An OAII advocacy perspective
Aging-in-place technologies often fail for a simple reason: they confuse awareness with surveillance.
Many systems assume that safety requires continuous monitoring — cameras always on, microphones always listening, data always streaming. This assumption is both technically unnecessary and ethically unsound.
The OAII Base Model takes a different position:
Safety emerges from meaningful events, not from constant observation.
Surveillance Is a Design Choice, Not a Requirement
Surveillance-heavy architectures are not inevitable. They are the result of design shortcuts:
- treating raw data as inherently valuable,
- pushing interpretation into centralized systems,
- optimizing for model training rather than human dignity.
In the home, these shortcuts create permanent risk:
- loss of privacy,
- unclear data ownership,
- opaque inference pipelines,
- long-term behavioral profiling.
Aging-in-place demands better boundaries.
Events as the Unit of Meaning
In the OAII model, an Event is not a raw detection or a continuous state.
An Event is:
- bounded in time,
- scoped to a World,
- derived by comparing observations to local knowledge,
- associated with uncertainty and revision.
Examples include:
- a door opening outside a typical time window,
- prolonged absence of motion in a normally active space,
- an unexpected transition between rooms.
Crucially, these Events can be recognized without retaining continuous audio or video.
Privacy by Architecture, Not by Policy Alone
Privacy protections often fail when they are layered on after the fact.
The OAII Base Model embeds privacy structurally:
- Signals are non-semantic and ephemeral by default;
- Sensor Knowledge remains local and scoped;
- Events summarize meaning without exposing raw data;
- World boundaries prevent context leakage;
- Edge-primary execution keeps sensitive data in the home.
This is privacy by construction, not by promise.
Episodic Sensing, Not Continuous Monitoring
One of the most important architectural shifts is the move from continuous sensing to episodic activation.
In an event-based system:
- low-cost signals establish baseline awareness,
- candidate Events trigger escalation only when needed,
- higher-cost sensing (audio, vision) is activated briefly and locally,
- raw data can be discarded after summarization.
This dramatically reduces exposure while improving relevance.
Accountability Requires Bounded Meaning
Surveillance systems struggle with accountability because meaning is diffuse:
- data accumulates without clear purpose,
- inferences are implicit and hard to audit,
- responsibility is distributed across opaque pipelines.
Event-based systems are different.
Each Event:
- has a declared type,
- has a defined lifecycle,
- references its evidence and knowledge sources,
- can be reviewed, revised, or invalidated.
Accountability becomes possible because interpretation is explicit.
Why This Matters for Aging-in-Place
For older adults, dignity and autonomy are not secondary concerns.
An aging-in-place system should:
- notice when something meaningful changes,
- stay quiet when nothing does,
- explain why attention is warranted,
- and do so without turning the home into a monitored space.
Event-based architecture makes this balance achievable.
The OAII Position
The Open Autonomous Intelligence Initiative advocates for AI systems that:
- treat events as the primary unit of meaning,
- reject unnecessary surveillance by design,
- enforce privacy through structure,
- and keep intelligence local whenever possible.
In aging-in-place, this is not an optimization.
It is a requirement.
This post builds on the OAII Base Model’s Event, Signal, Sensor Knowledge, and World concepts, and frames event-based design as a privacy and accountability imperative rather than a technical preference.
Open Autonomous Intelligence Initiative 
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