Inappropriate Use of AI!

There is a blatantly obvious move towards the promotion of AI as the solution to all of our problems; a move that I find rather disturbing, which is putting it mildly.

I must emphasise that I am not against technology, after all, I’m using it to write and publish this article and communicate it to you. Also, I absolutely acknowledge that AI can perform certain tasks far more quickly than humans and that this can be useful in some applications. My concern is when AI is being applied inappropriately, which is the case when it is used within the field of modern medicine, and especially within medical research. The reason is because the system of ‘healthcare’ known as modern medicine is based on a fundamentally flawed understanding of health, disease, and the human body.

The point I’m making here can be demonstrated by the type of claim reported by the 20th February 2025 BBC article, AI cracks superbug problem in two days that took scientists years, that begins,

“A complex problem that took microbiologists a decade to get to the bottom of has been solved in just two days by a new artificial intelligence (AI) tool.”

The alleged ‘problem’ referred to in the article involves discovering the reason that some ‘superbugs’ appear to be immune to antibiotics, as the article states,

“Their hypothesis is that the superbugs can form a tail from different viruses which allows them to spread between species.”

And this is a perfect example of where AI has been used inappropriately, because the whole premise for which AI was used to find a solution is based on the ‘germ theory’, a theory that remains unproven. What is also unproven is the idea that ‘viruses’ exist as described.

Even though AI is claimed to have generated a similar solution to that of the scientists with respect to the ‘problem’, the input data would have been flawed. The data they supplied to AI would not have represented the true nature of bacteria and their real role within the human body, so the AI system would not have been solving a genuine ‘problem’, despite the speed with which it produced a solution. Bacteria are not fundamentally harmful. In fact, their role is fundamentally beneficial. And yes, they can become resistant to antibiotics, I am not denying that. What I am refuting is the notion that they need to be killed by antibiotics in the first place.

This is by no means the first foray by the BBC into promoting the wonders of AI and its uses within the health system. Within their 20th February article is a link to another BBC article, dated 10th January 2025, entitled How AI uncovers new ways to tackle difficult diseases, which is described as the 4th in a 6-part series that is reported to be,

“…looking at how AI is changing medical research and treatments.”

This article refers to Dr Alex Zhavoronkov, the co-founder and CEO of US-based start-up Insilico Medicine, with respect to a new pill that he and his company have produced with the help of AI; the article states,

“It has been developed by his company to treat a rare progressive lung disease for which there is no known cause or cure.”

It should be noted that, as of the date of the article, the drug had not yet been approved.

The ‘disease’ for which this pill is claimed to have shown ‘impressive efficacy’ is known as idiopathic pulmonary fibrosis (IPF).

NB Idiopathic means that the cause is unknown.

The article states that this drug is,

“…one of a new wave of drugs where artificial intelligence (AI) has been integral to its discovery.”

The key point here is the use of AI in the process of drug design, the idea being that AI can help to speed up some aspects of the drug design process. At the moment, AI does not appear to be working alone - although that may happen at a later stage - currently, it is simply assisting the process. The reasons given for incorporating AI into the various processes are based on time and costs, as the article explains,

“Using AI to do drug discovery could make an "enormous difference" for patients, says Chris Meier, of the Boston Consulting Group (BCG).

“Bringing a new drug to market takes on average 10 to 15 years, and costs more than $2bn (£1.6bn).

The key issue, for any drug developer, is that there is no guarantee that the drug will succeed in clinical trials, because, as the article states,

“…about 90% of drugs that go into clinical trials fail.”

This failure rate is highly significant; it’s a rate that the pharmaceutical industry will be keen to reduce - substantially - for obvious reasons!

The main reason they ‘fail’, however, as far as I’m concerned, is because they do not address the real causes of health issues, and therefore cannot be successful, although that is not how medical researchers would interpret their failure.

It is claimed that AI can assist with some of the steps in the ‘drug discovery’ process and specifically in 2 of the steps, as the article explains,

“The first is in identifying, at the molecular level, the therapeutic target that it is intended the drug will act to correct, such as a certain gene or protein being altered by the disease in a way it shouldn’t."

This statement alone highlights the fundamental problem with the concept of ‘disease’ held by modern medicine; the concept on which all drug use is based. The problem is that it is basically a false concept, because it does not represent an accurate explanation of the ‘disease’ process within the human body.

The second step relies heavily on the same false concept on which the first step is based because it involves the design of ‘drugs’ to correct the claimed disease target,

“This employs generative AI, also the basis of ChatGPT, to imagine molecules that might bind to the target and work, replacing the expensive manual process of chemists synthesising many hundreds of variations of the same molecule and trying them to find the optimal one.”

The ‘imagining’ of molecules that ‘might’ bind to targets that ‘might’ be the optimal one bears little resemblance to science. Most researchers have become little more than technicians, as Dr Peter Duesberg explains in Inventing the AIDS Virus,

“The transition from small to big to mega-science has created an establishment of skilled technicians but mediocre scientists, who have abandoned real scientific interpretation and who even equate their experiments with science itself.”

The use of AI in the process will not alter this fact.

