While the last few decades have been marked by rapid technological and cultural changes, some dreams still remain part of the popular imagination. How many times have we heard the famous phrase, “my child the doctor”?
Florencio Sánchez, an Uruguayan playwright, depicted the clash of ideas and values within a rural family at the beginning of the last century after they sent their son to the city to earn a university degree in medicine.
A study published in 2011 (Cyranoski et al.)[56] in the journal Nature, noted that in the countries of the Organisation for Economic Co-operation and Development (OECD), the number of doctors, referring to academic and scientific professionals with postgraduate degrees, not medical or legal professionals who sometimes adopt this title without justification, grew by 40% between 1998 and 2008. This has led, in some cases, to an oversupply, leaving many to work in positions where their extensive education is not adequately reflected.
Returning to the field of medicine, it is worth noting that in recent years, magnificent AI tools for medical diagnosis have been developed. Some of these are on par with the diagnoses of professional doctors, able to detect specific diseases like pneumonia through X-ray images or skin cancer by analyzing a series of photos.
Let’s analyze how we obtain our medical diagnoses today. We visit a healthcare professional who, after conducting various tests on our body, proceeds to give their opinion on our condition. This is possible because this person likely enjoyed good nutrition at birth, properly developed their cognitive abilities, then attended university where they studied and passed numerous exams, and finally began working in the real world, applying the previously learned theory and honing their diagnoses through continuous practice.
The problem with this model is that knowledge is confined to the minds of very few people. No matter how renowned and talented they are, they are still human beings with imperfect memories and very limited time to stay updated on the latest scientific advancements, as Kai-Fu Lee, author of AI Super-powers, China, Silicon Valley and the New World Order, points out. As these words are being written, the company DeepMind, now owned by Alphabet -Google, continues to work on eye disease recognition, having already demonstrated high levels of effectiveness comparable to professional assessments since 2018. While no healthcare professional can stay updated on all advancements daily, an AI dedicated to medicine could update its database, and thus its knowledge, in seconds, incorporating new studies and discoveries daily. Moreover, all current doctors graduated before we fully sequenced the human genome[57]. In recent years, AlphaFold, another creation of DeepMind used by millions of researchers worldwide[58], has provided the infrastructure to predict the structure of over 200 million proteins, crucial for understanding our biology and fighting various diseases.
To make it clear once again, we must understand that if the World Health Organization identifies a new disease, or a new cure for a disease hits the market, it is impossible to impart that knowledge to all medical personnel worldwide simultaneously. Sending them the information is easy, ensuring they study and incorporate it is another matter. Conversely, we could update our AI program’s database in just a few minutes and ensure that all new diagnoses consider the latest available information. It doesn’t make sense to compare ourselves to a computer and try to learn faster than they do; it simply isn’t possible.
[56] Cyranoski, D., Gilbert, N., Ledford, H., Nayar, A., & Yahia, M. (2011). Education: The PhD factory. Nature. Retrieved June 28, 2021, from https://www.nature.com/articles/472276a.
[57] Pennisi, E. (2022). Most complete human genome yet reveals previously indecipherable DNA. Science.org. Retrieved April 11, 2022, from https://www.science.org/content/article/most-complete-human-genome-yet-reveals-previously-indecipherable-dna.
[58] European Bioinformatics Institute. (2023). Case study: AlphaFold uses open data and AI to discover the 3D protein universe. Ebi.ac.uk. Retrieved January 16, 2023, from https://www.ebi.ac.uk/about/news/perspectives/alphafold-using-open-data-and-ai-to-discover-the-3d-protein-universe.