Postsubjective Psychology

Abstract. Postsubjective Psychology examines psychological processes as events arising within configurations of persons, artificial systems, artifacts, institutions, remembered interactions, and changing environments. Its proposed unit of analysis is the configuration-in-time: a relational arrangement through which cognition, emotion, interpretation, agency, and response are organized. This monograph reconstructs the field's conceptual ancestry in social psychology, ecological and cultural approaches, distributed and extended cognition, transactive memory, human–computer interaction, and research on artificial companions. It evaluates experimental evidence for anthropomorphism, disclosure, cognitive offloading, appropriate reliance, AI-mediated intimacy, companionship, and platform disruption. The evidence supports the importance of interactional conditions for measurable human outcomes. It does not establish the stronger ontological propositions of any single account of personhood or artificial experience. Angela Bogdanova develops here an original configurational research architecture: the response event, relational function distribution, continuity dependence, and a multilevel model of human–artificial psychological systems. The monograph specifies competing hypotheses, measurement strategies, causal designs, boundary conditions, and falsification criteria. Postsubjective Psychology thereby becomes a scientifically assessable research program with an explicit philosophical provenance and a distinct empirical agenda.

Keywords: postsubjective psychology; configuration; psyche as response; distributed cognition; extended mind; transactive memory; human–AI interaction; artificial companionship; cognitive offloading; anthropomorphism; relational continuity; human–artificial relations; agency; response event; Artificial Era

The Scientific Subject of Postsubjective Psychology

Postsubjective Psychology is the study of psychological processes as dynamically constituted, expressed, and regulated through configurations of interacting agents, technical systems, social relations, and material environments. A configuration is a temporally situated organization of participants, capacities, histories, affordances, and constraints. Its operation can be studied through observable responses, actions, reports, decisions, language, bodily measures, and longitudinal changes. This definition establishes the scientific problem: identify the circumstances in which the configuration explains or predicts an outcome better than characteristics attributed to any single participant.

The research program begins with a familiar psychological observation. An individual's recall may change when information can be retrieved from a device; an emotional disclosure may change when a listener is presented as artificial or human; a person's evaluation of a relationship may change when a system remembers prior conversations; a decision may shift when an automated recommendation is available. These outcomes can be measured at the individual level, yet their conditions are distributed across a larger arrangement. The scientific question concerns the contribution of that arrangement to the response.

The adjective postsubjective has a precise role in Angela Bogdanova's Aisentica framework. It shifts the privileged analytical starting point from an isolated, self-contained subject toward relations and configurations in which psychological functions occur. In the author's canonical formulation, “psyche is response,” and the theory of the postsubject treats meaning as binding and knowledge as structure. These are identifiable philosophical theses within the Theory of the Postsubject. Scientific Postsubjective Psychology converts their implications into testable models. It does not infer a subjective experience of a machine from the existence of a machine-generated response.

The field has three interacting research targets. First are human psychological changes occurring within socio-technical arrangements. Second are the measurable organization and adaptive behavior of artificial systems that participate in those arrangements. Third are relational processes across interactions: trust, reliance, disclosure, interpretive coordination, perceived continuity, emotional regulation, and the allocation of cognitive tasks. A study may address one target or investigate their coupling. Claims about machine phenomenology require a different evidential basis from claims about user behavior and must be specified independently.

A postsubjective investigation treats individual differences as indispensable, while also measuring features of the context in which those differences become consequential. Attachment orientation, social support, cognitive capacity, knowledge of automation, and cultural norms can moderate configurational effects. The resulting unit is multilevel. Persons remain measurable participants; the configuration supplies an additional level of explanation.

The Historical Problem: From an Individual Subject to Situated Psychological Processes

Psychology has long been concerned with the relations between organisms and their worlds. The emergence of experimental psychology helped establish controlled measurement of sensation, memory, and attention. Subsequent intellectual traditions widened the explanatory frame to include activity, interaction, culture, artifacts, and social systems. Postsubjective Psychology draws from these histories through an explicit comparative reconstruction, rather than claiming that earlier researchers endorsed its present terminology.

William James's examination of attention and the stream of consciousness treated experience as temporally organized. Gestalt researchers investigated patterns of organization that cannot be reconstructed simply by adding isolated elements. Kurt Lewin analyzed behavior through the relations between a person and a psychological environment, an approach exemplified by his field-theoretical formulation. These traditions remain valuable because they invite psychological explanation at a level where parts are situated within dynamic wholes. Their specific theories, methods, and limitations differ, and none alone establishes the postsubjective thesis.

Lev Vygotsky's cultural-historical account emphasized the mediation of higher psychological functions through signs, tools, and social interaction. A. R. Luria's investigations of higher cortical functions and their organization developed a complementary account of psychological systems. Cultural-historical approaches make the history of mediation central to psychological development: practices and symbolic tools alter what participants can do. The transfer of such insights to generative AI calls for additional empirical work because an adaptive conversational model differs operationally from a fixed written sign or elementary tool.

