Domain AUR

Personal Aura and learning

Start here · Questions · Progress · People decide

Help people navigate the network, keep control of personal information and learn the next practical step.

Question	What we are working out	AI-generated potential answers and research	Work state
AUR-01	What useful navigation can a first-time visitor receive from a personal Aura, the proposed AI assistant, while choosing how much personal context to share?	AI-generated option: Offer guest navigation first, with an optional personal Aura helping someone find notices, services and the next useful step. Let the person choose the context shared for that task. Show the source, its age and a clear path to human assistance and session exit. AI-generated future concept: Explore an Aura explaining the same task through speech, text or XR using the person's chosen context. Evaluate comprehension, privacy, permissions and energy before claiming richer interaction improves the experience. Research examples: Web Content Accessibility Guidelines 2.2 · Kiwix Hotspots: an offline library over a local Wi-Fi network	open
AUR-02	How will the light-to-ultra-high-definition Aura journey be described in terms people can understand and compare?	AI-generated option: Describe Aura's proposed light-to-ultra-high-definition levels through the context a person chooses, tasks supported and evidence of useful results. Compare them on shared examples. Display quality, computing location and emergency energy settings would each remain separate choices, with GAJRA Earth as the values starting point. AI-generated future concept: Explore an ultra-high-definition Aura combining personally chosen history, simulations and specialist agents, with inspectable sources and reversible sharing choices. Treat advanced AI/SI performance as a hypothesis measured for each task and model edition. Research examples: llama.cpp: local and hosted language-model inference · NIST AI Risk Management Framework 1.0: core functions	open
AUR-03	How will the personal Aura operating system help someone find the next useful action as everyday services, transport and warning conditions change?	AI-generated option: Make an action card stating what the person can do, the issuing source and check time, and any confirmation still needed. The Aura could explain the card and compare options using chosen context. Official instructions and service availability would retain their actual source and status. AI-generated future concept: Explore a personal assistant comparing a ferry suspension or service closure against the person's chosen needs, then preparing a revised plan for confirmation. Show assumptions and withhold any claim that an unconfirmed alternative is available. Research examples: Translink open data: schedules and real-time feeds · Common Alerting Protocol Version 1.2	open
AUR-04	How can just-in-time learning help a resident or relief operator learn the next permitted task and recognise when a qualified person is needed?	AI-generated option: Prepare short task lessons linked to the actual equipment and approved procedure: prerequisites, demonstration, practice, check and handover. An Aura would help someone find the next permitted step and recognise when to pause for qualified assistance. Observed practice would establish usefulness. AI-generated future concept: Develop a spatial rehearsal of a permitted task, with an Aura adapting explanation to the learner's chosen needs. Compare real task performance after the lesson; simulated success would remain distinct from qualification and work permission. Research examples: About Kolibri: offline learning on devices and local networks · Web Content Accessibility Guidelines 2.2	open
AUR-05	How will a person's sharing choices travel with their records and AI work between a device, local hub and outside service?	AI-generated option: Attach understandable sharing choices to each record and derived item, naming purpose, recipient, copies, expiry and exit arrangements. Preview transfers between personal device, local hub and outside service. Track copies and AI derivatives explicitly, because withdrawing future access alone cannot recall information already received. AI-generated future concept: Explore an assistant comparing a proposed transfer with the person's recorded choices and producing a plain-language preview. Restricted cultural material would follow its custodians' actual conditions; the assistant's interpretation would remain open to review. Research examples: Solid FAQ: personal data sharing, storage and copies · NIST AI Risk Management Framework 1.0: core functions	open
AUR-06	How will a person decide which actions their Aura may read about, draft, propose or carry out on their behalf?	AI-generated option: Give each Aura action a stated scope: read, draft, propose or execute. Match execution to the person's existing authorisation, the actual recipient and an expiry. Show a preview and completion receipt, with cancellation and a recorded reason when changed circumstances require a new decision. AI-generated future concept: Explore a shared task card that an Aura, advanced AI/SI or robot can interpret, with bounded tools and observable completion. Trial expired and repeated actions in simulation before allowing the card to trigger real equipment or external services. Research examples: NIST AI Risk Management Framework 1.0: core functions · NIST SP 800-63B-4: authenticator event management	open