_True You_: A Behavioral Congruence Framework for Human, Artificial, and Human–AI Alignment

*True You: A Behavioral Congruence Framework for Human, Artificial, and Human–AI Alignment* proposes a framework for measuring whether an intelligent agent’s observed behavior corresponds to its declared or required behavioral profile over time. The framework is developed in three stages. For humans, True You is voluntary and is intended to support self-knowledge, behavioral self-assessment, interpersonal alignment, and evidence relevant to trust while recognizing substantial privacy and surveillance concerns. For sufficiently capable artificial intelligence systems, the paper proposes that True You should become compulsory: AI systems should maintain explicit behavioral alignment specifications, continuously self-report compliance, undergo independent evaluation, assess other AI systems, and track alignment drift over time. For humans substantially augmented with AI, the paper proposes a compulsory composite alignment framework that evaluates the behavior of the combined human–AI agent, including emergent behavior, attribution of actions, preservation of human autonomy, and prevention of “alignment laundering” across the human–AI boundary. Version 1.1 expands the human True You model by introducing the concept of **behavioral concept-boundary profiles**. Rather than asking only whether a person considers themselves “honest,” “nonviolent,” or “someone who does not swear,” True You can use clusters of concrete behavioral questions to infer how that person operationally defines concepts such as swearing, stealing, lying, cheating, and similar moral or social categories. The paper distinguishes between observed behavioral frequency and a person’s explicit classification of a behavior, allowing future research to test whether these individualized conceptual boundaries are stable and predictive. Version 1.1 also expands the proposed applications of Human True You profiles. These include improved self-understanding, compatibility matching in online dating, formation of aligned groups in massively multiplayer online games, personalization of virtual-reality environments, and speculative long-term preservation of behavioral identity. The latter is discussed in relation to Hans Moravec’s writings on future computation, simulation, and possible technological reconstruction of human persons, while explicitly distinguishing behavioral reconstruction from demonstrated continuity of consciousness or personal identity. The paper introduces formal definitions for behavioral congruence, interpersonal alignment, evidence coverage, AI self-congruence, required alignment compliance, severity-weighted compliance, alignment drift, and composite human–AI behavior. It also presents falsifiable research hypotheses, privacy and ethical constraints, failure modes, and a staged empirical validation program. The central thesis is that alignment should not be treated solely as an intention, policy, training objective, value statement, or one-time certification. It should also be treated as a continuously measurable relationship between declared or required behavior and observed behavior. This is Version 1.1 of a conceptual research preprint. It has not undergone peer review and does not report original human-subject experiments or claim empirical validation of the proposed framework.