The Experience Semantic Protocol — A North Star for Post-Linguistic Communication & Hive Mind

The Experience Semantic Protocol (ESP) is a protocol architecture for communicating typed, consent-governed latent representations of experience between humans and machines. It begins from a structural limitation of language: an utterance does not contain the experience it describes; it acts as a compact pointer into a receiver-side semantic prior built from language, culture, memory, embodiment, and common ground. ESP proposes a different operating regime in which part of that effective codebook becomes explicit, trainable, interoperable, and auditable. ESP decomposes experiential state into six approximately decorrelated semantic types — knowledge, intention, emotion, context, sensory, and temporal (TAOSS) — so that disclosure, consent, privacy accounting, compatibility, and leakage can be governed at the type level. The protocol defines a fixed 100-byte live-packet header, authenticated encryption, pseudonymous sender identities, canonical typed-latent encodings, bidirectional sender/receiver capabilities, revocation, persistent encrypted Experience Capsules, cross-encoder semantic anchors, and explicit handling of quantization, replay, provenance, post-quantum migration, and receiver-side policy enforcement. The mathematical layer separates established results from conjecture. It includes a proven local stability bound for attention-based processing, an explicitly identified disentanglement conjecture, predictive-V\mathcal V-information leakage measures, differential-privacy accounting under declared adjacency relations, and quantitative limits showing when strong local runtime DP is incompatible with high-rate semantic transfer. Three preregisterable hypotheses — H1 consent granularity, H2 cross-type leakage reduction, and H3 downstream utility — define the core falsification program, ExperienceBench. ESP is deliberately broader than human-to-human communication. The Machine Experience Bridge extends the same consent and provenance semantics to vehicles, robots, assistive systems, and machine agents. An ESP-Agent profile addresses contemporary latent communication between AI systems while explicitly distinguishing raw hidden/KV states from audited TAOSS representations. Threat T19, latent inversion / semantic over-recovery, treats interoperability itself as a potential attack surface. The long-horizon architecture includes encrypted persistent semantic memory, Experience Legacy for lifespan-decoupled semantic records, and a Typed Hive model for consent-bounded collective latent dynamics. The Hive layer formalizes predictive collective emergence, diversity, autonomy, influence concentration, member-level privacy, identified and anonymous membership modes, and safeguards for collective intention. It does not claim collective consciousness or phenomenal experience transfer. ESP is therefore both an implementable L1 protocol architecture and a North Star for progressively richer post-linguistic communication. Natural language remains a valuable renderer, but need not remain the compulsory transport representation if interoperable latent communication becomes sufficiently reliable, governable, and safe. The first ESP implementation is the Emotional Movie Search Engine, an L1 film-retrieval application using typed experiential representations. The official implementation repository is: https://github.com/Vigilant-CRS/Experience-Semantic-Protocol_Emotional-Movie-Search-Engine The current document is a protocol and research specification rather than a claim of completed empirical validation. Publicly reproducible ExperienceBench results and full conformance vectors remain future empirical deliverables. Keywords: Experience Semantic Protocol, post-linguistic communication, semantic communication, typed latent representations, multimodal representation learning, consent capability, differential privacy, latent-space interoperability, semantic leakage, brain-computer interface, machine-to-machine communication, collective intelligence, cryptographic governance, ExperienceBench.