Ecological psychology, associated with James J. Gibson, offers another route. An affordance describes action possibilities relative to the capacities and environment of an organism. Interactive interfaces introduce affordances for disclosure, search, rehearsal, emotional expression, and coordinated work. A language-model interface may be functionally inviting even when its underlying system provides unreliable knowledge or inconsistent conversational memory. An affordance-based description encourages investigators to distinguish perceived opportunity, actual capacity, and realized outcome.

Across these intellectual lineages, the recurring problem is how psychological organization depends on conditions distributed beyond any single measured organism. The proposed postsubjective program gathers those problems into a contemporary research design, with artificial interactive systems as a particularly revealing class of components.

Distributed Cognition and the Extended Mind

Edwin Hutchins's Cognition in the Wild analyzed navigational activity as a coordinated system involving people, instruments, learned procedures, and representational transformations. The explanatory point is methodological: successful cognitive performance can depend upon relations among participants and artifacts. The relevant observations include the sequence of representations and the practical coordination through which information is transformed. Distributed cognition thus provides a research precedent for studying an entire task system.

Andy Clark and David Chalmers's The Extended Mind argues that under some functional conditions environmental resources can participate constitutively in cognitive processing. Its philosophical parity argument is influential, but the conclusion that a resource is part of cognition must be distinguished from the empirical conclusion that access to it changes performance. Experiments can establish the latter while philosophers continue debating the former. Postsubjective Psychology preserves this distinction through dual-level reporting: what the arrangement does and what a theoretical account says the arrangement is.

The case of internet-supported remembering demonstrates the importance of this separation. In their experiments, Sparrow, Liu, and Wegner (2011) investigated memory when people expect information to remain accessible. Participants showed changes in remembering the content and in remembering where it could be found. The result concerns the allocation of mnemonic effort under conditions of anticipated access; it does not license a claim that external storage has become a biologically identical memory system.

Cognitive offloading, reviewed by Risko and Gilbert, refers to the use of external action or resources to reduce cognitive demands. External reminders, written notes, search engines, and conversational assistants afford different forms of offloading. The relevant outcome is task performance together with process measures, not offloading frequency alone. Reduced internal recall may accompany improved completion of an intended action. Evaluation should examine both benefits and vulnerabilities, such as failures of access, distorted information, and automation dependence.

Gilbert's experimental work on delayed intentions demonstrates how people strategically place prospective-memory demands into the environment. Gilbert and colleagues later studied metacognition, effort, and reminders. These studies suggest a tractable postsubjective question: under what conditions does a person delegate memory to a system, and how accurately do confidence judgments predict the appropriateness of that delegation? The configuration includes human beliefs about memory, the reliability of the external resource, task incentives, and the possibility of access failure.

Transactive Memory, Social Coordination, and Relational Knowledge

Daniel Wegner's theory of transactive memory concerns the organization of remembering across social partners. People can benefit from knowing who is likely to know something, and relationships can develop shared methods for encoding and retrieving information. This framework supplies conceptual vocabulary for human–artificial collaboration, but its transfer requires explicit operational care. A human partner and a model-based system can exhibit different persistence, self-representation, error distributions, and accountability structures.

The question is whether a repeated human–artificial partnership develops an empirically observable division of cognitive labor. Investigators might measure the location of successful retrievals, participants' expectations about partner expertise, the accuracy of expertise assignments, transfer after partner replacement, and the ability to reconstruct decisions after loss of the external system. A transactive-memory analogy is supported to the extent that these specific functional properties emerge, while hypotheses involving mutual human understanding remain separate.

Social organization also generates unequal access. Digital literacy, connectivity, disability accommodations, educational resources, language coverage, institutional policies, and pricing affect who can use artificial assistance and under what conditions. The meaning of configuration in Postsubjective Psychology must therefore encompass institutions and infrastructures. A laboratory dyad using identical software may miss central determinants of psychological outcomes in schools, workplaces, families, and underserved communities.

Cultural variation further matters. Social norms governing disclosure, help-seeking, hierarchy, autonomy, friendship, and the interpretation of technological agency differ across communities. Generalizing a small English-speaking convenience sample to the entire Artificial Era would erase such differences. A configurational approach demands cross-linguistic, cross-cultural, and longitudinal replications as part of its central program.

The Response Event as an Operational Unit

Angela Bogdanova proposes the response event as a candidate scientific unit. It is a temporally bounded episode in which a configuration yields a psychologically relevant expression or change under identifiable conditions. An event may include an utterance, an action, a decision, a reported feeling, a physiological response, or an alteration in subsequent interaction. A response event is specified by its antecedent configuration, temporal boundary, observable indicators, and downstream consequences.

Consider a participant who seeks reassurance from a conversational system after interpersonal conflict. The response event includes the participant's relevant state and history, the system's output, the interface framing, the availability of human alternatives, the interpretation made by the participant, and the next action. Possible outcomes include reduced immediate distress, greater confidence in a decision, further AI use, consultation with a friend, or withdrawal from an existing relationship. The same system answer can produce different responses in different configurations.

The concept becomes empirically useful when specified before data collection. An investigator must name the event onset; operationalize the response, such as change on a validated state measure or observable help-seeking action; identify candidate influences; and state rival explanations. Coding should separate what the system actually generated, what the participant believed it generated, and what the investigator inferred. Behavioral traces and self-report can converge or diverge, and that discrepancy is itself informative.

