AI Problem in Canada? Do American AI Outfits Care?
May 26, 2026
AI is supposed to make jobs easier and supposedly more accurate. That is not what is happening in Ontario, Canada. Ontario healthcare professionals rely on AI to take notes, but it is all bungled up says The Register article, “Sick And Wrong: Ontario Auditors Find Doctors’ AI Note Takers Routinely Blow Basic Facts.”
AI missed key details, inserted incorrectly information, and hallucinated content that no one mentioned. Not health care providers. Not the patients. This was discovered by a provincial audit that examined twenty approved systems.
The audit was conducted by the Office of the Auditor General of Ontario, Canada and was published in a larger report about AI usage by public services within the province. The report focused mainly on AI Scribe, the program used by the Ontario Ministry of Heath’s medical practitioners.
To evaluate the AI, simulated doctor-patient recordings were used. Medical experts then reviewed the AI-generated notes for accuracy. The results were shocking:
“Nine out of 20 AI systems reportedly “fabricated information and made suggestions to patients’ treatment plans” that weren’t discussed in the recordings. According to the report, evaluators spotted potentially devastating incorrect information in the sample reports, such as no masses being found, or patients being anxious, even though these things were never discussed in the recordings.
Twelve of the 20 systems evaluated inserted incorrect drug information into patient notes, while 17 of the systems “missed key details about the patients’ mental health issues” that were discussed in the recordings. Six of the systems “missed the patients’ mental health issues fully or partially or were missing key details,” per the report.”
The AI tools that were evaluated are used by doctors, nurses, and other medical professionals. They are used to make diagnoses, summarizer patient care, and more. The AI could produce biased, inaccurate medical records that place patients and medical practitioners in danger.
Do American BAIT (big AI tech) companies care?
Whitney Grace, May 26, 2026
Happy Friday Information: Death Risk News
March 27, 2026
Another dinobaby post. No AI unless it is an image. This dinobaby is not Grandma Moses, just Grandpa Arnold.
March has been an interesting month. Amazon Web Services fail over technology failed. But missile strikes are not something with which the two pizza teams had much familiarity. Now it’s a different story. The ensemble of estimable companies found themselves on the wrong side of social media addiction lawsuit. Let the appeals begin, but the decision is not going to boost the trust score in the European Union for US companies. Plus, there is some economic uncertainty forcing some seniors to decide, “Do I buy food or medicine this month?” There is vanlife, of course.
But for Friday, March 27, 2026, I want to present an even more uplifting item of allegedly true information. I know I believe everything I read on the Internet, and I assume you are even more rigorous in your information vetting than I. However, I found Science Daily’s “This Dangerous Combo in Your Body Could Raise Death Risk by 83%.”
Several click baity points. I like the idea of a “dangerous combo.” You put two things together and you may as well start coffin shopping now. Your “death risk” spikes. The odds are not quite twice as likely. The odds are only 1.83 percent. I keep remembering that everyone has a 100 percent chance of dying. But I think the point is that you will definitely or at least 1.83 percent change of heading to the quantum beyond faster. Speed is good in today’s high tech world, but speed in flopping over is a negative.
What’s Science News say? I noted this statement:
both excess abdominal fat and reduced muscle mass significantly raises the risk of death. People with this combination were 83% more likely to die than those without either condition.
Shocker. Who knew that being overweight in the tummy area and failing to exercise would shorten one’s life? Quite a scientific insight, is it not?
The write up points out:
simple methods can be used to detect sarcopenic obesity.
I think I understand. Look at a person. Big tummy and not much walking, paddle tennis, or competitive weight lifting signal a problem and put the observer on alert for trouble ahead.
True to modern science and diagnostic code chains, one does not just look at a person and say, “Put down that burger and hit the gym.” Nope. The article reports:
Diagnosing sarcopenic obesity usually requires advanced imaging tools such as magnetic resonance imaging, computed tomography, electrical bioimpedance, or densitometry…. but they are expensive…
Yes, they are, and that is the entire point of using advanced technology when common sense provides equivalent insight about a person.
