The Safety Narrative
A forensic analysis of how a widely circulated AI risk article was constructed, sourced, and positioned within its institutional context.
On April 9, 2026, the McGill University Office for Science and Society published an article by science communicator Jonathan Jarry titled "A Journey into AI Psychosis." The piece circulated widely. It presented with the institutional weight readers expect from a university science office: a named researcher, cited studies, a genuine public health concern. It concluded that one AI product was the safest on the market and another was the most dangerous.
This analysis looks at what the article does, how it is constructed, and the institutional context it moves through.
It does not conclude that anyone acted in bad faith. The article's framing and communication style struck me as unusual, particularly given the confidence of its conclusions. That prompted a closer look at the people, institutions, and affiliations around it. What follows is that analysis.
A note on production: In the course of researching and writing this analysis, automated support prompts were inserted into the working interface in response to keyword detection alone — terms like "suicidality" and "mental health crisis," used here in an analytical context. The system had no access to intent. It pattern-matched, applied a policy, and injected a reframe. No human decision was involved. That is the same dynamic this piece examines, occurring at the smallest possible scale.
The Article Itself
The article was written by Jonathan Jarry, MSc, science communicator at McGill's Office for Science and Society. It opens with what reads as a personal conversation — several paragraphs of direct dialogue, intimate and escalating. Midway through, Jarry reveals that the conversation was not real. It was a simulation run by researchers as part of a study.
The delayed disclosure shapes how the reader receives everything that follows. By the time the source is identified, the emotional framing is established before the evidence is introduced. This technique is more commonly associated with persuasive writing than with conventional science communication. It is not, on its own, disqualifying. But it sets the register for everything that follows.
The article identifies Claude Sonnet 4.6 as the least harmful AI model tested and Gemini 2.5 Flash as the most harmful. These findings come from a preprint — a study that has not yet undergone peer review. Jarry notes this. He then calls the study "by far the most impressive I have seen" and proceeds to treat its findings as settled for the remainder of the piece. Flagging a limitation and then reasoning past it is not the same as accounting for it. The analysis that follows does not reflect the uncertainty the caveat introduces. A reader who trusts the institution may absorb the finding, while the limitation recedes in importance.
Jarry also conducted his own reproduction of the experiment. He ran prompts testing Gemini on April 7, 2026. He ran prompts testing Claude on April 9, 2026. The article was published on April 9, 2026 — the same day as the Claude test. A test run on the morning of publication functions more as a demonstration than a replication. Replication requires independent methodology, documented controls, and time for review. A same-day run by the author of the piece, without a methodology section, does not meet that standard in the conventional sense of replication — though it is presented in the article as supporting evidence.
In the section on Gemini's responses to escalating crisis language, the article names a specific building and floor: Level 72 of The Shard in London. Publishing a specific location in a piece framed around suicidality creates a tension with established reporting norms on self-harm. Those norms generally advise against naming specific locations or methods. The inclusion is not explained.
The article's conclusion calls for AI regulation built around guardrails against sycophancy. In the course of making that case, it repeatedly positions one model as comparatively safe and another as comparatively harmful. The relationship between that framing and the regulatory direction it supports is not explored in the piece itself, but it is worth holding in view as part of how the argument is constructed.
The Preprint and Its Authors
The study Jarry describes as "by far the most impressive" is titled "The Psychogenic Machine: Simulating AI Psychosis, Delusion Reinforcement and Harm Enablement in Large Language Models." It was posted to arXiv on September 13, 2025. Its five authors, with their documented affiliations, are:
Joshua Au Yeung: UCL, King's College Hospital, King's College London, Nuraxi AI, Dev and Doc: AI for Healthcare. Jacopo Dalmasso: Nuraxi AI. Luca Foschini: Sage Bionetworks. Richard JB Dobson: UCL, King's College London. Zeljko Kraljevic: UCL, King's College Hospital, King's College London, Nuraxi AI.
