One new trend in the definition of patient autonomy is a shift away from traditional views prioritizing individual decision-making towards what is called relational autonomy. Relational autonomy emphasizes and recognizes that individuals are interconnected with social networks and relationships that can influence their decisions about treatment options. For example, both emotionally and legally through health-care proxies, patients often rely on family caregivers, and community members for support in times of decision-making. An individual’s end of life care may be influenced by their family’s wishes, their cultural background or their religious beliefs. Healthcare providers are encouraged to consider these factors in an ethical framework when supporting patients in making choices about their health.
AI’s new dominance in healthcare also creates challenges to ethical frameworks of patient autonomy. AI is rapidly transforming healthcare in many areas, from diagnostic imaging, to telemedicine opportunities, to growing public awareness of different illnesses and treatment options, to creating more personalized medical plans and interventions. However, with AI advancements comes more concerns surrounding data privacy, algorithmic bias, and the potential for broad systems to greatly undermine individual patient autonomy. Ethicists are concerned with ensuring that developed AI systems are ethical, and protect personal data while promoting transparency, and accountability. Ethics education needs to adapt quickly to address these new AI challenges, equipping healthcare professionals with skills to navigate these emerging ethical complexities.