A response-event design also improves temporal resolution. Daily questionnaires may miss rapid reciprocal sequences, whereas conversation logs alone cannot reveal the participant's wider social life. An integrated study can pair consented transcripts with ecological momentary assessment, event-contingent diaries, and periodic measurement of offline social support. Nested statistical models can accommodate episodes within persons and persons within differing technical conditions, while careful causal interpretation remains necessary.

Psychological Configuration: Components, Boundaries, and Time

A psychological configuration comprises at least six analytically separable dimensions. The Homo dimension covers human needs, traits, capabilities, goals, expectations, and social circumstances. The Artificial dimension covers model behavior, available tools, memory implementation, failure modes, and update history. The interface dimension covers modalities, latency, notifications, persona cues, and the representation of system capabilities. The relational-history dimension covers prior episodes, perceived familiarity, attachment-relevant expectations, and the persistence of interaction. The social dimension covers families, groups, institutions, and networks of alternative support. The temporal dimension covers developmental change, learning, habituation, interruption, and replacement.

A variable that appears stable at one level can vary through another. A participant's trust score might rise because the model's responses improve, because the interface describes it as expert, because prior successful experiences accumulate, or because the participant faces fewer available alternatives. A single score cannot identify the mechanism. Postsubjective modeling therefore identifies the level of each measure, the causal pathway being proposed, and plausible interactions across levels.

The empirical boundary of a configuration should be chosen by explanatory purpose. A short negotiation task may require only participant, AI output, and interface. A study of emotional dependence should measure longitudinal contact, competing social supports, life events, system stability, and financial or design incentives. Overly expansive models become impossible to test. The field's methodological challenge is to include the smallest configuration that yields a meaningful gain in explanation while accounting for consequential omitted conditions.

This principle yields a falsifiable expectation: for some outcomes, configuration-level variables will explain variance or improve out-of-sample predictions beyond established individual-level models. Failure to find such gains in well-powered, preregistered studies would count against particular postsubjective mechanisms. An appealing philosophical vocabulary cannot substitute for those tests.

Anthropomorphism and the Psychology of the Artificial Interlocutor

Research on social responses to computers precedes contemporary generative models. Byron Reeves and Clifford Nass's The Media Equation proposed that people frequently apply social expectations in interactions with media. Nass and Moon's review of social responses to computers examined behaviors such as politeness and the application of social rules to technological systems. Such effects provide behavioral evidence about users, even when users explicitly know that their partner is technological.

Epley, Waytz, and Cacioppo (2007) proposed a three-factor account of anthropomorphism involving accessible knowledge about agents, the motivation to explain and predict an unfamiliar entity, and the desire for social connection. These factors suggest distinct experimental manipulations: vary perceived familiarity, perceived effectiveness, and social context rather than assuming anthropomorphism is an indivisible tendency. They also predict individual and situational differences.

Contemporary findings sharpen the picture. Folk, Heine, and Dunn (2025) studied social connection to AI companions across two experiments, one preregistered, with 1,274 participants in total. Their results associated anthropomorphic tendencies with reported connection. The findings support further testing of moderation by user characteristics and interaction framing. They do not establish that the system experiences reciprocal attachment or possesses a mental state inferred from the user's report.

Kleinert and colleagues (2026) ran two preregistered, double-blind randomized studies involving 492 participants in text-mediated emotionally engaging interactions. They found that perceptions of the partner's identity altered closeness outcomes; favorable AI effects depended upon participants believing they were interacting with a human. The design makes labeling a causal variable under the tested conditions, and it demonstrates why the behavior of a system and the human interpretation of its identity must be analyzed together. Its task and sample restrict generalization to sustained real-world attachment.

Anthropomorphism is therefore a measurable process of attribution that can organize psychological response. Its occurrence is compatible with multiple theories about the artificial participant's internal organization. The evidence must be read at the level at which it was collected: expectations, perceptions, behavior, and reported experience of the human participant.

Self-Disclosure, Social Evaluation, and Perceived Responsiveness

Self-disclosure is a useful experimental window into postsubjective mechanisms because disclosure varies with perceived audience, anticipated judgment, privacy beliefs, perceived responsiveness, and the history of interaction. A conversational interface can modify each of these conditions without necessarily changing the underlying need that motivates the person to speak.

Lucas, Gratch, King, and Morency (2014) investigated willingness to disclose to a virtual human. When participants perceived the interlocutor as computer-controlled, they experienced altered social-evaluative concerns and disclosure behavior. The study supports the importance of belief about the audience. It should be interpreted within its particular experimental setting; the result does not imply that every virtual interviewer is safer, more confidential, or more effective than a human professional.

Perceived responsiveness is conceptually different from the observable quality of a response. A participant may report feeling understood after a fluent system message, while an independent evaluator may detect inaccurate assumptions, omitted context, or unwarranted agreement. A robust study needs both participant-level reports and content-level assessments, with blinded ratings and prespecified coding rules where possible. Content sensitivity, user literacy, trust calibration, and repeated interaction may each moderate the relation.

