Each year, the University of Wisconsin School of Medicine School of Public Health hosts the Bioethics Symposium, which brings together distinguished scholars from a variety of backgrounds to explore themes related to public health, medicine, and ethics. His 2024 Bioethics Symposium, the 15th, explored the theme “AI, Ethics, and Healthcare.”
The symposium explored concerns about the intersectionality of AI and healthcare. Part of the learning goals for the 2024 symposium was to identify strategies for building trust with patients and discuss emerging issues in AI related to social justice.
According to the symposium's website, artificial intelligence has changed the world of medicine, creating a wide range of diagnostic, patient care, and clinical decision-making opportunities. However, it also raises ethical concerns and challenges that can perpetuate inequalities in public health.
University of California SMPH Dean Robert Golden gave a welcome address, followed by the introduction of Carola Kreitmeyer, assistant professor of medical history and bioethics.
The first talk of the symposium was with Associate Professor of Medicine Majid Afshar on bias embedded in electronic medical record databases. Afshar said training data plays an important role in reducing the stigmatizing language and inequalities that exist for patients of different ethnicities.
Possibilities of Open Generative Pre-trained Transformer 4 — Multipurpose language model trained to generate images, emails, and other tasks — Afshar said it could perpetuate racial and gender bias in the health care system.
“OpenAI GPT-4 is more likely to rate black male patients as opioid abusers than Asian, black, Hispanic, or white women…AI progress has been held back by us.” [physicians]” Afshar said. “It requires learning how to construct answers, backtesting, and ensuring code transparency across multiple language models.”
Nicole Turner Lee, director of the Center for Technology Innovation at the Brookings Institution, discusses strategies for mitigating bias in AI, how to identify the impact of using AI, how to research and address real-world examples for approaching bias in data, and He talked about the method. Provides support for health equity training on data and models used in AI.
Other speakers included K&L Gates, Professor of Ethics and Computational Technology at Carnegie Mellon University, Alex John London, Associate Professor of Philosophy and Canada Research Chair at McGill University, and Clytmare. Each speaker touched on the safe use of AI in healthcare, machine learning in healthcare, and cognitive challenges in clinician-patient interactions.
The 2024 Bioethics Symposium aimed to create a roadmap for the responsible use of AI to promote medical practice that reflects equity and ethics.