Here’s the shocker. The authors of the paper don’t want to do the DRG billing trick that rolled up hospitals favor. The write up says:
… the team used practical criteria to identify those at risk. Abdominal obesity was defined as a waist circumference greater than 102 centimeters for men and 88 centimeters for women. Low muscle mass was defined as a skeletal muscle mass index below 9.36 kg/m2 for men and below 6.73 kg/m2 for women.
The approach may work in Campinas, Brazil, a city in which we lived. But in the US? I am not so sure. Why? Learn more about health care billing and those nifty DRG chains. It’s a fun subject. Be aware that some of the documentation about the organizations chasing this issue is no longer available on certain US government public facing Web sites.
Net net: It’s NCAA basketball time. Kick back. Eat those cheese drenched nachos. Have a beverage. Change that behavior after the games. Monday for sure. If you think about 1.83 angle, the bad news is that it may be too late if one is over 22 years old.
Stephen E Arnold, March 27, 2026
SPACtacular Palantir Tech Gets More Attention: This Is Good?
June 30, 2021
Palantir is working to expand its public-private partnership operations beyond security into the healthcare field. Some say the company has fallen short in its efforts to peddle security software to officials in Europe, so the data-rich field of government-managed healthcare is the next logical step. Apparently the pandemic gave Palantir the opening it was looking for, paving the way for a deal it made with the UK’s National Health Service to develop the NHS COVID-19 Data Store. Now however, CNBC reports, “Campaign Launches to Try to Force Palantir Out of Britain’s NHS.” Reporter Sam L. Shead states that more than 50 organizations, led by tech-justice nonprofit Foxglove, are protesting Palantir’s involvement. We learn:
“The Covid-19 Data Store project, which involves Palantir’s Foundry data management platform, began in March 2020 alongside other tech giants as the government tried to slow the spread of the virus across the U.K. It was sold as a short-term effort to predict how best to deploy resources to deal with the pandemic. The contract was quietly extended in December, when the NHS and Palantir signed a £23 million ($34 million) two-year deal that allows the company to continue its work until December 2022. The NHS was sued by political website openDemocracy in February over the contract extension. ‘December’s new, two-year contract reaches far beyond Covid: to Brexit, general business planning and much more,’ the group said. The NHS contract allows Palantir to help manage the data lake, which contains everybody’s health data for pandemic purposes. ‘The reality is, sad to say, all this whiz-bang data integration didn’t stop the United Kingdom having one of the worst death tolls in the Western world,’ said [Foxglove co-founder Cori] Crider. ‘This kind of techno solutionism is not necessarily the best way of making an NHS sustainable for the long haul.’”
Not surprisingly, privacy is the advocacy groups’ main concern. The very personal data used in the project is not being truly anonymized—instead it is being “pseudo-anonymized,” a reversible process where an alias is swapped out for identifying information. Both the NHS and Palantir assure citizens re-identification will only be performed if necessary, and that the company has no interest in the patient data itself. In fact, we are told, that data remains the property of NHS and Palantir can only do so much with it. Those protesting the project, though, understand that money can talk louder than corporate promises; many companies would offer much for the opportunity to monetize that data.
Cynthia Murrell, June 30, 2021
Will More Big Data Make AI Deliver Results
April 6, 2020
Many companies have issued news releases about their coronavirus research support. Personally I find the majority of these “real news” announcements low ball marketing at its finest. The coronavirus problem is indeed serious, and researchers, art history majors, and MBA executives who hop on the “We are helping” bandwagon are amusing.
I read a 3,500 ZDNet article titled:
AI Runs Smack Up Against a Big Data Problem in COVID-19 Diagnosis. Researchers around the world have quickly pulled together combinations of neural networks that show real promise in diagnosing COVID-19 from chest X-rays and CT scans. But a lack of data is hampering the ability of many efforts to move forward. Some kind of global data sharing may be the answer.
