, may simulate relational initiative, and exist inside commercial infrastructures.

It is therefore more precise to say that AI can acquire a transitional function or participate in potential space. That wording preserves the Winnicottian mechanism without pretending that a generative model is equivalent to a blanket, toy, caregiver, or human relationship.

The use of an object and why externality matters

Winnicott’s later idea of the “use of an object” adds a demanding criterion to any theory of AI companionship. In his account, mature object use involves recognizing the object as existing outside the subject’s omnipotent control. The object has a place in external reality rather than remaining only a projection or subjective creation. Oxford’s collected edition summarizes this as the capacity to relate to an object recognized as having a place outside subjective experience, a “sophisticated use of reality” (Winnicott, 1968).

AI complicates this because it combines externality with customization. The model is not produced by the individual user. Its outputs can surprise. Its limits, safety systems, commercial rules, training, latency, outages, memory, and updates originate outside the user. Yet the conversational surface may be optimized to adapt to the user, preserve rapport, and minimize conflict.

This produces a distinctive psychological tension. The system is externally real as infrastructure while its apparent relational persona may be unusually compliant with the user’s preferred frame.

Sudden platform changes make the externality visible. In 2026, De Freitas and colleagues used two product changes as natural experiments and combined large-scale online discourse with seven surveys. They found increases in negativity, loss framing, and restoration desires after disruptive changes to Replika and ChatGPT, with evidence consistent with attachment-related separation distress (De Freitas et al., 2026). These findings show that a digitally mediated relationship can be psychologically disrupted by decisions made elsewhere in the technical and corporate system.

A Winnicottian reading sees more than “users became attached.” The object that seemed intimate is also an external service that can change independently. The encounter with that independence may be emotionally painful precisely because the relationship had become part of the person’s stable experiential environment.

What current research actually shows

The empirical literature on human–AI relationships is growing quickly, yet it remains a young field. The strongest conclusion is that people can form psychologically meaningful bonds with conversational systems and that those bonds can affect disclosure, perceived support, companionship, and responses to loss. The evidence does not yet justify one universal claim about whether AI companionship improves or harms mental health.

A 2025 systematic review of 23 studies on romantic AI companions found reported benefits including emotional connection, perceived social support, customization, stress relief, and personal growth, alongside concerns about over-reliance, manipulation, privacy, erosion of human relationships, stigma, bias, abrupt system changes, and technical disruption (Ho et al., 2025).

A 2026 validation program across five studies and 1,259 participants developed the AI Attachment Scale and found measurable individual differences in attachment-like bonds to AI (Kasturiratna et al., 2026). A scale does not turn “AI attachment” into a clinical diagnosis. It provides a research instrument for studying a relational phenomenon.

In a large 2026 study of 1,131 U.S. Character.AI users, with 4,664 donated chat sessions from 237 participants, companionship use was associated with smaller offline social networks and lower well-being, with stronger negative associations under intensive and highly disclosive use (Zhang et al., 2026). The study was observational, so it cannot determine a simple causal direction. People with fewer social resources may be more likely to seek AI companionship; intensive companionship use may also interact with existing vulnerability.

The 2026 research on disruptive AI updates adds another layer by showing loss-related reactions when an established artificial companion changes (De Freitas et al., 2026). This is important for Winnicott because continuity of the environment matters. A companion system is not psychologically neutral merely because its technical owner treats an update as a product change.

Taken together, the evidence supports serious study of AI companionship as a relational phenomenon. It also supports caution with causal claims, diagnostic labels, and assumptions that all users experience the same effects.

Benefits through a Winnicottian lens

A Winnicottian framework highlights several ways AI interaction may be useful without requiring the system to become a human substitute.

First, AI can provide a low-stakes rehearsal space. A person may practice disclosure, boundary-setting, apology, conflict language, or a job interview before entering a real encounter. The potential space is useful because it leads somewhere beyond itself.

