Artificial Intelligence Is Good for Your Health
Many of us benefit from artificial intelligence (AI) every day. Google and Amazon employ AI to refine their search-result algorithms. Like many professional writers, I use AI-driven editing software that has improved my prose—it’s easier to learn the subtleties of grammar when the application corrects mistakes in real time. These examples do not describe the type of AI that has caused a stir as of late.
Generative AI includes image and language models that output text or images based upon human prompts. The internet is awash with praise and criticism of how generative AI will shape culture. This technology—like all technology—is a double-edged sword. There is high potential for abuse by prompting these applications to create content in the style of a published and copyrighted author or artist. This is highly unethical to the hardworking creators trying to make a living off their work.
The unethical use of AI should not dissuade us from the many benefits. We need to look beyond the binary that AI is either here to save us or the downfall of humanity. Seeking a ternary relationship with AI reveals its positive-use potential. In the example of writing, if we allow AI to embellish our own inspired work, we can become better writers. As opposed to the old computer science idiom of “garbage in, garbage out,” with AI, we have the possibility of entering “good in” and getting “great out.”
With human health, I’m going to go out on a limb and predict that artificial general intelligence will be to biology and ecology what mathematics is to physics. The scientific method has been the champion of conventional science for hundreds of years, with revolutionary breakthroughs in many fields, including my discipline of medicine. The blind spot of science, starkly evident within conventional medicine, is the inability to solve for all the variables in multifactorial problems. Consider that randomized, controlled trials try to eliminate as many variables as possible in order to home in on the efficacy of a treatment. This is the essence of the scientific method done properly, but biological systems are exceedingly complex.
Systems biology is the emerging field bringing computational analysis to study diverse interactions within biology and medicine. The interdisciplinary field of systems biology exists because there is a difference between being complicated and being complex. The basic needs of a cat are simple—a safe place with food and water are the basis for the feline’s survival. An occasional brushing and a bit of catnip go a long way, but a cat’s primary needs are not complicated. However, trying to predict what a cat will do next is nigh impossible. This makes cats—and certainly humans—complex creatures.
AI is poised to shine when we can do the opposite of a randomized, controlled trial and input multiple variables to study their combined effect. As a case in point, one of the trickiest aspects of prescribing pharmaceutical medications is the unknown effects when combining multiple drugs. Clinical trials seldom study the effects of polypharmacy.
Now think bigger picture. Imagine an AI that can make a detailed analysis of how exposure to this endocrine-disrupting environmental toxicant is interacting with that microbiome-disrupting herbicide, in the context of someone with a certain genetic single-nucleotide polymorphism who is also taking multiple medications.
The art of medicine is understanding the complex interactions at the intersection of the terrain of the body and influences from the environment. Supercomputing AI may be the disrupting technology that galvanizes public and private sectors with the (self-evident) conclusion that human actions such as widespread pollution underlie chronic illness and ecological degradation. Though it may not be intuitive, there is a connection between such seemingly disparate issues as loss of pollinators and increases in cancer. The web of life will be revealed by systems biology when the discipline can fully leverage the power of AI.