Selfsway The personal life model network Token symbol: SELFSWAY Your life model, under your control Selfsway is a proposed network for personal life models that people control, update over time and make available to AI services through explicit permission Our aim is to help each person build a lasting understanding of their own health history, then decide which AI services may use it and for what purpose Why Selfsway A report captures one appointment, a wearable captures part of a day and personal notes add context that neither can explain on its own These records often sit in separate systems, leaving each new service with only a fragment of the person behind them Selfsway plans to organize information that a person chooses to provide into a model with traceable sources, clear distinctions between evidence and interpretation, and a history of corrections Compatible AI services could then work with the relevant background under separate permissions, helping understanding carry forward across applications What a personal life model contains A personal life model is an evolving representation of a person's recorded state, history and changes over time General AI supplies reasoning capabilities, while the personal model supplies the individual background available for a particular task The proposed model keeps four kinds of information distinct Original records Reports, device readings and personal entries retain their sources and timestamps so an interpretation can be traced back to its evidence Confirmed information Personal history confirmed by the individual and information supported by clear evidence are labeled separately and remain open to correction Calculations and interpretations Trends and possible explanations show their supporting records, missing context and uncertainty, with AI interpretations kept distinct from established facts Follow-up and corrections New records, personal feedback and later outcomes can revise earlier interpretations while preserving the history of what changed and why The quality of a model depends on its evidence, update process and ability to handle mistakes How the model would work Choose the sources The individual chooses which reports, personal records and supported devices to connect, with integrations introduced as the product develops Organize the evidence The system aligns dates, units and formats while retaining original sources and flagging duplicates, missing information and conflicts Build personal context When there is enough evidence, the model describes longer-term patterns and records how new information differs from earlier observations Grant permission for a task The individual chooses the AI service, intended purpose, permitted information and access duration, with access limited to what the task needs Update through feedback Personal corrections and subsequent evidence inform revisions, with each interpretation retaining its supporting context and uncertainty One model, separate permissions A sleep service could receive sleep records and selected routine notes for a review of recent changes An activity service could receive activity logs and personal observations for a review of exercise and recovery context A visit-preparation service could receive selected reports and confirmed history to organize questions for a clinician Each service would operate within its own permission scope, without gaining automatic access to the rest of the model The initial product scope is planned around record organization, explanations of recorded changes and preparation for clinical appointments Diagnosis and treatment decisions remain the responsibility of qualified healthcare professionals Personal control and privacy Personal models are intended to remain separate, with the network sharing interface standards, permission rules and service settlement methods Raw health records, identifying information and personal model details are planned to be encrypted and stored off-chain Blockchain use is intended for necessary service settlement and verifiable service obligations, with public records designed to avoid revealing personal health information Revoking permission would stop future access controlled by the system, but it cannot automatically retrieve information already received or retained by a third party Training use would require separate, explicit permission SELFSWAY and network services Model maintenance, data organization, computation and authorized AI calls require ongoing work SELFSWAY is proposed as a way to settle those services and coordinate shared network responsibilities Service settlement Pay for defined services such as model maintenance, data processing, computation and authorized AI calls Provider compensation Compensate providers for work actually delivered, funded by service fees or an explicitly disclosed ecosystem budget Provider bonds Once verifiable obligations and dispute procedures exist, require bonds for selected services to support commitments such as availability and settlement Public network governance Once governance mechanisms are established, participate in decisions about network fees, integration standards and shared resources Provider bonds would apply to specific service commitments and would not guarantee the correctness of medical judgments Access to personal health information would always depend on the individual's explicit permission Holding SELFSWAY would not grant access to anyone else's records or model Basic management of one's own information is intended to be independent of token ownership, with application-sponsored payments among the settlement options under consideration Token functions depend on the corresponding products and network rules becoming operational Supply, allocation, release schedules and fees require separate disclosure in a formal token proposal Development sequence First, validate a complete personal-model workflow: import records, inspect sources, correct information and grant a clearly bounded AI permission Then, add supported data sources and compatible applications to test whether useful context can carry forward across services Introduce service settlement, provider bonds and governance as the network develops actual needs and workable rules Current stage Selfsway is in the concept and product-planning stage The network capabilities and SELFSWAY functions described here are proposed designs The website's permission experience is a local illustration using preset examples, without connections to real devices, personal records or AI services Actual features, supported integrations and token arrangements will be defined through formal releases and disclosures