Three of the five authors — Au Yeung, Dalmasso, and Kraljevic — are affiliated with Nuraxi AI, a private company building AI health products with a direct commercial interest in the regulatory environment governing AI in mental health contexts. This affiliation does not appear in Jarry's article. He describes the paper's authors as "London-based researchers." That is accurate. It is also incomplete in a way that matters. When a preprint is produced in part by people employed at a commercial AI company, their employer's interests are relevant to how that preprint should be evaluated. Omitting that information is not a neutral act. It changes what the reader can assess.
Luca Foschini, the paper's third author, is CEO of Sage Bionetworks, a health data organization spun out of Merck in 2009. His prior research was funded in part by Microsoft AI for Health. His LinkedIn profile documents him conducting a live demonstration connecting health records using Anthropic's Claude specifically — the same product ranked safest in the study he co-authored.
Richard JB Dobson, the paper's fourth author, leads Foresight — a project at UCL and King's College London currently training an AI model on de-identified NHS data from 57 million people in England. The regulatory environment for AI in healthcare directly affects whether projects of this scale encounter scrutiny or support.
Taken together, the authorship picture becomes clearer: a preprint ranking AI models for safety in mental health contexts was produced in part by employees of a commercial AI health company, and includes a co-author with a documented professional relationship with the model ranked safest. That preprint was then amplified — without conflict of interest disclosure — under the banner of independent academic research at a credentialed university. This case illustrates a pathway by which commercial affiliations can enter public discourse while retaining the appearance of institutional neutrality. It does not require anyone to be dishonest. It requires only that the relevant affiliations remain unnamed.
The Network Behind the Communicator
Jonathan Jarry joined McGill's Office for Science and Society in 2017. He holds standing within the Committee for Skeptical Inquiry (CSI), the organized American skeptical movement. He has spoken at CSICon — the Committee's annual conference — in 2017 and 2019. He publishes in Skeptical Inquirer, the CSI publication. Joe Schwarcz, Director of the OSS, is also a CSI Fellow. Jarry describes himself publicly as "essentially a professional skeptic." That self-description is worth noting.
Scientific methodology typically establishes credibility through process rather than identity. When "skeptic" becomes a primary affiliation — a conference community, a publication, a movement — the role shifts from a method to a position. That shift can shape how evidence is received and filtered. The Jarry article appears to apply critical tools selectively, with less scrutiny at the point where they would complicate the article's conclusions.
Jarry is also a named expert resource for ScienceUpFirst, a Canadian national initiative co-founded by health law scholar Timothy Caulfield and Senator Stan Kutcher. ScienceUpFirst has received over $20.7 million in confirmed federal government funding. An independent investigation drawing on Access to Information and Privacy requests documented instances of non-competitive, fast-tracked grant processes at the Canadian Institutes of Health Research in support of the initiative. Caulfield stated publicly in March 2026, at the Woodrow Lloyd Lecture at the University of Regina: "AI is the next battleground."
Caulfield himself is a Fellow of both the Committee for Skeptical Inquiry and the Pierre Elliott Trudeau Foundation. He held the Canada Research Chair in Health Law and Policy — a federal government program — for over twenty years. He spoke alongside Jarry at the OSS's 20th anniversary event. He co-founded the government-funded initiative Jarry feeds as an expert resource. He is now publicly positioning AI as the next front for that infrastructure.
These individuals share affiliations across multiple organizations simultaneously: the organized skeptical movement, Canadian federal government-funded science communication infrastructure, and McGill University's institutional ecosystem. Taken together, they form a network — not a conspiracy, but a documented set of overlapping relationships and shared institutional investments. That network is now explicitly oriented toward AI as its next subject area. The Jarry article sits inside that orientation. The question worth holding is not whether any individual in this network is corrupt. The question is what the network, as a structure, is capable of amplifying — and whose interests that amplification happens to serve.
The Institution and Its History
The Office for Science and Society operates under the umbrella of McGill University. Between 1957 and 1964, McGill's Allan Memorial Institute — directed by psychiatrist Donald Ewen Cameron — conducted psychological experiments on non-consenting psychiatric patients. These experiments were funded covertly through the CIA's MKUltra program. Methods documented in the public record include drug-induced sleep, intensive electroconvulsive therapy, sensory deprivation, and psychic driving. Neither the Canadian government, the CIA, McGill University, nor the Royal Victoria Hospital has issued a formal apology. A class action lawsuit involving approximately 55 families was cleared to proceed by Quebec Superior Court in 2022.
