In recent essays, I’ve addressed the challenges facing medical societies and offered some thoughts on ways to reignite growth and member affinity. The most significant challenges facing scholarly societies stem from the “relevance gap” that exists between traditional association offerings and the new realities of modern medical practice. Nowhere is that gap so vividly demonstrated than in the burgeoning role of artificial intelligence (AI) in medicine.

Some observers have argued that we are entering a fourth industrial revolution. The first occurred in the 18th century and was driven by the steam engine. The second, in the early 20th century, saw the introduction of electrical power and assembly lines, and the third, which began in the late 20th century, was led by the development of modern computer and telecommunications technology.

The fourth industrial revolution, which is underway now, is characterized by a vast number of new technologies built on an advanced digital infrastructure. These bellwether technologies include nanotechnology, artificial intelligence (AI), natural language processing (NLP), computer vision, the Internet of Things (IoT), and three-dimensional printing. While the previous industrial revolutions occurred linearly and geometrically, this new industrial revolution is evolving at an exponential rate. The effect is that traditional business and clinical care models will be disrupted and rendered obsolete virtually overnight.

Concerning this fourth industrial revolution, Klaus Schwabe, the president of the World Economic Forum, stated, “We stand on the brink of a technological revolution that will fundamentally alter the way we live, work, and relate to one another. In its scale, scope, and complexity, the transformation will be unlike anything humankind has experienced before.” For those who believe that AI in healthcare is still the stuff of far-off science fiction, consider the following:

• As of this writing, the FDA has approved 38 AI algorithms for clinical use.
• There will be over 100 AI Showcase companies at RSNA 2019.
• A recent report in the Lancet described a Chinese multicenter dataset of over a million endoscopies performed on over 84,000 individuals that’s being used to train a highly accurate gastrointestinal AI-based artificial intelligence diagnostic system (GRAIDS).
• CMS just announced 25 finalists vying for a $1.6 million prize studying how to use AI to predict unplanned hospital visits for Medicare beneficiaries.
• Over $864 million was invested in the development of AI in healthcare in Q2 2019 alone.
• At the recently concluded American Academy of Ophthalmology annual meeting, over 24 AI- related abstracts were presented.
• Researchers at Geisinger used millions of ECG’s to train an algorithm to accurately predict the future incidence of atrial fibrillation.

AI in clinical care will play an increasingly prominent role in the professional lives of our members. In light of this, how should a scholarly society organize itself to lead in this new era? How can medical societies help practitioners prepare for this brave new world? How can we best ensure that these new technologies are utilized in a thoughtful and clinically appropriate fashion?

In order for professional associations to fulfill their vital role as standards setters, they will need to evolve more rapidly than ever before. The keys to that evolution are education and engagement:

Education

This is the first and most essential first step. When most of us trained, AI was the stuff of science fiction and seemed a world away from clinical medicine. Just as we had to retrain to keep up with the genomic revolution, we must now make our way up the clinical AI learning curve. Medical societies must provide educational opportunities related to the central issues of clinical AI for their boards, key committees, senior leadership, and staff. Every medical discipline has clinicians who are active in this space; these thought leaders must be engaged, empaneled, and empowered as educators and mentors. Association leaders must take advantage of the many conferences, news feeds, blogs, and podcasts about this topic.

Engagement

Clinical AI is a team sport. The scholarly societies are ideally suited to serve as the epicenter of AI innovation within each of their disciplines. To earn this leadership role, associations must actively engage an ecosystem that includes industry, investors, tech incubators, regulatory agencies, universities, and academic health systems. By actively engaging nontraditional constituencies, the scholarly societies can serve as catalysts for clinically meaningful innovation.

Clinical AI is here to stay and its influence on medicine will increase exponentially. Medical societies that are in command of the moment can seize this opportunity to play a key leadership role. Marc Andreessen, the well-known technologist and investor, once speculated that, in the future, there would only be two kinds of people: those who tell computers what to do and those who are told by computers what to do. So too will it be in medicine. There will be medical societies that boldly lead this fourth revolution and others that will be left to follow.