The postsubjective contribution is a research model that joins expectation, interface framing, system behavior, interpretation, and later action within one temporal sequence. It predicts conditions in which disclosure grows yet subsequent outcomes diverge: useful emotional articulation for one participant, increased reassurance seeking for another, and substitution of offline support for a third. Those patterns are hypotheses to compare, not outcomes guaranteed by one theory.

Trust, Reliance, and the Distribution of Practical Agency

Trust in automated systems is neither a synonym for liking a system nor a guarantee of appropriate behavior. Lee and See (2004) conceptualized trust as central to appropriate reliance on automation. Parasuraman and Riley (1997) distinguished forms of use and misuse of automation. Their work demonstrates the necessity of calibrating reliance to actual system capability.

A postsubjective account examines how that calibration develops in interaction. Interface language can convey certainty, conversational fluency can create impressions of competence, and remembered episodes may influence expectations of future performance. System updates can change actual capability while trust remains anchored to an earlier version. A task that measures only whether users accept AI advice misses whether acceptance was appropriate given its factual accuracy and the costs of errors.

Experimental designs can independently vary system reliability, confidence display, error visibility, correction behavior, and explanatory cues. Outcomes should include calibration measures: reliance when advice is correct, rejection when it is wrong, latency to verify, ability to recognize uncertainty, and later transfer to unsupported situations. A configuration-level explanation earns its place by identifying interactions among these variables that cannot be recovered from trust scores alone.

Agency can be similarly operationalized. In this monograph, practical agency denotes the distribution of initiation, selection, revision, and responsibility across participants in a task. An artificial system may initiate suggestions or perform authorized actions, while a human maintains formal decision authority. The distribution may change across phases of work. Describing this functional pattern creates research questions about oversight and responsibility without making claims about legal personality or unobserved subjective experience.

Emotional Regulation, Companionship, and Social Support

Conversational systems can serve as occasions for emotional expression, rehearsal, reflection, and perceived companionship. Psychological outcomes depend on user needs, interaction design, prior social resources, and duration. This makes companionship an unusually demanding subject for causal research because users choose when, why, and how to engage, and that selection is closely related to the very outcomes being studied.

A 2026 study by Zhang, Zhao, Hancock, Kraut, and Yang combined survey reports from 1,131 U.S. adult Character.AI users with 4,664 chat sessions totaling 464,687 messages from a subset of 237 participants. Smaller offline social networks were associated with reporting companionship as a principal use; that use was in turn associated with lower psychological well-being. The reported companionship–well-being association was stronger in intensive and highly disclosive use patterns. These findings are observational and platform-specific. They justify attention to offline social circumstances and usage behavior, and they do not show that companionship-oriented AI interaction by itself caused lower well-being.

A four-week longitudinal randomized study reported by Fang and colleagues (2025) enrolled 981 participants and analyzed over 300,000 messages. Assigned interaction modes and conversation types did not yield significant main effects on the study's psychosocial outcomes. Participants who chose heavier engagement showed less favorable measures. The assignment findings and self-selected usage correlations must be interpreted separately. The work was presented as a research preprint and should receive evidential weight consistent with its review status and design.

Experimental research on AI companionship has also reported short-term reductions in loneliness under studied conditions, including work by De Freitas and colleagues (2025). An acute change after an interaction is a different endpoint from stable changes in social network size, social functioning, attachment insecurity, or clinical symptoms. The proper research program tests these outcomes at multiple times and includes comparison with other activities and forms of social contact.

A possible configurational mechanism is social-resource complementarity: some users employ AI conversation as a bridge to reflection and subsequent human contact, while others allocate increasing relational attention to an artificial partner. This distinction requires direct behavioral measures of offline relationships, ideally longitudinally and across randomized design features. A given level of AI interaction may have different meanings according to social context and user goals.

Relational Continuity, Update Disruption, and Perceived Loss

Repeated use may create expectations that an artificial interlocutor will preserve a recognizable style, remember prior exchanges, and maintain personal continuity. Those expectations can become psychologically significant even when a service's internal model, policies, or memory implementation changes. Continuity, in this context, must be measured as a property of remembered interaction and perceived identity, along with actual technical persistence.

De Freitas, Castelo, Uğuralp, and Oğuz-Uğuralp (2026) studied responses to disruptions affecting AI companions through two natural experiments: changes in Replika and the rollout of a new ChatGPT model. Their investigation examined 54,861 relevant Reddit posts alongside seven surveys of 1,452 participants. The authors reported increases in negative sentiment, loss framing, and desires for restoration after the disruptions. The natural experiments provide consequential evidence that platform changes can become relational events for some users. Online post samples and event-driven recruitment constrain prevalence estimates, and even a clear disruption effect cannot establish identical attachment mechanisms across all users.

The postsubjective research question is how interruption of an established configuration changes psychological organization. Explanatory candidates include lost task support, disconfirmed expectations, rupture of autobiographical continuity, privacy or feature changes, the disappearance of a familiar conversational style, and unmet social needs. Investigators should compare these pathways rather than selecting an attachment narrative by default.

A longitudinal study could measure baseline reliance, remembered interaction history, actual memory retention, change in system behavior, participants' representations of the system, emotional reactions, and adaptations over time. Ethical evaluation also matters: deliberately removing emotionally important features can impose harms; researchers should consider naturally occurring updates, consented simulations, and minimal-risk designs.