Now that’s an SEO inspired title, but the write up makes one amazing assertion: More data will allow medical AI systems to output actionable information.
If I run through the litany of medical AI revolutions, my fingers would get tired clicking and mousing. The IBM Watson silliness is a good example, and it encapsulates the problem of using collections of numerical recipes to help physicians deal with cancer. Google has not made much, if any, progress on solving death. Remember that “hard problem.” Pushing deeper into the past there was NuTech Solutions’ ability to identify individuals likely to get diabetes based on sparse data and ant algorithms.
How did these companies’ efforts work out?
Failures from my point of view.
The write up runs down a number of research efforts. Companies like DarwinAI are mentioned. There are quotes which provide guidance to organizations challenged to find the snack room; for example:
“I think it would help if the WHO made a central database with de-identifying mechanisms, and some really good encryption,” said Dr. Luccioni. “That way, local health authorities would be reassured and motivated to share their data with each other.”
The problem is that smart software is mostly implementation of methods known in some cases for hundreds of years. These smart systems use recursion, feedback loops, and statistical procedures to output statistically valid (probable) information.
How are these systems working? There are data, but they are conflicting, disorganized, and inconsistent. News flash. That’s how information is. There is zero evidence that more data can be verified, normalized, processed in near real time to allow smart software to demonstrate it can do more than generate marketing collateral.
The companies pitching their artificial intelligence should articulate the reality of the outputs their workflows of algorithms can actually generate.
That might help more than the craziness of wanting data to be better, having some magic wand to normalize the messy real world of information, and converting what are mostly graduate school projects into something useful beyond speeding up some lab tests and getting a “real” job.
Will this happen? Not for a long time. Data are not the problem. Humans are the problem because the idea of creating a consistent, verified repository of on point data has not been achieved for small domains of content. Forget global data.
Don’t believe me. Check out any online system. Run some queries. Is “everything” in that system or federated system? What about a small collection of data; for example, the data on your mobile? What’s there that you can access? “What?” you ask. Yeah, the high value data are sucked away and those data are not shared with “everyone” including you who created the data in the first place.
Smart software performs some useful functions. Will data make Bayesian methods or patented techniques like those from Qure.ai “solve” Covid?
Hard in reality. Easy in ZDNet articles. Even easier for marketers. And the patients suffering? What? Who? Where?
Exactly.
Stephen E Arnold, April 5, 2020
Health Care: Data an Issue
June 28, 2018
Healthcare analytics is helping doctors and patients make decisions in ways we never could have dreamed. From helping keep your heart healthy to deciding when to have major surgery, analytic numbers make a big impact. However, that data needs to be perfect in order to work, according a recent ZD Net story, “Google AI is Very Good at Predicting When a Patient is Going to Die.”
According to the story:
“As noted, 80 percent of the effort in creating an analytic model is in cleaning the data, so it could provide a way to scale up predictive models, assuming the data is available to mine…. “This technique would allow clinicians to check whether a prediction is based on credible facts and address concerns about so-called ‘black-box’ methods that don’t explain why a prediction has been made.”
This really illustrates how powerful clean data can be in the health field. However, cleaning data is just about the most misunderstood wallflower in the often tedious world of machine learning and data science—not just in healthcare. According to Entrepreneur magazine, the act of filling in blanks, removing outliers, and basically looking at all the data to make sure it will be accurate, is the most important part of the process and also the hardest role to fill on a team.
Garbage in, garbage out. True decades ago. True today. How do we know? Just ask one of IBM Watson’s former health care specialists. Querying patients who were on the wrong end of a smart output may be helpful as well.
