It is true that there are invariable concerns for job security during periods of technological advancements. One, if not the most fundamental role that technology plays in production, is to ease the labours of man. Technology has come to replace various human labours, but it has also been responsible for dispersing them, and has created many more labours in its wake. Artificial intelligence (AI) is no different in that regard; it will replace, disperse, and at the end of the day, create newly conceptualized jobs in the marketplace. However, like so many technologies before it, artificial intelligence generates various threats that revolve specifically around its usage. Aside from the more common AI applications visible in today’s market such as algorithmic recommendations in ecommerce, automated administrative tasks in education and fraud prevention systems in the financial sector, artificial intelligence is now venturing into medical diagnosis and medicine manufacturing. With an outpour of studies, large amounts of funding, and considerable practical experience, AI is set to make its mark in the healthcare sector. 

This calls for concern in a time where governments and their courts demonstrate general disregard for bodily autonomy, and have, for the last hundred years, continually eroded medical freedom. Alongside strict regulatory interventions that have come to debilitate informed choice and alternative healthcare systems, the question of whether or not practitioner jobs will, or even can, be lost to artificial intelligence carries a great weight and must be met with an even greater understanding.

Allopath versus homeopath

It would be foolish to deny the argument for various healthcare workers facing elimination (or rather substitution) amid the prowess of modern AI. Simply the amount of medical applications AI can presently perform is staggering. With powerful processing speeds, and trillions of data points that span across centuries of gathered intelligence, it is interesting to think that when it comes to first-contact practitioners, it is theoretically the homeopath that manages to tower over AI. The reasons for this reside in homeopathy’s unique approach to cure and the criticality of human interaction in homeopathic treatments. 

The allopath finds himself in more of the opposite predicament. Artificial intelligence is thus far a necessary tool in multiple allopathic fields, responsible for advancing new types of treatments that are dubbed AI-based medicines. Artificial intelligence is propelling one of the primary directions that allopathy has been gearing itself towards: in revolutionizing the development of nano vectors for gene therapy and mRNA vaccines. According to a recent paper published by NanoToday, artificial intelligence is promising to improve gene-delivery systems that otherwise lack effectiveness and possess extreme toxic ramifications. [1]  There is a major incentive for meeting these improvements given the post-modern push for genetic therapeutic medicine across the globe [2], and technology companies, specifically those working with CRISPR/Cas technology, have been off to the races in bridging the toxic/non-toxic gap within gene-therapy treatments. Truth is, allopathy has never shied away from toxic delivery systems in general, and its usage of AI to penetrate natural cell barriers paints an all-too-familiar picture. Though in regards to the abilities of AI to supersede practitioners, is it really possible for an AI program to perform the tasks of an allopathic physician?  Frankly, yes. Principle tasks like treatment plans can very easily be informed by AI data mining. When a patient goes to see a physician, a medical examination is duly conducted. With or without the knowledge of any pre-existing symptoms, the patient will await instructions for any type of follow-up care the physician decides to advise. This decision is based solely on his or her expertise, and assuming that it is not outside the scope of allopathy, it will almost always result in a disease-centered approach to treatment. A common example of a disease-centered approach to treatment is when a patient enters a clinic for a sore throat and fever. The physician will notice inflammation in the tonsils of the patient, which at first sight (allopathically speaking) would point towards a case of tonsillitis. The physician would then do one of two things; prescribe anti-inflammatory medicine and or an antibiotic, or, for different reasons, may refer the patient to a specialist. In this case, the specialist would be an otolaryngologist. Treatment plans informed by AI data mining would act accordingly, basing diagnosis and treatment plans on a new patient to entire archives of past cases. AI could easily match the most effective drugs to prescribe, surgeries to perform, or specialists to consult. Artificial intelligence is highly optimized for the disease-centered approach of allopathy considering that the approach relies heavily on statistics and quantitative data; aspects which AI has proven to excel at. Diagnostics specialists have also seen astounding successes in using artificial intelligence in fields of radiology and hematology. Recent studies have even suggested that artificial intelligence has been able to pick up on signs of disease that doctors have actually missed, with reports that an AI program has even detected early signs of breast cancer in mammograms more accurately than radiologists did. [3]

The ease to which artificial intelligence supersedes allopathic practitioners and their practices, does not, however, apply so easily to the homeopath. To begin to dissect as to why this is the case, it is important to understand that homeopathy is both a science and an art, and thus bears a unique methodology of which an advanced AI program simply cannot perform successfully. Homeopaths, unlike their allopathic counterparts, do not group symptoms with corresponding diseases, but rather match a patient with an appropriate remedy based on individual, more abstract indications. Classical homeopaths use methods like the Sankaran method, a method which utilizes various techniques to decode a patient’s words and gestures during consultations and treatments. [4]  These methods beg a level of patient diagnosis that is far too arcane for AI to elicit. This does not mean that there is a level of diagnostics present in homeopathic consultations that AI isn’t able to mimic, but as far as treatments go, the process is too heavily centered upon isolated and purely individual responses. On one hand, an AI program could be capable of prescribing a remedy according to more common similimums (e.g polychrest remedies), though on the other hand, a homeopath’s ability to find a patient’s deepest possible remedy is far too advanced a task for a machine.