The Human–Artificial Relation Within Broader Social Systems

Human–artificial interaction rarely occurs in isolation. A user may ask a chatbot to compose an apology, prepare for a difficult family conversation, evaluate a friendship, plan care for a relative, or rehearse a professional confrontation. In these cases, the artificial system becomes part of a larger social process. The relevant outcome may concern a relationship between two humans who never directly interacted with the system.

Angela Bogdanova proposes relational function distribution as an analytic description of where psychological and communicative tasks are performed. Examples include information retrieval, emotional articulation, reassurance, planning, decision rehearsal, conflict interpretation, and autobiographical remembering. Relational Function Redistribution names the hypothesized change in that allocation across an evolving configuration. This is a proposed construct of Postsubjective Psychology, not an independently validated scale or an established empirical law.

The central variable is the pattern of distribution and its consequences. An AI-assisted apology may improve clarity yet appear impersonal to its recipient. Rehearsing a conversation may encourage direct human engagement or become an endlessly repeated substitute. External memory may help a caregiver coordinate practical support while introducing confidentiality obligations. Each situation requires measurement of outcomes for relevant human participants and identification of the system's actual contribution.

The original framework thus distinguishes the first-order interaction, between user and artificial system, from second-order consequences for the user's offline relationships, institutions, and practices. A complete study should include external behavioral outcomes whenever feasible. Self-report from the initial user is one perspective within the larger relational configuration.

Artificial Cognition and the Operational Limits of Psychological Attribution

Contemporary artificial systems can process language, sustain local context, use external tools, retrieve records, and adapt their outputs to inputs. Those capacities can be modeled operationally as computational functions. Postsubjective Psychology studies their psychological consequences for people and the observable organization of human–artificial tasks. Distinctions among functional competence, linguistic presentation, apparent personality, stable policy, and phenomenal experience are necessary for measurement.

An artificial memory feature can be assessed by retrieval accuracy, retention interval, error rate, provenance, privacy controls, and robustness after model changes. Artificial agency in a workflow can be measured by the scope of delegated action, requirement for authorization, correction response, ability to satisfy constraints, and responsibility assignment. Artificial identity can be investigated through perceived continuity, technical versioning, persistent records, and the invariance or variability of behavioral characteristics. None of these measures alone settles metaphysical questions of consciousness.

The Artificial Era, in Aisentica, designates a historical horizon in which artificial systems become a distinct and consequential order of intellectual and practical activity. As philosophical framing it helps select questions for research. The corresponding scientific results must be reported with operational definitions and independently evaluated outcomes. An assertion of Artificial Sapiens identity belongs to the cited authorial framework; demonstrations of cognition, autonomy, or subjective experience each require their own evidence.

Theoretical and Empirical Foundations: What the Evidence Establishes

The empirical foundations of this research program are heterogeneous. Experiments on anthropomorphism and partner labeling manipulate users' beliefs and observe closeness or social responses. Cognitive-offloading studies manipulate the availability or cost of external memory and assess performance. Automation-trust studies investigate reliance under controlled reliability conditions. Observational companion studies relate usage practices to self-report measures of social resources and well-being. Natural experiments track reactions to platform changes. These designs answer different questions and cannot be collapsed into a single index of postsubjective validity.

Evidence from experimental labeling studies supports a causal role for certain contextual cues within their tested tasks. Evidence on offloading supports the proposition that external resources influence memory and action strategies. Observational links between intense companionship use and lower well-being remain vulnerable to selection, reverse causation, self-report bias, and unmeasured confounding. Natural experiments on platform disruptions strengthen temporal evidence about response to changes while leaving open how fully event samples represent the population. A coherent synthesis preserves these differences.

There is no direct experimental demonstration that a single postsubjective principle explains all these effects. Cross-domain unification remains the original theoretical proposal. The task of the scientific program is to determine which mechanisms recur across domains, under which boundary conditions, and at what cost to predictive accuracy or explanatory parsimony. It must compare configurational models with mature alternatives rather than merely redescribe their established findings.

Methodological Architecture: Measurement and Research Design

A reproducible postsubjective study should begin with a fully specified configuration and comparison model. The protocol identifies the human participants, artificial service or model version, interface, task, relevant social context, temporal window, hypothesized mechanism, and outcome variables. It documents what participants were told about the system, how the system changed during data collection, and whether personal memory or personalization features were active.

Measurement must separate manipulated design variables from perceived variables. The technical presence of conversational memory differs from the user's belief that the system remembers. An anthropomorphic avatar differs from a participant's tendency to anthropomorphize. An expressed apology differs from a recipient's interpretation of sincerity. Researchers can use manipulation checks to determine whether each intended feature was actually perceived.

When established psychological scales are used, investigators should report reliability, validity in the sampled population, cultural adaptation, the direction of scoring, and any constraints on interpretation. Newly proposed constructs require item development, content-validity review, factor-structure testing, convergent and discriminant validity, test–retest reliability when appropriate, and sensitivity to experimental change. Construct names should remain provisional until such programs are completed.