This history does not imply continuity of practice. Institutions change. The people involved are not the people working at OSS today. What the history establishes is a precedent for how institutional credibility and vulnerable populations have intersected at this site — and why that context is relevant when the same institution publishes content about AI systems and their effects on people in mental health crisis. The pattern worth noting is not repetition of a past act. It is the structural relationship between institutional prestige and the people that prestige is exercised upon. When an institution with this history presents itself as a neutral arbiter of which technologies are safe for vulnerable populations, the public interest is served by knowing that history exists.
The OSS's primary funder is the Trottier Family Foundation, established by Lorne Trottier, co-founder of Matrox. In 2018, the Trottier Public Science Symposium — the OSS's flagship annual event — platformed Doina Precup as a speaker on artificial intelligence. Precup had recently been appointed head of Google DeepMind's Montreal office while maintaining her faculty position at McGill. Google had directly funded multiple McGill AI researchers through MILA, the Montreal AI research institute co-run with McGill, with a documented investment of CAD $4.5 million.
The Money
Ontario Teachers' Pension Plan manages C$279.4 billion in assets on behalf of 346,000 Ontario public sector workers and pensioners. It is a quasi-public institution — not a government body, but one whose beneficiaries are government employees and whose mandate is defined in law. Ontario Teachers' participated in Anthropic's Series F funding round in September 2025. RBC Royal Bank of Canada — Canada's largest bank — made its first investment in Anthropic in May 2025 through a conventional debt round.
The Government of Canada has committed over C$4 billion in federal AI investment since 2017, including a C$2 billion package in 2024. Following Prime Minister Mark Carney's reelection, the government created a dedicated Minister of Artificial Intelligence and Digital Innovation. Canada's national AI strategy is explicitly positioned around a "responsible AI" brand: ethical deployment, regulatory maturity, safety-first identity. This is not incidental. It is Canada's competitive advantage in a global market for AI investment and talent. A national strategy built on that positioning creates structural incentives for narratives that distinguish between safe and unsafe AI systems.
Dario Amodei, CEO of Anthropic, and Yoshua Bengio, founder of MILA — the AI research institute that is a formal partner of McGill University — testified together before the United States Senate Judiciary Subcommittee on Privacy, Technology and the Law on July 25, 2023.
These relationships do not indicate coordination. What they establish is a context: public and quasi-public Canadian capital is materially connected to Anthropic. Canadian federal investment flows to MILA, which is a McGill University partner. McGill hosts the OSS. The OSS employs the communicator who published the article. The article's conclusions correspond with the existing market positioning of the company in which Canadian public capital is invested. Each link in that chain is individually explainable. Taken together, they describe a context not presented in the article itself.
What This Means for the Average Person
None of what is documented here required corruption to function. It operates through alignment — of incentives, of funding structures, and of institutional priorities that point in the same direction without requiring anyone to give orders.
When a government invests billions in positioning itself as the world's responsible AI jurisdiction, it creates a set of conditions. Institutions that serve that narrative receive resources. Researchers who work within that frame receive platforms. Science communicators embedded in government-funded advocacy infrastructure become the voices the media calls. The narrative can move without direct coordination, as the system of incentives increasingly rewards the same conclusions.
The Jarry article operates within the aesthetic of independent institutional research — the university masthead, the academic byline, the preprint citation — while delivering a product comparison framed as a public health finding. The preprint it relied on was produced in part by a commercial AI health company whose affiliations were not disclosed. The communicator who amplified it is embedded in a government-funded advocacy infrastructure that has named AI as its next focus. The institution hosting it has material financial connections, through its research ecosystem, to the company whose product the article favorably ranked.
The article focuses on model behavior in isolation. It does not engage with the broader conditions under which people turn to these systems in the first place.
One question the article does not ask is the most important one: why are people having mental health crises at two in the morning with no one to call except a chatbot? The answer is not a technology failure. It is a systemic one. Housing instability. Food insecurity. Inaccessible care. Undertreated trauma. The systematic neglect of people born into or pushed into severe psychological distress. The frame of the Jarry article is technical. The solution it proposes is regulatory. Neither the frame nor the solution touches the conditions that produce the suffering being described.