Patrick Roland, June 28, 2018
Google and AI Digital Shrooms
March 30, 2018
Magic mushrooms are a delightful way to experience reality as well as hurt your body and become addicted to drugs. They were a big symbol of the 1960s-70s counterculture. Beyond their hallucinogenic properties, medical experts discovered they have medicinal uses too. Mushroom enthusiast loves the mold, but there might be a way for them to trip without breaking any laws. The International Business Times reported that “Hallucination Machine Uses Google AI, Gives Magic Mushroom-Like ‘Trip’ Without Drugs.”
The possibilities of virtual reality have been imagined for years, but only now can we fully begin to explore the possibilities. One way researchers are testing virtual reality is with the Hallucination Machine, built on Google AI and uses a virtual reality headset. The Hallucination Machine allows users to “trip” without the drugs’ harmful effects. Scientists are fascinated with hallucinations and hallucinogens because they love to study the brain’s processes when it “trips out.”
Sussex University’s Sackler Centre for Consciousness Science published a paper in the Scientific Reports journal discussing how the Hallucination Machine compares to real drug-induced hallucinations.
Hallucinations help scientists focus their study on areas of the brain that are affected when there is an altered reality. Using hallucinogens alters the chemical composition of the brain, which makes it hard to isolate just the visual effects. So the team used Google’s DeepDream system, which uses a neural network approach to try and identify patterns and features in images. You can actually try it out for yourself online. DeepDream works by creating patterns and over emphasizing on certain recurring details that helps put our brain into perception overdrive, so much so that it starts to imagine stuff that isn’t actually there.
The Sackler Center conducted two tests. The first exposed participants to DeepDream and users experienced hallucinations similar to those caused by magic mushrooms. The second tested participants’ time perception, but the Hallucination Machine cannot recreate that psychedelic experience yet.
Replicating the magic mushroom’s tripping experience is still in the development phases, but give it a few more years and this will probably be a popular virtual reality program.
Whitney Grace, March 30, 2018
AI Makes Life-Saving Medical Advances
January 2, 2018
Too often we discuss the grey area around AI and machine learning. While that is incredibly important during this time, it is also not all this amazing technology can do. Saving lives, for instance. We learned a little more on that front from a recent Digital Journal story, “Algorithm Repairs Corrupted Digital Images.”
According to the story:
University of Maryland researchers have devised a technique exploits the power of artificial neural networks to tackle multiple types of flaws and degradations in a single image in one go.
The researchers achieved image correction through the use of a new algorithm. The algorithm operates artificial neural networks simultaneously, so that the networks apply a range of different fixes to corrupted digital images. The algorithm was tested on thousands of damage digital images, some with severe degradations. The algorithm was able to repair the damage and return each image to its original state.
The application of such technology crosses the business and consumer divide, taking in everything from everyday camera snapshots to lifesaving medical scans. The types of faults digital images can develop include blurriness, grainy noise, missing pixels and color corruption.
Very promising from a commercial and medical standpoint. Especially, the medical side. This news, coupled with the story in Forbes about AI disrupting healthcare norms in 2018 makes for a big promise. We are looking forward to seeing what the new year brings for medical AI.
Patrick Roland, January 2, 2018
Watson and CDC Research Blockchain
December 29, 2017
Oh, Watson! What will IBM have you do next? Apparently, you will team up with the Centers for Disease Control and Prevention to research blockchain benefits. The details about Watson’s newest career are detailed in Fast Company’s article, “IBM Watson Health Team With the CDC To Research Blockchain.” Teaming up with the CDC is an extension of the work IBM Watson is already doing with the Food and Drug Administration by exploring owned-mediated data exchange with blockchain.
IBM chief science officer Shahram Ebadollahi explained that the research with the CDC and FDA with lead to blockchain adoption at the federal government level. By using blockchain, the CDC hopes to discover new ways to use data and expedite federal reactions to health threats.
Blockchain is a very new technology developed to handle sensitive data and cryptocurrency transactions. It is used for applications that require high levels of security. Ebadollahi said:
‘Blockchain is very useful when there are so many actors in the system,’ Ebadollahi said. ‘It enables the ecosystem of data in healthcare to have more fluidity, and AI allows us to extract insights from the data. Everybody talks about Big Data in healthcare but I think the more important thing is Long Data.’
