ChatGPT believes a fake disease was real and diagnoses millions of people as having the disease.
Many parallels with M2C and the Interpreter.
We can all see that RLDS author L.E. Hills invented M2C with his 1917 map and commentary.
One way to understand M2C is to view it as a joke L.E. Hills played, or maybe just a thought experiment.
At the time, Joseph Fielding Smith called it out as false and contrary to the teachings of the Church for a hundred years.
But certain LDS scholars picked up M2C from Hills and ran with it.
And just like ChatGPT, the M2Cers find "evidence" of M2C everywhere.
The rest of us observe the obvious: the M2Cers are merely confirming their biases.
As we've seen in the latest Brant Gardner video, the M2Cers pretend to rely on the text of the Book of Mormon but they continuously add "texture" and "nuance" to make it fit Mesoamerica. Most readers observe that the text does not mention volcanoes, or jungles, jaguars and jade, or even a large indigenous population that "absorbed" the Nephites and inexplicably made Nephi a king instead of just killing the new arrivals. The M2Cers use the Sorenson translation because they believe Joseph Smith didn't translate it correctly, which is consistent with their overall theory that they understand the book better than Joseph or Oliver ever did.
By now, M2C is the only "truth" allowed at the Interpreter. All the Interpreters have completely rejected and repudiated what Oliver Cowdery, Joseph Smith, and their contemporaries and successors have taught about Cumorah/Ramah.
_____
ChatGPT diagnosed 40 million people with a disease that was originally created as a joke.
Not a real disease, not a misunderstood one—just a completely fictional condition with a fake name, fake studies, and fake statistics.
And it told patients to see a specialist.
The disease is called Bixonimania. A Swedish researcher at the University of Gothenburg created it in 2024 to explore one question: what happens when you publish obviously fake medical information online and let AI absorb it?
She deliberately chose the name bixonimania because it sounded ridiculous — bixon is a nonsense word, and mania is a psychiatric term that no legitimate eye condition would ever use. She uploaded two papers to a preprint server. Both were obviously fraudulent. AI-generated images of patients with dark circles gave the fake research a veneer of plausibility.
Then she waited.
She did not have to wait long.
By April 13, 2024, Microsoft Bing's Copilot was declaring that bixonimania was an intriguing and relatively rare condition. On the same day, Google's Gemini was informing users that bixonimania was caused by excessive blue light exposure and advising them to visit an ophthalmologist. Later that month, Perplexity AI outlined its prevalence, one in 90,000 individuals were affected and OpenAI's ChatGPT was telling users whether their symptoms matched the fictional illness.
One in 90,000. A precise statistic. For a disease that does not exist.
Every red flag was visible. The name was absurd. The papers were crude. The condition made no scientific sense. None of the AI systems flagged any of it.
They read the fake papers. They absorbed the fake statistics. They presented both to patients with clinical authority and zero hesitation.
Then it got worse.
Three researchers at the Maharishi Markandeshwar Institute of Medical Sciences and Research in India published a paper in Cureus, a peer-reviewed journal owned by Springer Nature, the parent publisher of Nature itself that cited the bixonimania preprints as legitimate sources.
A real peer-reviewed paper. In a Springer Nature journal. Citing a fictional disease as established medical fact. Passing editorial review. Entering the permanent scientific record.
It was only retracted after the hoax became public.
Nature published a full investigation of the experiment. Alex Ruani, a health-misinformation researcher at University College London, called it a masterclass in how misinformation operates.
Here is the scale of what this means.
More than 40 million people turn to ChatGPT every day for health information, according to OpenAI's own analysis. ECRI, a US patient-safety nonprofit has named chatbot misuse the number-one health technology hazard of 2026. ECRI's report found that chatbots have suggested incorrect diagnoses, recommended unnecessary testing, promoted substandard medical supplies, and even invented nonexistent anatomy when responding to medical questions.
Number one. Out of every health technology hazard that exists in 2026.
An April 2026 study published in BMJ Open found that nearly half of the answers provided by leading AI chatbots to common health questions contain misleading or problematic information.
Nearly half. Of all health answers. From the tools 40 million people use every day.
Here is the line from the researcher that cuts through everything.
The Bixonimania case is striking precisely because it was engineered to be so obviously fake. The real question it raises is: what is passing through the same systems that is not nearly so easy to spot?
The experiment used a ridiculous name. Fraudulent papers. Visible red flags at every level.
It was designed to be caught.
It was not caught.
The AI that told patients about Bixonimania is the same AI they asked about their chest pain, their medication, their child's symptoms, and their cancer screening schedule.
40 million people. Every day.
And nobody is telling them that nearly half of what comes back may be wrong.
Source: Osmanovic Thunström · University of Gothenburg · Nature · April 2026 ·
Link in the (comments)
https://x.com/primemans/status/2059660243186196609?s=20
No comments:
Post a Comment