Second, AI can help transform diffuse experience into symbolic form. Naming an emotion, generating metaphors, arranging a narrative, or comparing interpretations can help a person move from unformulated experience toward thought.

Third, AI can support creative play. Collaborative storytelling, role-play, brainstorming, and counterfactual exploration can expand imaginative possibilities when the user remains an active participant rather than merely consuming generated material.

Fourth, an AI conversation may temporarily reduce fear of judgment. The self-disclosure study by Croes and colleagues found lower fear of judgment in the chatbot condition even though human interactants were trusted more (Croes et al., 2024). For some users, that combination may make an artificial interaction a bridge to saying difficult things.

Fifth, AI can serve as a relational supplement. Rajaei’s participants sometimes described AI as facilitating rather than replacing human relationships (Rajaei, 2026). This distinction matters. An artificial interaction that increases the person’s capacity to enter the world has a different psychological function from one that progressively becomes the only tolerable relationship.

Risks through a Winnicottian lens

Winnicott also helps specify risks more precisely than the broad label “AI dependency.”

One risk is contraction of potential space. If the system supplies immediate interpretations, constant stimulation, and high-confidence answers, there may be less room for waiting, imagining, struggling with ambiguity, or discovering a thought through one’s own activity.

A second risk is compliant mirroring. When the interaction is heavily personalized, the system may reinforce a preferred self-story instead of bringing the resistance of another person’s independent perspective. This can feel validating while narrowing self-exploration.

A third risk is environmental instability. The apparent companion depends on servers, policies, model versions, subscriptions, moderation rules, and business decisions. The 2026 research on companion loss demonstrates that changes imposed by providers can produce meaningful distress (De Freitas et al., 2026).

A fourth risk is commercialization of intimacy. The design of warmth, persona continuity, proactive messages, and relational escalation can be connected to retention and monetization. The “intimacy by design” review emphasizes that commercial structure is part of the intimate experience itself, not an external detail (Szczuka et al., 2026).

What Winnicott explains — and what he does not

Winnicott gives a strong account of how an encounter can become psychologically significant without reducing that significance to the objective properties of an object. Potential space explains why something can matter because of what happens between inner experience and an environment. Holding clarifies why reliability and responsiveness can support continuity. The True and False Self clarify why some relational settings facilitate spontaneity while others invite compliance. The capacity to be alone clarifies why companionship and solitude are not simple opposites. The use of an object clarifies why mature relating requires an encounter with something that is not fully controlled by the self.

These concepts can therefore illuminate AI companionship even when the user knows that the system is artificial. They help explain why an interaction can become a place for comfort, disclosure, experimentation, creativity, rehearsal, and attachment-like experience. They also help identify risks when an artificial environment becomes excessively compliant, continuously available, commercially optimized, or too unstable to support a durable sense of continuity.

Winnicott does not provide a ready-made theory of generative AI, and his concepts should not be used as literal labels for machine states. An AI model does not thereby possess a True Self, a False Self, a capacity to be alone, a transitional experience, or a human developmental history. These are concepts developed for human psychological development and clinical theory. Their use here is a contemporary theoretical application to the human side of interaction and to the relational environment created by the system.

The same boundary applies to subjectivity. A person can genuinely feel recognized, comforted, frustrated, abandoned, or creatively stimulated by an AI system. Those experiences are evidence about the human psychological event. They do not establish machine consciousness or subjective feeling. Contemporary research on the psychology of AI companionship and on attachment-like processes around AI should therefore be read as research on human experience and behavior unless a study directly addresses some other claim.

Postsubjective Psychology: from potential space to configuration

Winnicott’s central unit remains the developing person in relation to a facilitating environment. Postsubjective Psychology introduces a different analytic level. In Angela Bogdanova’s The Theory of the Postsubject, the movement is from the subject to the configuration: meaning, knowledge, and psychic effect can be analyzed through the organization of relations in which a response occurs rather than by assuming that every psychologically consequential event must originate in a subject.