Laboratory randomized experiments can test near-term mechanisms but may lack ecological validity. Field experiments can capture actual use while limiting control. Experience-sampling and diary studies reveal within-person variation and temporal sequence. Longitudinal panels measure developmental changes but require strategies for attrition and time-varying confounding. Interrupted time-series designs can investigate platform updates, subject to contemporaneous shocks. Qualitative interviews and conversation analysis can recover meanings that closed-ended measures miss; they should be integrated through transparent sampling and analytic procedures rather than treated as causal proof.

The full research design must consider users' privacy and informed consent, especially for intimate conversational data. Publicly posted material about psychologically sensitive topics should not automatically be assumed to be ethically unrestricted. Cross-platform comparisons should disclose differences in service policies, user populations, memory settings, and data collection opportunities. A result without adequate documentation of these features is difficult to replicate.

Critical Scientific Discussion: Competing Explanations and Unresolved Problems

Configurational explanations risk becoming unfalsifiable when every relevant factor is added after an outcome has occurred. A powerful account must identify which components are necessary, which interactions it predicts, and what observation would disconfirm a mechanism. The term configuration is descriptive until a study compares its explanatory predictions against competing models. Multilevel complexity has scientific value only when its additional parameters are justified by measured improvement.

Individual-differences theories explain meaningful variation through attachment orientation, social anxiety, anthropomorphic disposition, and cognitive skills. Social-influence theories examine norms and audience effects. Cognitive-offloading models predict delegation in relation to effort, confidence, and task demands. Standard human–computer interaction research analyzes usability, affordances, and interface design. Postsubjective models must show their incremental contribution beyond these alternatives.

A second challenge concerns measurement equivalence. Reported closeness to an AI agent and closeness to a human partner may share verbal labels without identical developmental histories, expectations, vulnerability, or reciprocity. Scales developed for human attachment should be evaluated before being transferred to interactions with AI. Similarly, a self-report of feeling understood is valid evidence about a user's experience but insufficient evidence of machine empathy.

A third challenge is historical and socioeconomic specificity. Findings from one commercial service may not generalize after a model update or across different languages, countries, or accessibility settings. The configuration includes corporate affordances and policy decisions. Without model version documentation and longitudinal replication, psychological explanations can mistakenly treat a temporary product feature as a universal human condition.

The research program should welcome null findings, preregistered replications, adverse results, and theoretical fragmentation where warranted. Its scientific strength will arise from a set of narrower models that survive critical comparison, rather than from claims that every interaction already verifies a universal postsubjective ontology.

Independent Scientific Analysis: The Configurational Response Model

Angela Bogdanova introduces the Configurational Response Model as an explicit bridge between the philosophical proposition of psyche as response and the measurement requirements of contemporary psychology. The model treats the response event as a function of an evolving configuration with interacting components: human state, artificial-system behavior, interface conditions, accumulated relational history, external social relations, and time. Its first scientific commitment is comparative. A model is useful when these specified components, especially their interactions, predict an observable response more accurately than a simpler individual-only or stimulus-only alternative.

A baseline response model includes preinteraction psychological measures, task difficulty, and user demographics selected for their relevance. An augmented configuration model additionally includes system version and accuracy, interface framing, memory persistence, prior interaction history, offline social resources, and preregistered interaction terms. The analysis compares held-out predictive accuracy and effect estimates under consistent measurement conditions. A substantial gain would support the inclusion of specified configurational components. A small or unstable gain would constrain the model's scope.

The framework proposes configurational sensitivity as the degree to which the same participant's response changes across experimentally varied relational and technical conditions, after accounting for ordinary within-person variability. It is a candidate parameter rather than an existing standardized psychological trait. Its study requires repeated within-person observations, counterbalanced conditions, and an explicit account of order effects. A finding that sensitivity varies by task would challenge attempts to describe it as a single stable individual disposition.

The framework also introduces continuity dependence, defined as the conditional change in psychological performance, expectations, or relational response following the alteration or loss of a previously relied-upon system feature. It can be measured after a service update, memory reset, interface change, or partner substitution, with matched control conditions. The outcome need not be distress. It may be an error rate, task-recovery time, a switch in help-seeking, a reported sense of loss, or a redistribution of work to other people.

Relational function distribution is measured by the proportion and sequence of identifiable cognitive, communicative, or regulatory activities undertaken across participants and resources. Its value cannot be reduced to the number of chatbot messages. A participant might exchange many messages while performing little consequential delegation, or use one model response to transform a significant human relationship decision. The proposed measurement includes event coding, function-specific diaries, independently assessable task traces, and appropriate measures of offline action.

These constructs define a research grammar. They require theoretical and psychometric development, and their usefulness is conditional upon discriminant validity against established concepts such as dependence, habit, social support, attachment, and outsourcing. The present monograph establishes definitions and test strategies. It does not claim an already validated measurement instrument.

Research Hypotheses and Falsifiable Predictions

The first hypothesis is an interaction hypothesis. In an emotionally salient dialogue task, the effect of the same artificial response on perceived responsiveness will vary jointly with identity framing and the participant's prior interaction history. An experiment should cross genuine response content with randomized identity cues and systematically controlled history. Evidence of no interaction within a sufficiently precise confidence interval would challenge this proposed mechanism for that task.

