The media loves to hype concerns about artificial intelligence: What if machines become super-intelligent and self-aware? How will humanity compete and survive? But artificial intelligence today is a far cry from a robot takeover. "AI" is a catch-all term that often refers to machine training or machine learning: There is an abundance of data, vastly more than the human mind can assimilate, being tagged, captured and stored. This systematic data processing requires methodologies that can put it in usable form and formats. While these new developments stoke fear in some corners, the ability to predict outcomes is generally seen as a good thing, as it can mitigate risks and even save lives.
We, collectively, want AI even though it is seldom expressed this way.
The prospects and attempts toward artificial intelligence has been with us for decades. Only recently have the underlying technologies and infrastructure--including computer processing, storage, networking speed and advanced software platforms--become omnipresent. These technological advances enabled the implementation of data mining concepts and the subsequent advantages that were not feasible just a decade ago.
AI is fantastical by vision, evolutionary by experience, and disruptive upon reflection. In the world of health care, AI is already transforming research and clinical practice. We, collectively, want AI even though it is seldom expressed this way. What we, the patient population, patient advocates and caregivers, agree on and want is: (1) timely, precise and inexpensive diagnoses of our ailments, injuries and disorders; (2) timely, personalized, highly effective and efficient courses of therapies; and (3) expedited recovery with minimum deficits, complications and recurrence.
"Artificial intelligence and machine learning will impact healthcare as profoundly as the discovery of the microscope."
Implicitly, we all are saying that we want our healthcare systems and clinicians to accomplish truly inhuman feats: to incorporate all sources of structured data (such as published statistics and reports) and unstructured data (including news articles, conversational analysis by care givers, nuances of similar cases, talks at professional societies); to analyze the data sourced and uncover patterns, reveal side effects, define probable success and outcomes; and to present the best personalized course of treatment for the patient that addresses the ailment and mitigates associated risks. It is hard to argue against any of this.
In a recent published interview, Keith J. Dreyer, executive director of the Massachusetts General Hospital and Brigham and Women's Hospital Center for Clinical Data Science, says that "artificial intelligence and machine learning will impact healthcare as profoundly as the discovery of the microscope."
But as AI helps physicians in profound ways, like detecting subtle lesions on scans or distinguishing the symptoms of a stroke from a brain tumor, we humans can't get too complacent. Evolving AI platforms will provide more sophisticated sets of "tools" to address both mundane and complex medical challenges, albeit with humans very much in the mix and routinely at the helm.
Humans do not appear endangered to be replaced anytime soon.
Human beings are capable of a level of nuance and contextual understanding of complex medical scenarios and, consequently, do not appear endangered to be replaced anytime soon. These platforms will do some heavy lifting for sure and provide considerable assistance across the healthcare industry. But human involvement is crucial, as we are best at adaptive learning, cognition, ensuring accuracy of the data, and continually providing feedback to improve the machine learning components of the AI platforms that the health industry will increasingly rely upon.
The human/machine interface is not binary; there is no line in the sand. It is fuzzy and evolutionary, a synchronicity that we all will surely witness and experience. In the future, it may be possible that all recorded knowledge, including genetic, genomic and laboratory data, from structured and unstructured sources, can be at the fingertips of your clinician, and then factored into diagnosing your condition and prescribing your course of treatment. This is precision and personalized medicine on a grand scale applied at the micro level--you!
But none of this will diminish the importance of doctors, nurses and all assortment of care providers. Though they all will undoubtedly become more effective with such awesome AI assistance, their job will always be to heal you with compassion, wisdom, and kindness, for the essence of humanity cannot be automated.
Rob Waddell dreaded getting a kidney transplant. He suffers from a genetic condition called polycystic kidney disease that causes the uncontrolled growth of cysts that gradually choke off kidney function. The inherited defect has haunted his family for generations, killing his great grandmother, grandmother, and numerous cousins, aunts and uncles.
But he saw how difficult it was for his mother and sister, who also suffer from this condition, to live with the side effects of the drugs they needed to take to prevent organ rejection, which can cause diabetes, high blood pressure and cancer, and even kidney failure because of their toxicity. Many of his relatives followed the same course, says Waddell: "They were all on dialysis, then a transplant and ended up usually dying from cancers caused by the medications."
This article is part of the magazine, "The Future of Science In America: The Election Issue," co-published by LeapsMag, the Aspen Institute Science & Society Program, and GOOD.
We invited Nobel Prize, National Medal of Science, and Breakthrough Prize Laureates working in America to offer advice to the next President on how to prioritize science and medicine in the next four years. Almost universally, these 28 letters underscore the importance of government support for basic or fundamental research to fuel long-term solutions to challenges like infectious diseases, climate change, and environmental preservation.
Many of these scientists are immigrants to the United States and emphasize how they moved to this country for its educational and scientific opportunities, which recently have been threatened by changes in visa policies for students and researchers from overseas. Many respondents emphasize the importance of training opportunities for scientists from diverse backgrounds to ensure that America can continue to have one of the strongest, most creative scientific workforces in the world.