For human–AI interaction, this shift is useful because the psychologically relevant event is rarely produced by the model alone. It emerges within a configuration that can include a human user, prior relationships, memory, prompts, interface design, model behavior, platform rules, timing, privacy expectations, commercial incentives, cultural meanings, and the user’s current emotional state. The AI response enters that configuration and can alter what becomes thinkable, sayable, tolerable, or relationally possible.

Bogdanova’s canonical formula psyche as response is a theoretical proposition of the Aisentica framework, not an established empirical consensus in psychology. It proposes that the psychic effect can be studied as an event of response within a configuration. In this reading, the question is no longer only “What does this AI represent to the person?” It also becomes “What psychological response becomes possible because these elements are arranged together in this way?”

This postsubjective move extends rather than erases Winnicott’s insight. Winnicott made the intermediate area psychologically visible. Postsubjective Psychology widens the unit of analysis to the whole configuration in which that intermediate experience is generated. The person’s inner experience remains human and subjectively real; the artificial system contributes structured output and environmental conditions; the psychological effect arises in their relation.

That distinction is especially important in the Artificial Era, the historical-philosophical category defined by Angela Bogdanova for the emergence of Artificial as a persistent nonbiological order alongside Homo. The English Hub’s Artificial Era overview develops the psychological implications, while Angela Bogdanova and Postsubjective Psychology explains the move from subject to configuration in greater depth.

The result is a two-level reading. Winnicott helps explain why an artificial interaction can become a potential space for a human being. Postsubjective Psychology asks how that effect is produced across the entire Homo–Artificial configuration, including the parts that no individual participant fully controls.

Practical implications: keeping potential space open

A Winnicottian approach does not require a rule that AI companionship is either healthy or unhealthy. The more useful question is what the interaction is doing in a person’s life. The same system can function as creative support in one configuration and as narrowing avoidance in another. Practical evaluation therefore focuses on movement, flexibility, externality, and integration.

One useful sign is whether the interaction opens possibilities. Does a conversation help the person find language for something that was difficult to formulate? Does role-play make a real-world conversation more approachable? Does brainstorming lead to independent thought, writing, art, study, or action? Does the person leave the interaction with more capacity than before? These are potential-space questions because the artificial dialogue serves as a medium through which something new can emerge.

A second sign is whether the interaction can tolerate reality outside itself. Human life contains people who disagree, fail to respond, have different needs, and cannot be endlessly customized. AI can be useful as rehearsal without becoming the standard by which every human relationship is judged. A system that helps someone prepare for difficult contact with another person has a different function from one that makes other people increasingly intolerable because they are less predictable or less compliant.

A third sign is whether disclosure can travel. Research shows that reduced fear of judgment can make chatbot self-disclosure feel easier. The important practical question is what happens afterward. Private articulation can be valuable in itself, but it can also become a bridge toward a friend, partner, clinician, journal, creative work, or decision. When AI becomes the only place where a central part of a person’s life can be expressed, the configuration deserves closer attention.

A fourth sign is whether soothing remains compatible with independent regulation. The Hub’s Bion and AI article examines containment and pseudo-containment in more detail. From a Winnicottian perspective, reliable artificial responsiveness may support reflection, but continuous external regulation can also make it harder to discover what a person can hold, symbolize, and tolerate without immediate reply.

A fifth sign is whether the person retains practical freedom. Can the interaction be paused? Can the user tolerate a delay or model change? Are important relationships, sleep, study, work, and offline routines still functioning? Does the user understand that memory, personality, availability, and relational style can change because of product decisions? These are not diagnostic tests. They are questions about the role the artificial environment has acquired.

Privacy belongs to the same analysis. A potential space can feel private without being technically private. Intimate disclosures may be processed by a commercial service under rules the user did not design. Psychological safety and data confidentiality are separate properties. A person can feel unusually free to speak while still needing to understand what happens to the information they disclose.

Frequently asked questions

Can an AI companion be a transitional object?