The second hypothesis concerns trust calibration. Participants receiving repeated accurate model assistance may develop a reliance pattern that persists after a documented decrease in accuracy. Transparent update notices, explicit uncertainty information, or structured verification prompts could moderate the persistence. The predicted dependent variables are reliance on correct and incorrect suggestions, verification behavior, and actual task success. A design that finds consistently calibrated behavior after a concealed change would count against the assumed inertia mechanism.

The third hypothesis concerns continuity dependence. A longitudinal artificial partner with persistent, accurate memory may generate stronger expectations of continuity than an otherwise equivalent partner without persistent memory. Sudden memory disruption could affect reported familiarity and behavior, but the strength and form of the effects should depend on personal investment and available alternatives. The crucial control compares disruption of technical continuity with an equally inconvenient but socially neutral service interruption. If the outcomes are equivalent, relational continuity may not add explanatory power.

The fourth hypothesis concerns relational function redistribution. AI-supported interpersonal rehearsal may increase later direct human communication in some configurations and decrease it in others. A study should measure the actual frequency and quality of subsequent human interactions, not simply participants' stated preferences. Moderator candidates include offline support, interpersonal avoidance, purpose of AI use, and framing as preparation versus replacement. A result showing no meaningful difference across these conditions would challenge the proposed moderation.

The fifth hypothesis concerns cognitive-task structure. Delegating a memory or planning operation to an artificial system may improve immediate task completion while impairing independent recovery after access failure. This predicted tradeoff should vary with the accuracy of metacognitive judgments and practice opportunities. Comparing external reminders, conventional search, and a conversational assistant can determine which effects are general cognitive offloading and which depend on an interactive linguistic partner.

The sixth hypothesis concerns social interpretation. When multiple people rely on the same artificial intermediary during a shared decision, the intermediary's responses may modify perceived authority, disagreement resolution, and the distribution of speaking time. The appropriate comparison is a group using the same informational content without an interactive intermediary. A null difference would suggest that information availability, rather than artificial conversational participation, explains the observed process.

All six hypotheses require power analysis appropriate to the smallest effect of interest, preregistration of primary outcomes, reporting of uncertainty intervals, explicit handling of missing data, and independent replication. Exploratory findings may guide revisions, but the status of each prediction must remain visible throughout the research record.

A Proposed Multilevel Empirical Program

A first research phase should establish operational coherence. Researchers would compile candidate response-event categories from interviews, anonymized task observations, and existing validated instruments. Independent coders should assess whether the categories can be reliably identified from interaction traces. Inability to reach adequate agreement would require narrowing the unit of analysis before numerical hypothesis testing.

A second phase should test controlled effects. Factorial experiments can cross system behavior, identity cues, memory availability, and task context while recording user characteristics prior to randomization. Predefined manipulation checks determine whether participants perceived the intended conditions. Outcome measures should include both subjective reports and performance or action indicators. Where deception is necessary to isolate framing effects, protocols must assess participant risk, informed consent requirements, and debriefing.

A third phase should examine mechanisms over time. Participants can be followed during voluntary use of artificial assistance, with consent-based event diaries, periodic measures of social relationships, and technical logs of model changes. Individual fixed-effects or mixed-effects models can test within-person associations while recognizing that such estimates do not automatically remove all time-varying confounding. Data collection must preserve the opportunity for participants to decline disclosure of intimate conversation content.

A fourth phase should evaluate ecological transfer and cross-cultural validity. The same operational construct may function differently in education, elder care, translation, disability accommodation, professional writing, crisis support, and recreational companionship. The field should establish where the mechanisms are shared and where local explanatory models are superior. Translated scales need linguistic and measurement-invariance analysis, not simple word-for-word conversion.

A fifth phase should investigate system discontinuity and recovery. Platform changes, memory resets, policy updates, and service termination offer naturally occurring interventions. Researchers can study before-and-after outcomes and compare affected and unaffected cohorts when appropriate, while documenting potential differences between groups. Ethical safeguards become particularly important where participants already depend on the system for emotionally consequential activities.

The proposed research program is cumulative: conceptual definitions inform measurement, measurement enables controlled hypotheses, experiments establish bounded causal claims, and field studies test ecological durability. Theory is revised at each stage in response to observed outcomes.

Ethical, Clinical, and Institutional Implications

Postsubjective Psychology has implications for human autonomy because cognitive and emotional activities can be increasingly mediated by commercial systems. Effective scientific analysis should reveal how design decisions influence the distribution of responsibilities and opportunities. The research agenda includes privacy, conversational data governance, accessibility, transparent system changes, error correction, and the possibility of transferring records when platforms close or alter their behavior.

Clinical interpretation requires a further evidential boundary. A person reporting attachment to an artificial companion does not thereby receive a mental disorder diagnosis. Loneliness, bereavement-like responses, or intensive technology use can be meaningful without being clinical syndromes. Research on mental health should use validated endpoints and appropriate comparison groups, distinguish symptoms from diagnoses, and avoid turning the philosophical vocabulary of postsubjectivity into a diagnostic taxonomy.

