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“The Promise of Artificial Intelligence in the East Asian Medicine Clinicor How I Learned to Stop Stressing and Love the Bot”By Sarah E. Rivkin, DAHM, LAc, Dipl. OMAt a recent check-up for my dog, our veterinarian began by asking if shecould use AI (artificial intelligence) to record the appointment. That way, sheexplained, she could give my anxious pup her full attention, without having toswitch back and forth between him and the computer to take notes. After theappointment she or her assistant would then review and correct his chart to makesure it was accurate. Despite my Luddite tendencies—and knee-jerk distrust ofAI—I said yes. My dog had the calmest and easiest appointment he’d had in years.As I later learned, AI scribe services are an exploding sector of medical technology,for both animals and humans. After this experience I could see why.Perhaps it was time to learn more about the upside to AI. I started with tworecent bestsellers on the subject:Nexus, by Yuval Noah Harari andCo-Intelligence,by Ethan Mollick. Harari’s premise is that “the rise of AI is arguably the biggestinformation revolution in history” (p. xxx) however “to exercise our agency, we firstneed to understand what the new technologies are and what they can do.” (p. 228)Mollick predicts that AI will make us all into editors, like the veterinarian reviewingher chart. He goes on to assert that “an AI future requires that we lean into buildingour own expertise as human experts.” (pg. 191) Delving more into how AI is alreadybeing used in East Asian medicine, I then learned that at the most recent Society forAcupuncture Research (SAR) conference, there were presentations on using AI forautomated needle detection, tongue diagnosis, and other types of diagnosisprediction.[1] © Sarah Rivkin 2024
How could I ignore AI? And, moreover, could I integrate AI into my practice?Could it make my professional life easier or even make me a better clinician? Thepromise of the technology is that we could use it to offload mundane tasks, freeingus up to focus on more meaningful aspects of our work. Perhaps a chatbot on mywebsite to answer simple questions or assistance with email queries? Better yet,having run into difficulty following the arcane rules of “iron-clad” charting to satisfyvarying insurance requirements, might AI be able not only to record the patientencounter, as at my veterinarian’s, but also ensure that it was charted correctly foroptimal reimbursement?These kinds of applications seem relatively straightforward andnon-threatening, but what of using AI and large language models (LLMs) fordiagnosis? This is the fear that the machines may someday replace us. But as a loverof case studies with mediocre Chinese language skills, this is also the potentialapplication that excites me the most: What if you trained an LLM on the completecase studies (in Chinese) of your favorite historical physician. Many of these oldcases are freely available online and not subject to copyright. Maybe Liu Duzhou?Now imagine you have a patient you are struggling with. Could you feed their signsand symptoms into the model to learn what Professor Liu would do? Why not getXu Shuwei and Yi Tianshi’s takes as well, so you could compare their approaches?These old Chinese doctors might serve as virtual guides, but they wouldn’t replacethe living clinician who would still need to sift through results and decide how bestto proceed. As Mollick says, AI can “mentor us to increase our own skills … helpingus fill the gaps in our own knowledge and pushing us to become better ourselves.”(p. 191)Finally, to data collection and analysis. All of us who chart electronicallypotentially have an extraordinary amount of valuable information available to us, buthow to access and interpret it to increase our clinical efficacy? How do we sift © Sarah Rivkin 2024
through it? We all have our favorite herbal formulas, acupuncture points, and otherstrategies: Do we know when and for whom they are most effective? And what ifwe wanted to compare our application or outcomes with that of a colleague orcolleagues or even more broadly with practitioners distributed across time andspace? Allopathic medicine is starting to use AI to predict who will do best on aparticular drug or with a surgical intervention, making huge strides in oncology,women’s health, and the treatment of chronic disease. Provided there are adequatesafeguards in place to ensure HIPAA compliance and data security, might somethingsimilar be possible in our field?AI has the potential to upend many aspects of our personal and professionallives, necessitating it is deployed responsibly. Its implementation will require humanoversight and guard rails, particularly in vital areas like health care. However, fear ofthe unknown should not scare us away from potential benefits. The choice of howto use a particular technology, to harm or help, is up to us. And, as Harari points out,we “still have a lot of control over the pace, shape, and direction of thisrevolution—which means we also have a lot of responsibility” (p. 226). But we alsohave a tremendous opportunity.[1]For the complete abstracts of the papers presented at SAR/RCMI PolyU InternationalResearch Conference (May 23–25, 2024, the Hong Kong Polytechnic University, Hong Kong,China) see Journal of Integrative Medicine 22 (2024) 303–378. © Sarah Rivkin 2024