My Robot-Surgeon’s Name Was Rosa

 

She had some help from a human doctor who watched her as she removed my old knee and expertly inserted a new one in its place. Titanium and ceramic knee replacement. I was, as you might assume, quite anesthetized except for the informal introduction in the OR, but the advent of artificial intelligence in my world has been profound. OK, my human doctor helped! But AI is in my life… big time. As a practicing entertainment attorney, my business came to a virtual halt as actors and writers went on strike (from April 2 through November 9, 2023), in significant part over the actual and potential impact of AI on all aspects of film and television production.

I am a speaker in an upcoming day-long presentation from the Beverly Hills Bar Assn and the Entertainment & Sports Forum of the American Bar Assn for entertainment lawyers dealing with AI issues. It is a huge deal. We know the combination of AI and accelerating computing power – oozing into analytics, creativity, drafting and organizing, automated communications, robotics (hi Rosa) and even decision-making – is changing the work world like no other. If most of the high-paying jobs, today requiring advanced skills and/or education, are replaced by AI, who’s going to have enough money to purchase the products and services these automatic processes produce? Are those controlling AI a separate class of people (assuming the AI robots do not take over) with most of the wealth on the planet? Is the dreaded “S” word an inevitable reality? Socialism?

But in the meantime, AI is producing some miraculous results. Yet, it has been awkward in so many cases and so robust in others. On March 27th, The Economist began a focus on the impact of AI on healthcare: “Better diagnoses. Personalised support for patients. Faster drug discovery. Greater efficiency. Artificial intelligence (AI) is generating excitement and hyperbole everywhere, but in the field of health care it has the potential to be transformational. In Europe analysts predict that deploying AI could save hundreds of thousands of lives each year; in America, they say, it could also save money, shaving $200bn-360bn from overall annual medical spending, now $4.5trn a year (or 17% of GDP). From smart stethoscopes and robot surgeons to the analysis of large data sets or the ability to chat to a medical ai with a human face, opportunities abound.

“There is already evidence that ai systems can enhance diagnostic accuracy and disease tracking, improve the prediction of patients’ outcomes and suggest better treatments. It can also boost efficiency in hospitals and surgeries by taking on tasks such as medical transcription and monitoring patients, and by streamlining administration. It may already be speeding the time it takes for new drugs to reach clinical trials. New tools, including generative AI, could supercharge these abilities. Yet as our Technology Quarterly [in late March] shows, although AI has been used in health care for many years, integration has been slow and the results have often been mediocre.

“There are good and bad reasons for this. The good reasons are that health care demands high evidentiary barriers when introducing new tools, to protect patients’ safety. The bad reasons involve data, regulation and incentives. Overcoming them could hold lessons for AI in other fields…. AI systems learn by processing huge volumes of data, something health-care providers have in abundance. But health data is highly fragmented; strict rules control its use. Governments recognise that patients want their medical privacy protected. But patients also want better and more personalised care. Each year roughly 800,000 Americans suffer from poor medical decision-making…

“A [large] problem involves institutions and incentives. AI promises to cut medical costs by assisting or replacing workers, improving productivity, reducing errors and flattening or reducing spending, all while improving care. That is desperately needed. The world could lack 10m health-care workers by 2030, around 15% of today’s workforce. And administration accounted for about 30% of America’s excess health-care costs, compared with other countries, in 2022.

“Yet saving money using innovation is tricky. Health systems are set up to use it to improve care, not cut costs. New technology may account for as much as half of the annual growth in health spending. Layering on new systems will increase costs and complexity. But redesigning processes to make efficient use of ai is likely to be resisted by patients and medics. Though AI may be able to triage them over the phone or provide routine results, patients may demand to be seen in person.

“Worse, many health systems, such as America’s, are set up to reward the volume of work. They have little reason to adopt technologies that cut the number of visits, tests or procedures. And even publicly run health-care systems may lack incentives to adopt technologies that reduce costs rather than improve outcomes, perhaps because saving money may lead to a smaller budget next year. Unless governments can change these incentives, so that AI combines better treatment with new efficiencies, innovation will increase costs. Accordingly, governments and health authorities will need to fund schemes dedicated to testing and deploying new ai technologies. Countries including America, Britain and Canada are pointing the way.” Good reason why universal healthcare is better for patient care, where AI will be more effective.

At least, I can attest to the precision value. Indeed, today a robot allows a petite orthopedic surgeon to generate superb results – no longer requiring a muscle-bound jock to jostle and saw bones anymore. The post-surgical X-rays showed perfect placement on my knee. Thanks Rosa… and er… Brad (the human doctor who monitored and adjusted the process). We’re struggling on how to implement regulations that control and limit the use of AI in medicine, and as fast as such rules may be implemented, many are obsolete almost immediately upon issuance. But we are making progress.

AI can create virtual experiments in nano seconds and suggest new combinations to create new and evolving medications and surgical procedures. But so far, as magnificently as my surgery went, the most amazing achievements have been in diagnostics, particularly in reading X-rays and MRIs, looking for the minutia, the tiny clues, of cancer and other anomalies. The greatest evidence of this success has been in the detection and treatment of breast cancer. With a database of millions of X-rays that evidence cancer, AI has “learned” to recognize those tiny signs that may even elude a seasoned radiologist. As one of the leading causes of death and suffering among women, breast cancer can be more efficiently screened and treated than ever before.

I’m Peter Dekom, and soon almost everyone is going to have to come to grips with the extreme plusses and extreme minuses that AI continues to bring into this world.