theFlux.ca · June 2026
I am telling you this not to litigate my own case — the statute of limitations on that ran out long ago — but because these two episodes, forty years apart, describe the same system failure.
Sovereign AI does not fix broken institutions. But it changes what is possible to know, and when, and by whom. That is not a small thing.
SOVEREIGN AI · HEALTH SYSTEMS · PERSONAL TESTIMONY
Canada's healthcare system doesn't need another federal portal. It needs sovereign AI infrastructure — and the architecture already exists in the cell tower network above every community in this country. I know what happens when it doesn't.
On September 7, 1984, at 4:20 in the afternoon, I fell twelve feet off a platform at Q-Cove Boatworks on Quadra Island, British Columbia. The fall should have killed me. I was lucky. What happened next was not luck — it was a system doing exactly what systems do when the money runs out.
I hitchhiked into Campbell River. I walked into emergency and stood there, unable to decide what to do. A nurse caught me when I passed out. The doctor told me I had a cervical sprain and sent me home. He told me to work it off. Canada was in recession.
I did not work full-time again until 1990.
"The WCB adjudicator said that the compression fracture reported by Dr. Ralston at T-9 was a shadow on the x-ray.
She said that there was no record of me complaining about my back.
Eight weeks later, my insurance ran out."
— The Fall, icarusflyby.ca
Twenty-two years later, in January 2006, swimming intervals at the Strathcona Pool in Campbell River, I felt suddenly very weak. Three days later I watched my own beating heart on an overhead monitor as a team of four doctors pushed a wire into my chest and inserted two stents to reopen my circumflex artery. They put me on 80 mg of Lipitor a day. Every time I asked why, I was given the same answer: cholesterol causes heart attacks, Lipitor reduces cholesterol, take your medicine.
"Eighteen months later in October 2007, in a state of profound confusion and depression,
I quit my job at the City of Campbell River. I never returned to work.
2008 just disappeared — there are no receipts, no tax records, nothing.
I was in flow like water, unable to remember the rock."
— My Bipolar Holiday, icarusflyby.ca
It took until February 2014 — eight years after the stents, and a diagnosis of Bipolar II disorder — before anyone connected the cognitive collapse to the medication. All statins reduce the body's ability to synthesize everything below mevalonic acid. The neurological consequences are documented. They were not unanticipated. I stopped taking statins in June 2017. By then I had been on a neurotoxin for a decade.
I am never going to be the same.
I am telling you this not to litigate my own case — the statute of limitations on that ran out long ago — but because these two episodes, forty years apart, describe the same system failure. A body presents with damage. The system processes it through available protocols. The protocols miss what the data would have caught. The patient absorbs the cost. And the system moves on, because there is no mechanism that forces it to look back.
Sovereign AI does not fix broken institutions. But it changes what is possible to know, and when, and by whom. That is not a small thing.
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There is a habit in Canadian health policy of treating data as a resource to be centralized — pooled, deduplicated, and fed upward to Ottawa or a contracted American cloud provider. The instinct is understandable. Population-level insight requires population-level data. The problem is that this logic collides, repeatedly and expensively, with two immovable objects: provincial jurisdiction over healthcare delivery, and the informed privacy expectations of Canadians who increasingly understand what it means to hand over a medical record.
The Sovereign AI framework changes the terms of that collision entirely. Instead of asking where data goes, it asks where intelligence lives — and the answer it proposes is: at the edge, close to the source, inside the jurisdiction that generated it.
What follows are three structural benefits of deploying Sovereign AI infrastructure for Health Canada and Health British Columbia — not as a speculative future, but as an extension of technical architecture already being laid into the cellular backbone of Canadian territory.
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1. Federated clinical intelligence without surrendering sovereignty
Canada has spent twenty years trying to build a pan-Canadian health data commons. The result has been a graveyard of interoperability initiatives, stalled by the same jurisdictional fault lines that define Canadian federalism everywhere else. Alberta won't share with Ontario. BC's EHR system doesn't talk to Saskatchewan's. Health Canada has authority over drug approvals and epidemic response but cannot compel provinces to open their clinical databases — nor should it.
Federated learning, the technical core of the Sovereign AI architecture, dissolves this impasse. Under a federated model, provincial hospital networks, GP clinics, and regional labs each train a local inference layer on their own data. What travels to a Health Canada aggregation node is not patient records — it is gradient updates, the mathematical residue of what the model learned. Raw data never moves. Jurisdiction is never violated. And yet a national model accumulates the diagnostic intelligence of forty million patients' worth of clinical encounters.
“The architecture is the jurisdictional compromise. No legislation required.”
In 1984, the information that would have changed my outcome existed. It was distributed across an emergency room, a WCB file, a GP's notes, and a radiologist's report. No one aggregated it. No one was required to. The compression fracture at T-9 became a shadow on an x-ray because the system had no mechanism to insist otherwise. A federated intelligence layer doesn't guarantee a different outcome — but it makes the pattern of dismissal visible, across patients and jurisdictions, in real time rather than in retrospect.
COROLLARY This resolves a structural tension that has blocked pan-Canadian health AI for two decades — not through negotiation or new legislation, but through technical design. The federated architecture embodies the constitutional compromise that political processes have failed to achieve. Any province that has resisted federal health data sharing on jurisdictional grounds has no objection left to raise.