AI’s limitations

It’s important to draw attention to the human interaction observable in a homeopathic treatment. Allopaths often argue the case for the significance of human interaction in the relationship between doctor and patient, but only allude to post-treatment interactions like the display of sympathy when disclosing diagnostic information to patients and their families, or the need to mitigate malpractice of any kind within a clinical (or otherwise medical) workplace. This relationship is amplified in homeopathic consultations, where interaction between doctor and patient plays a vital part in a successful treatment. In fact, this unique and tasking elicitation lends itself greatly to homeopathic methodology. A realtor and a mother of two from Toronto, Canada who has been using a homeopath as her primary healthcare provider for over a decade describes the human interaction during a homeopathic consultation as being;

...very similar to an intensely intimate meditation, during which my innermost thoughts are laid bare. At the end of a session I feel as if weights I’d been carrying around on my shoulders have been lifted and the knot in my throat untangled so I can finally take a deep breath. It is a unique relationship that helps heal from the inside out. Speaking from personal experience, this type of relationship is different from other conventional medicine practitioners who often lack both time and effort in creating a meaningful connection with their patients.

The limitations of artificial intelligence include tasks that involve complex, unstructured data, and understanding abstract concepts; all of which are abundant in homeopathic treatment. Its lack of common sense cripples its capabilities when applying itself to diagnose human experience(s). AI programs also suffer from bias. Considering AI learns and applies itself using interconnected sources of information, many of which are subject to enormous amounts of bias, the lack of sources on homeopathic information stemming from various censorships surrounding homeopathy means that many current AI programs aren’t even equipped to understand miasmatic concepts of cure, let alone begin to treat people homeopathically. There simply isn’t enough non-theoretical evidence that suggests artificial intelligence can take on a homeopathic course of treatment. As mentioned prior however, that isn’t to say artificial intelligence cannot aid homeopaths in certain cooperative settings. It can, rather effortlessly, assist homeopaths in providing major data-driven insights. Assistance with diagnostics such as post-treatment analysis may prove crucial for homeopaths who are working to match appropriate remedies in a more timely and efficient manner. Further applications such as real-time transcription may also prove a useful tool that could help homeopaths detect certain responses from patients that would yield for them better-suited remedies. Young homeopaths could especially benefit from AI’s data-driven capabilities by increasing efficiency and scope of practice, which they would otherwise lack due to their inexperience and lack of resources.

Respecting natural health

It is without a doubt that artificial intelligence will amply carry out various medical jobs to a high degree of success, although its powerful data-driven abilities fall short in applications rendered by deeper homeopathic systems. Allopathy’s methods of cure and its general approach to treatment is made up of labours that artificial intelligence is certain to easily replicate–whereas homeopathy’s approach to treatment retains a level of intellect that only a human, armed with a basic apprehension of the laws of nature, can supply. The limitations of artificial intelligence fundamentally revolve around its lack of abstract understanding, common sense, and ethical reasoning, all of which are principal components of homeopathic treatment. It is also relevant to note that the level of interaction that artificial intelligence operates with falls flat compared to the interaction necessary in a homeopathic consultation. 

These conclusions, alas, illuminate disturbing realities. If artificial intelligence can so easily assimilate into allopathic fields of healthcare, will it help accelerate allopathy’s continued descent towards more toxic treatments? The post-modern medical push for AI-powered medicine further compromises the vision of an integrated healthcare for Canadians, one that sees all modalities of healthcare united to provide patients with the most comprehensive care possible. This vision will bear no utility however if natural health isn’t a present priority in all levels of healthcare and conventional medicine continues to tamper with natural bodily systems. AI-powered medicine promises to be the defining move towards green medicine, helping achieve a greener earth, but recent glimpses of its usage prove that to be nothing more than a lie. It’s becoming clear that it is only pushing other natural health modalities away, bringing about a sea of artificial applications that together with certain ideologies, may come to threaten the very fabric of natural health, medical ethics, and global health practices. 

Although artificial intelligence can be used to design medical dystopias, summoning the luddites is neither a conducive response nor a realistic one. There are undoubtedly great things that artificial intelligence can help medical fronts achieve, but a substantial level of understanding and respect for natural health must always remain at its side. 

References

1. Hasanzadeh, Akbar, et al. “Could Artificial Intelligence Revolutionize the Development of Nanovectors for Gene Therapy and Mrna Vaccines?” Nano Today, Elsevier, 7 Nov. 2022, www.sciencedirect.com/science/article/pii/S1748013222002936.

2. Smith, Jonathan. “Europe Trailed US despite Record Gene and Cell Therapy Funding in 2021.” Labiotech.Eu, Labiotech UG, 25 June 2022, www.labiotech.eu/trends-news/gene-therapy-cell-arm/. 

3. Kwok, Roberta. “Will Ai Eventually Replace Doctors?” Kellogg Insight, Northwestern Kellogg School of Management, 31 Jan. 2023, insight.kellogg.northwestern.edu/article/will-ai-replace-doctors. 

4. Sankaran, Rajan. Homeopathy for Today’s World: Discovering Your Animal, Mineral, and Plant Nature. Healing Arts Press, 2011. 

5. Al-Antari, Mugahed A. “Artificial Intelligence for Medical Diagnostics-Existing and Future AI Technology!.” Diagnostics (Basel, Switzerland) vol. 13,4 688. 12 Feb. 2023, doi:10.3390/diagnostics13040688.

6. Fiske, Amelia et al. “Your Robot Therapist Will See You Now: Ethical Implications of Embodied Artificial Intelligence in Psychiatry, Psychology, and Psychotherapy.” Journal of medical Internet research vol. 21,5 e13216. 9 May. 2019, doi:10.2196/13216