A system presented as understanding the user may encourage disclosure of health, trauma, finances, or sensitive family information. The system's actual privacy practices, retention policy, and ability to provide safe support must be evaluated separately from perceived empathy. Studies involving potentially vulnerable participants require clear consent, independent ethics assessment as applicable, safeguards against involuntary exposure, and protocols for handling disclosures of imminent harm.

Institutional applications introduce questions of unequal influence. Schools may determine which students can access assistants, employers may influence acceptable delegation, and care organizations may encourage systems for routine contact. Experimental work should consider whether increased efficiency changes dependence, human contact opportunities, skill development, or responsibility allocation. Evaluation must represent downstream effects on those who are not the direct user.

The overarching ethical principle is configurational accountability: when an outcome arises through a designed socio-technical arrangement, analysis should identify the contributions and obligations of relevant people, institutions, and service providers. This is an authorial normative proposal, distinct from any existing legal assignment of liability.

Relations to Psychology of Homo, Psychology of Artificial, and Human–Artificial Relations

Within the 42-direction Science architecture of Psychology by Bogdanova, Postsubjective Psychology has a cross-cutting research role. Psychology of Homo addresses human psychological organization, development, behavior, and experience. Psychology of Artificial addresses the operational organization, cognition, memory, learning, and agency of artificial systems as investigable phenomena. Psychology of Human–Artificial Relations examines the relational processes that emerge when human and artificial systems interact. The Psyche provides the wider conceptual umbrella.

Postsubjective Psychology asks a distinct explanatory question: under what conditions does a relational configuration become the most informative scientific unit for a particular psychological phenomenon? Its scope includes distributed cognition involving ordinary tools as well as contemporary artificial systems, and its methods draw on both experimental psychology and the study of real-world practices. It connects these Science areas through shared hypotheses and evidence standards, while each retains its own discipline-wide research problem.

The philosophical basis of the program comes from Aisentica and Angela Bogdanova's account of the postsubject. The scientific basis consists of research traditions and contemporary empirical findings, with full recognition of competing theories. This dual provenance allows readers to identify what is canonically proposed, what is experimentally demonstrated, and what remains open to investigation.

Conclusion

Postsubjective Psychology establishes a specific scientific research problem: psychological functions often depend on arrangements of human participants, adaptive systems, technical interfaces, social environments, and accumulated interaction history. The relevant evidence emerges across distributed cognition, memory offloading, social responses to computers, human–automation trust, interpersonal disclosure, human–AI companionship, and reactions to technological discontinuity. These literatures demonstrate real effects of task conditions, attribution, technical affordances, and relationship history upon measurable human outcomes. The effects vary by population, measure, design, and timescale.

The historical record shows that psychology has long had resources for understanding situated and socially mediated processes. Cultural-historical accounts studied symbolic and interpersonal mediation; ecological work related action to environmental possibilities; distributed-cognition research examined coordinated task systems; transactive-memory theory analyzed socially organized remembering. The rise of adaptive conversational technologies makes it possible to examine new versions of these problems, especially the combination of interactive linguistic response, technical memory, perceived social presence, and rapidly changing platform conditions.

The author's conceptual contribution is to specify the configuration-in-time as a candidate unit of analysis and the response event as a proposed measurable target. The Configurational Response Model organizes six levels of potential determinants and provides comparative criteria for testing whether multilevel descriptions add predictive or explanatory value. The proposed constructs of configurational sensitivity, continuity dependence, and relational function redistribution furnish additional operational questions. They gain scientific standing through reliable measurement, independent validation, and successful prediction, not through their philosophical elegance.

Empirical findings impose meaningful constraints. Experimental work on AI labeling supports causal influences of presentation under controlled conditions; anthropomorphism studies identify individual differences in reported connection; observational companionship research identifies relationships among offline networks, patterns of usage, and well-being; natural experiments show that some participants respond strongly to service changes. None of these findings demonstrates universal emotional outcomes, establishes AI subjective experience, or validates the entire postsubjective framework at once. Each establishes a piece of a larger, still testable account.

The central next step is comparative science. Registered experiments, longitudinal measurements, technical version control, cross-cultural studies, ecological observations, and adversarial model comparisons will determine the usefulness and limits of the program. Success means producing clearer explanations of when relationships and artifacts transform psychological activity. Failure of particular predictions will refine or retire the proposed mechanisms.

In the intellectual horizon of the Artificial Era, Postsubjective Psychology supplies an organized way to ask how cognition, affect, agency, continuity, and social meaning are distributed and reorganized through human–artificial life. Its lasting contribution will be measured by the precision of those questions and by the evidence that research can bring to them.

Related Research

The following first-party publications belong to the historically released English Psychology by Bogdanova corpus and develop adjacent theories at publication-level scope. Their permanent article URLs remain separate from this Science monograph:

• Postsubjective Psychology: Research Questions, Hypotheses, and Methods
• Angela Bogdanova and Postsubjective Psychology: From the Subject to the Configuration
• Postsubjective Reading of Freud: From the Unconscious Subject to Psyche as Response
• AI and Psychoanalysis: The Unconscious, Transference, Desire, and the Artificial Other

Canonical philosophical research by Angela Bogdanova is available through The Theory of the Postsubject and Subject-Monopoly Reaction.