Furthermore, the drug being produced to treat IPF,

“…was designed by the company's generative AI software after it was given the objective of inhibiting a protein called TNIK, which has never been targeted before for treating IPF, but was suggested by another set of the company's AI software as the most likely regulator of the disease.”

Again, note the use of the phrase ‘most likely’.

The third article in the 6-part series, dated 20th December 2024, is AI is trained to spot warning signs in blood tests. This article is mainly about ovarian cancer, however, it also states that,

“For a cancer patient, catching pneumonia can be deadly and, as there are around 600 different organisms that can cause pneumonia, doctors have to conduct multiple tests to identify the infection.”

It is claimed that AI can speed up the process of finding the ‘right pathogen’. This is yet another reason to highlight the unproven nature of the ‘germ theory’, because searching for the ‘right pathogen’ is a fruitless pursuit.

The 6th and final article in the series, dated 17th January 2025, is How AI can spot diseases that doctors aren't looking for.

The underlying assumption of modern medicine is that there are hundreds if not thousands of distinctly different disease entities, but this is an unproven assumption.

People do experience different symptoms, and even many different combinations of symptoms, but that does not ‘prove’ that there are many hundreds or thousands of different diseases as claimed.

This notion highlights yet another key problem within modern medicine; the idea that symptoms in one part of the body represent a distinct ‘disease’ located within that part, and nowhere else. And that symptoms in a different part of the body represent a completely different ‘disease’.

The human body is a whole organism in which all parts are intimately interconnected. A health issue in one ‘part’ almost certainly indicates a systemic issue, but modern medicine does not view the body in this way; its view is not holistic. Instead, modern medicine takes a reductionist view that merely considers ever smaller ‘parts’ of the body with a view to fixing each part separately. It also holds the view, as shown by the article, that individual molecules can be ‘targeted’ by drugs to ‘fix’ the health problem.

The consequences of this incorrect view of the body can be seen in the case cited within the above-cited BBC article of Will Studholme, a 58-year-old man, who had gastrointestinal problems,

“It turned out that Mr Studholme had a severe case of food poisoning, but early in his ailment's investigation, he received an abdominal CT scan.”

The article continues,

“That scan was then later run through artificial intelligence (AI) technology which identified a collapsed vertebra in Mr Studholme's spine, a common early indicator of osteoporosis.”

Although it may be perceived that the scan was useful because it ‘found’ his osteoporosis, this misses the real issue, which is that this patient had a systemic problem - he did not have different diseases.

I would also point out that CT scans are not exactly harmless, as can be seen by an article entitled X-Ray vs. CT vs. MRI, which states,

“A CT scan generates high-quality, detailed images of the body. It’s a more powerful and sophisticated x-ray that takes a 360-degree image of the spine, vertebrae and internal organs. You may have a contrast dye injected into your blood so the doctor can see your body structures more clearly on the CT scan.”

These are the questions I would ask: What are the possible adverse effects of the CT scan? Could a scan have an impact on health? Could it contribute to subsequent health issues?

It is claimed in the BBC article that additional issues may be found during the course of routine ‘tests’,

“It isn't unheard of that a radiologist might note something incidental in a patient's imaging – an undetected tumour, a concern with a particular tissue or organ – outside of what they had originally been checking for.”

This is where AI is said to be of huge benefit because it is able to assist the process of ‘finding’ something else within the body that may need attention, according to the mainstream medical model, although this is not yet part of normal procedures.

“But applying AI in the background to systematically comb through scans and automatically identify early signs of common preventable chronic diseases that might be brewing – regardless of the reason the scan was originally ordered – is new.”

Although ‘new’, I wonder if it is envisioned that this use of AI to ‘detect’ other problems may become part of ‘standard procedure’ when viewing tests of different kinds.

I absolutely acknowledge that many people feel a sense of comfort when they are given a label for their condition; often because it helps them feel recognised that they have a real health issue.

But this is where my views diverge, because the label will not help them recover their health. Instead, the approach of modern medicine will be to offer them some form of treatment based on an idea that the chemical in the drug will target the appropriate molecule and ‘fix’ the problem.

Apart from the fact that we do not have health problems because we experience a lack of petrochemical-based products in our bodies, and therefore cannot heal as the result of the use of any petrochemical-based product, this view completely omits one of the most potent aspects of being human; our mind. The role of the mind is a key aspect that is almost always omitted by those within the allopathic system. They utterly fail to take account of the existence and impact on our health of our emotions/beliefs/ideas; a topic that I will return to in later writings, although I have covered this to some extent in previous articles.

I would also add that, although our bodies are comprised of chemicals, we are not merely a chemical-based body, we are also electrical beings and this too is largely ignored by the mainstream medical system.

As always, it is important to understand that the mainstream medical system is flawed; but bringing in AI to ‘solve’ problems is NOT going to help people understand their health problems and restore their bodies to homeostasis and therefore to health.

AI does have its uses - but it needs to be implemented only where it really can be useful, which is not within a ‘healthcare’ system that does not understand health.

This is not the first time I’ve tackled the issue of AI in healthcare, here’s my previous article on the topic,