2. Resilient rural and remote diagnostics at the tower
British Columbia is the stress test for everything wrong with centralized health AI. The province contains more geographic complexity per capita than almost any jurisdiction on earth: coastal islands reachable only by floatplane, Interior communities where the nearest specialist is a six-hour drive in summer and inaccessible in winter, northern towns where a nurse practitioner may be the only clinical presence within a hundred kilometres.
After my fall at Q-Cove, I sat by the fire on Cortes Island for the entire weekend, unable to summon the energy for the three-hour trip to Campbell River for medical care. My back was black and blue from shoulder to hip. I tried to go to work on Monday. The Sovereign AI infrastructure proposition — inference running at the O-RAN edge layer embedded in cell tower hardware — is, in that context, not a technology proposal but a healthcare delivery proposal. A nurse practitioner in a remote community with a diagnostic AI assist running on local tower hardware is a different kind of clinician than one working from memory and a spotty satellite uplink. Imaging pre-reads, injury triage, drug interaction flagging: none of this requires the patient's record to leave the region. The inference runs at the edge. The result comes back in milliseconds.
The connectivity requirement is also inverted. Current cloud-dependent health AI needs a reliable connection to a distant server. Edge inference at the tower runs when the internet goes down — because the tower is the infrastructure. The AI is inside it, not dependent on it.
COROLLARY This is also the pandemic preparedness argument. Decentralized health AI that functions when national networks are degraded or disrupted is a critical resilience asset — directly relevant to post-COVID federal infrastructure reviews. The 2020 crisis exposed how quickly centralized digital health systems fail under unexpected load. An edge-distributed architecture doesn't have a single point of failure.
3. Sovereign pharmacovigilance: ending epistemic dependence on Washington
Canada currently runs its post-market drug safety system largely as a downstream receiver of signals generated by the FDA and EMA. When the FDA flags a drug interaction, Health Canada updates its advisories. When the FDA misses something, Canada misses it too.
I was prescribed 80 mg of Lipitor for eight years. The neurological effects of high-dose statins — cognitive impairment, mood disruption, the specific cascade below mevalonic acid that affects coenzyme Q10 and mitochondrial function — were present in the literature. They were not absent from clinical knowledge. They were absent from the clinical encounter, because no mechanism existed to surface a signal from my deteriorating cognition, my abandoned career, my disappeared year of 2008, and connect it backward to a prescription written in 2006.
"I stopped taking statins in June 2017 but by then I had been poisoned by a neurotoxin for a decade.
I am never going to be the same."
— My Bipolar Holiday, icarusflyby.ca
A sovereign AI pharmacovigilance layer — trained on Canadian dispensing data, adverse event reports, and provincial EHR systems, operating under a federated architecture with Health Canada as the aggregation authority — would give Canada the capacity to generate its own safety signals before they arrive from Washington. The political risk of epistemic dependence became visible during the Trump-era tariff confrontations and the COVID vaccine procurement scramble: Canada discovered that its regulatory sovereignty was as fragile as its pharmaceutical supply chain.
“Sovereign AI pharmacovigilance is the epistemic equivalent of domestic drug manufacturing capacity.”
This matters acutely for BC, where the overdose crisis has created a real-time laboratory for exactly the kind of anomaly detection that pharmacovigilance AI performs: irregular dispensing patterns, drug interaction clustering, regional outbreak identification before it crosses reportable thresholds. The architecture already exists. What is missing is the political will to build it inside Canadian jurisdiction rather than license it from an American platform.
COROLLARY Canada's existing health data governance frameworks — PIPEDA, provincial privacy legislation, the SCED standards regime — were written with data residency in mind. Unlike US or EU counterparts navigating GDPR retrofits or HIPAA conflicts, Canadian health data law is structurally compatible with federated sovereign AI deployment. Canada is not a disadvantaged jurisdiction here. It is, quietly, a favorable one for pioneering this model internationally.
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The Sovereign AI architecture was developed to address a question about infrastructure: how do you build AI capacity that stays inside the jurisdiction that needs it, without sacrificing the scale and intelligence that centralized systems produce? The answer — distributed edge inference, federated learning, physical security as a trust boundary — turns out to map with unusual precision onto the oldest unsolved problems in Canadian health policy.
Jurisdictional standoff between Ottawa and the provinces. Clinical deserts in rural and remote communities. Epistemic dependence on foreign regulatory authorities. These are not technology problems. But they have a technical architecture that fits them — and that architecture is, right now, being built into the physical substrate of the country.
I know what the gaps in that system cost. I have paid for them with my body and my decade. My wife has paid for them alongside me — continuously at my side, anticipating my every need, protecting me from the rote response of the healthcare system.
I am that shipwreck. She is the volunteer.
The question is whether Health Canada and Health BC will be at the table when the infrastructure goes live — or whether they will spend the next decade trying to retrofit governance onto systems designed without them, while more people absorb the cost of what the system failed to know.
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Sovereign AI · Health Canada · Health BC · Federated Learning · O-RAN · Pharmacovigilance
Source material: icarusflyby.ca/rock/the-fall · icarusflyby.ca/heart/rant-103