Ethics Forum: The Current Landscape of Artificial Intelligence in Medicine

A handful of articles on artificial intelligence (AI) have graced the pages of this publication in the past six years, including one by Bharat Kumar, MD, in November 2022. Dr. Kumar highlighted the exciting potential of AI in rheumatology, including machine learning (ML) algorithms for the prediction of response to methotrexate and a predictive model for the early diagnosis of ankylosing spondylitis, while emphasizing the critical importance of humans, particularly physicians and patients, in the development and deployment of AI in medicine.¹

Since that article was published nearly two years ago—a generation in computer years—much has changed and much has remained the same. OpenAI’s ChatGPT appears on many of our home screens. As the company’s marketing material suggests, instead of consulting “Dr. Google,” patients can share their symptoms with an AI-powered chatbot, K Health, partially funded by Cedars-Sinai, a nonprofit academic healthcare organization.² We now attend grand rounds that seek to demystify the nomenclature of AI and to instill us with hope and fear.

Few of us in medicine, however, have harnessed the capabilities of large language models (LLMs) to increase the efficiency of our interactions with powerful, yet somehow obtuse, electronic health records (EHRs). In rheumatology, we are not yet the beneficiaries of the automated image processing software, described by Hügle et al., that promises improved efficiency and accuracy in interpreting images and diagnosing osteoarthritis.³ To my knowledge, none of the machine learning (ML) algorithms for the detection of osteoporosis using computed tomography (CT), evaluated by Ong et al. in a systematic review, have made it to clinical practice.^3,4 Still, it is difficult to look at the advancement of AI-enabled systems in fields such as gastroenterology and breast imaging and not appreciate what our future holds.^5-8

As of Oct. 19, 2023, the U.S. Food & Drug Administration (FDA) had authorized nearly 700 AI/ML-enabled medical devices, dating back to 1995, with 155 approved between 2022 and 2023 alone, the vast majority in the field of radiology.⁹ We will most certainly see this technology grow and expand into more fields of medicine in the coming years, including rheumatology.

As we await task-specific advances in our specialty, AI pushes forward in the harnessing of big data with foundation models. Howell et al. describe the acceleration in AI/ML over the past few years as our entry into the “third epoch,” or “AI 3.0,” marked by foundation models capable of generating new content without seeing new training data, encompassing LLMs that interpret complex medically related questions and produce comprehensive answers.¹⁰