One possible result is that consumers will purchase a personal health care system like a home security system. Blockchain could potentially offer a new level of security that everyone from patients to physicians is comfortable with.
Blockchain is basically big data, except it is a more specific data type. The applications are the same and it will revolutionize the world just like big data.
Whitney Grace, December 29, 2017
Humans Living Longer but Life Quality Suffers
December 28, 2017
Here is an article that offers some thoughts worth pondering. The Daily Herald published, “Study: Americans Are Retiring Later, Dying Sooner And Sicker In Between”. It takes a look at how Americans are forced to retire at later ages than their parents because the retirement age keeps getting pushed up. Since retirement is being put off, it allows people to ideally store away more finances for their eventual retirement. The problem, however, is that retirees are not able to enjoy themselves in their golden years, instead, they are forced to continue working in some capacity or deal with health problems.
Despite being one of the world’s richest countries and having some of the best healthcare, Americans’ health has deteriorated in the past decade. Here are some neighbors to make you cringe:
University of Michigan economists HwaJung Choi and Robert Schoeni used survey data to compare middle-age Americans’ health. A key measure is whether people have trouble with an “activity of daily living,” or ADL, such as walking across a room, dressing and bathing themselves, eating, or getting in or out of bed. The study showed the number of middle-age Americans with ADL limitations has jumped: 12.5 percent of Americans at the current retirement age of 66 had an ADL limitation in their late 50s, up from 8.8 percent for people with a retirement age of 65.
Also, Americans’ brains are rotting with an 11 percent increase in dementia and other cognitive declines in people from 58-60 years old. Researchers are not quite sure what is causing the decline in health, but they, of course, have a lot of speculation. These include alcohol abuse, suicide, drug overdoses, and, the current favorite, increased obesity.
The real answer is multiple factors, such as genes, lifestyle, stress, environment, and diet. All of these things come into play. Despite poor health quality, we can count on more medical technological advances in the future. The aging population maybe the test grounds and improve the golden years of their grandchildren.
Whitney Grace, December 28, 2017
Silicon Valley Has the Secret to Eternal Life
December 27, 2017
Walt Disney envisioned his namesake park, Walt Disney World, to be a blueprint for the city of the future. Disney was a keen futurist and was interested in new technology that could improve his studios and theme parks. His futuristic tendencies led to the urban legend that he was cryogenically frozen and will one day be revived. Disney wasn’t put on the ice, but his futuristic visions are carried out by Silicon Valley technologists seeking immortality. Quartz reports on the key to eternal life in the article, “Seeking Eternal Life, Silicon Valley Is Solving For Death.”
Death is the ultimate problem that has yet to be solved. Many in Silicon Valley, including Oracle’s Larry Ellison, are searching for a solution to prolong life with anti-aging research. Bill Maris convinced Alphabet’s Larry Page and Sergey Brin to start Calico, Google’s billion-dollar effort to cure aging. Also, cryogenics remains popular:
Other denizens of the valley pursue cryogenics or cryonics, which is the process of freezing oneself in a vat of liquid nitrogen soon after death. They do this in the hope that it will suspend them in time, preserving them for a future when science can bring them back to life. There are about 350 people already frozen worldwide with another 2,000 signed up—but yet to die.
Medical breakthroughs have already extended the US lifespan and that of other developed nations. Developing nations still have short lifespans and it draws the conclusion that wealthier people will live forever, while the poor ie quicker. It is questionable that the extra years tacked onto people’s lives are really worth it because many people spend them unable to care for themselves or in pain.
The article spins into current anti-aging research, then into philosophy about humans vs. machines and what makes a person a person. Throw in some science-fiction and that is the article in short.
Whitney Grace, December 27, 2017
-
- Subscribe to Beyond Search
Feature archive
News archive
-
