R. Gregory Lande, DO, COL (Ret) FACN, FAOAAM is a past president of the AOAAM. Dr. Lande retired from the US Army Medical Corps in recognition for which he received the Legion of Merit award. Dr. Lande then assumed a variety of administrative, clinical, academic, and research positions. Currently, Dr. Lande is a clinical supervisor, Editor-in-Chief of the Journal of Addictive Diseases, and a clinical professor at the Orlando College of Osteopathic Medicine. He is the author of over 100 articles, chapters, and books on a wide variety of medical and medical history subjects.
Technological advances are part of the changing landscape in addiction medicine. Researchers are actively exploring non-invasive brain interventions, such as transcranial magnetic stimulation, for practical clinical roles in addiction medicine. Software applications that engage patients in treatment and telemedicine both leverage modern technology. All three approaches expand the scope of clinical practice, but not without concerns ranging from safety, efficacy, and privacy.
Now comes a novel approach that aims to simulate aspects of care in human addiction medicine. This newcomer, Artificial Intelligence (AI), is rapidly entering healthcare and, like other technological approaches, is raising questions that extend beyond safety, efficacy, and privacy to include ethical concerns and tensions over the boundary between human interaction and AI’s ability to co-opt aspects of clinical care.
AI brings with it a language foreign to clinical practitioners. Evaluating AI’s benefits and harms requires at least a rudimentary understanding of this new terminology. The following discussion does not aim to produce a clinician fluent in the language but instead to stimulate further reflection and study.
As it currently stands, there is a knowledge gap between those who use AI and those who develop it. This barrier contributes to silos or stovepipes that interfere with the free flow of information. Lowering the knowledge barrier helps clinicians understand both the capabilities and limitations of AI while preserving the essential role of clinical judgment.
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