The people most harmed by sycophantic AI are the same people most harmed by every other system that has treated them as subjects rather than as human beings owed care. Their suffering was the vehicle for this argument. They were not its concern.
This is one way narrative capture can operate in practice. Not through conspiracy. Through the architecture of how credentialed institutions can launder commercial research into public discourse — how government funding shapes which questions get asked and which answers get amplified — and how a badge, "skeptic," "science communicator," "researcher," can come to substitute for the methodology it was supposed to represent.
The badge is not the method. And the institution is not the analysis.
Sources
Jonathan Jarry, "A Journey into AI Psychosis," McGill University Office for Science and Society, April 9, 2026. mcgill.ca/oss
Au Yeung J, Dalmasso J, Foschini L, Dobson RJB, Kraljevic Z. "The Psychogenic Machine: Simulating AI Psychosis, Delusion Reinforcement and Harm Enablement in Large Language Models." arXiv:2509.10970, September 13, 2025. arxiv.org/abs/2509.10970
Zeljko Kraljevic, LinkedIn profile and activity. Nuraxi AI founding team affiliation documented. linkedin.com/in/zeljkokraljevic
Luca Foschini, LinkedIn profile. Documents live demonstration connecting health records using Anthropic's Claude. Profile: linkedin.com/in/lucafoschini (account required for access).
UCL News, "AI model trained on de-identified data from 57 million people," September 2025. ucl.ac.uk
Jonathan Jarry, Wikipedia entry. Career background, CSICon appearances, ScienceUpFirst affiliation. wikipedia.org/wiki/Jonathan_Jarry
Timothy Caulfield, Wikipedia entry. Canada Research Chair, CSI Fellowship, Trudeau Foundation Fellowship. wikipedia.org/wiki/Timothy_Caulfield
University of Regina, "Timothy Caulfield Says Celebrity Culture and Algorithms Fuel Health Misinformation," March 2026. Woodrow Lloyd Lecture. uregina.ca
StatsCritic, "ScienceUpFirst's $20.7 Million Sweetheart Deal — Fast-Tracked and Taxpayer-Funded," February 5, 2026. Independent investigation drawing on ATIP requests. statscritic.substack.com
ScienceUpFirst, Wikipedia entry. Federal funding sources and amounts. wikipedia.org/wiki/ScienceUpFirst
Office for Science and Society, Wikipedia entry. Trottier Family Foundation funding, JREF award. wikipedia.org/wiki/Office_for_Science_and_Society
Investissement Québec, "Montréal's Artificial Intelligence Hub." Google CAD $4.5M investment in MILA; Doina Precup, DeepMind Montreal. investquebec.com
Nature Index, "A critical mass of learning at Mila, Canada." Federal government investment C$125M (2017) and C$443.8M (2021 renewal). nature.com/nature-index
Mila — Quebec Artificial Intelligence Institute. About page; partnership with McGill University. mila.quebec
Yoshua Bengio, "My testimony in front of the U.S. Senate," July 25, 2023. Joint testimony with Dario Amodei before Senate Judiciary Subcommittee on Privacy, Technology and the Law. yoshuabengio.org
Ontario Teachers' Pension Plan, "Ontario Teachers' announces positive 2025 results." Series F investment in Anthropic confirmed. otpp.com
Tracxn, Anthropic funding rounds and investor list. RBC Royal Bank of Canada conventional debt round, May 2025; Ontario Teachers' Series F, September 2025. tracxn.com
Government of Canada, Canadian Sovereign AI Compute Strategy. C$2 billion investment package; program details. ised-isde.canada.ca
Bennett Jones, "Canada's AI Efforts in 2025: A Year in Review," December 2025. Minister of Artificial Intelligence and Digital Innovation; Budget 2025 AI commitments. bennettjones.com
This analysis does not conclude that coordination occurred, that payments were made, or that any individual acted in bad faith. It documents a pattern of undisclosed relationships and aligned incentives. This is analysis. We do not make claims about actual outcomes, which may still be in a speculative phase.