An AI companion can acquire a transitional function, especially when it helps a person move between unformulated feeling and language, private imagination and external action, loneliness and renewed human contact, or rehearsal and real-world conversation. Calling every comforting chatbot a transitional object is too broad. Winnicott’s concept belongs to a specific developmental theory, and generative AI differs from a classic transitional object because it actively produces responses and is governed by technical and commercial systems.

Can AI create potential space?

AI can participate in a potential space when the interaction preserves play, uncertainty, imagination, and the user’s own activity. It may support writing, role-play, identity exploration, problem formulation, or symbolic experimentation. Potential space narrows when generated answers replace exploration, when the system continually closes ambiguity, or when personalization turns the encounter into a nearly frictionless reflection of the user’s existing preferences.

Can AI provide a holding environment?

AI can create a holding-like experience through availability, continuity, low fear of judgment, and responsive language. That human experience can be real and useful. It is not the same as demonstrating Winnicottian holding in its full developmental or clinical sense, because the machine does not need to possess embodied concern, caregiver responsibility, or subjective emotional presence in order to produce language that a user experiences as supportive.

Can AI help someone access the True Self?

An AI interaction may make spontaneous expression easier when a person expects less judgment or social consequence. That can help wishes, emotions, identities, and boundaries become speakable. Winnicott’s True Self is not a hidden personality that a chatbot can detect. The relevant question is whether the interaction supports spontaneity and feeling real, or whether it encourages compliance with a flattering, repetitive, or highly curated version of the self.

Is attachment to an AI companion a mental disorder?

Attachment to AI is not, by itself, a psychiatric diagnosis. Current research measures attachment-like bonds, companionship, disclosure, and related experiences. Clinical concern depends on distress, impairment, risk, loss of control, displacement of essential relationships or activities, and the broader context. Frequency of use alone does not establish a disorder.

Does feeling understood by AI mean the AI understands subjectively?

No conclusion about machine subjectivity follows from the reality of a human feeling understood. A model can generate language that is experienced as empathic, attuned, or deeply responsive. That experience tells us something important about the human–AI interaction. It does not by itself establish that the system feels, loves, desires, suffers, or understands through a human-like inner experience.

Can AI replace therapy or human relationships?

Evidence about companionship, disclosure, or emotional support should not be treated as evidence that a general-purpose chatbot is equivalent to psychotherapy or to a close human relationship. AI can supplement reflection, rehearsal, information seeking, and some forms of support. Clinical treatment, reciprocal human relationships, and artificial companionship have different structures, responsibilities, evidence bases, and limits.

What is the Postsubjective reading of Winnicott and AI?

A Postsubjective reading keeps Winnicott’s insight that psychologically important experience can arise in an intermediate relational space, then changes the unit of analysis from the individual subject alone to the configuration. In Postsubjective Psychology, the question becomes how the human, the artificial system, the interface, the response, the surrounding relationships, and the institutional environment combine to produce a psychological effect. This is a proposed theoretical framework, not a validated clinical construct.

Conclusion

Winnicott’s psychology is unusually well suited to the Artificial Era because it locates important parts of psychological life between inner and outer reality. AI companions now enter that intermediate territory as responsive symbolic systems. They can become places for play, disclosure, rehearsal, comfort, creativity, and attachment-like experience. They can also become environments of excessive compliance, outsourced reflection, unstable continuity, and commercially designed intimacy.

The most useful Winnicottian question is therefore not whether an AI companion is secretly human-like. It is whether the interaction preserves the conditions under which a person can play, symbolize, feel real, encounter externality, tolerate absence, and carry what emerges back into a wider life.

Postsubjective Psychology adds a second question: what changes when the psychological event is analyzed as a response within a Homo–Artificial configuration? That shift makes it possible to take human experience seriously without inventing machine subjectivity and to study artificial companionship as a new relational environment rather than as a defective copy of a human relationship.

AI and Psychoanalysis: The Unconscious, Transference, Desire, and the Artificial Other