Techné / Society for Philosophy & Technology (SPT)

🚨 [AI RESEARCH] The paper "The Ethics of AI in Health Care: An Updated Mapping Review" by @jessRmorley & @Floridi is GREAT for understanding ethical issues in AI-powered healthcare. 3 core ethical concerns everybody should be familiar with: 1️⃣  Epistemic concerns: inconclusive, inscrutable, and misguided evidence "(...) Just because an AI model can recognize a pattern, does not automatically make the pattern meaningful nor the action it informs clinically efficacious or safe. In brief, AI models trained on poor-quality data can produce inaccurate or discriminatory outputs that may lead to patient fatalities (...); models that are initially well-trained and properly validated may introduce patient safety risks post-deployment due to the negative effects of dataset drift or even data poisoning (...); and large language models may regurgitate or hallucinate harmful misinformation (...)" 2️⃣ Normative concerns: unfair outcomes and transformative effects "(...) normative ethical concerns focus on how the integration of AI into healthcare systems might fundamentally alter the nature of care delivery. Specifically, by focusing on how the implementation of AI may reconfigure relationships between different parts of the healthcare ecosystem, normative ethical implications stress AI’s potential to (a) change how health and illness are conceptualized, categorized, and managed (...); (b) reshape the embodied and affective experiences of both patients and clinicians; (c) reinforce social inequalities (...); and (d) erode trust in human healthcare professionals (...)" 3️⃣ Concerns related to traceability "The preceding discussion of the normative ethical risks associated with the increasing use of AI in healthcare highlighted how AI has the potential to transform the delivery of healthcare fundamentally. At the core of this transformation process, is the development of a far more complex network consisting of humans and non-human agents. The complexity of this resultant network makes responsibility attribution difficult because a fault, that may result in a patient safety issue, may have multiple different causes that are hard to trace (...). This is concerning because, according to Felder (2021), the transparent organization of responsibility in a healthcare system serves at least two purposes: (a) to incentivize healthcare providers to act ethically in all circumstances; and (b) to ensure the foundation of patient trust in the reliability of healthcare providers is sufficiently solid for healthcare to flourish. (...)" ➡️ Read the paper below. 🏛️ STAY UP TO DATE. AI governance is moving fast: join 37,000+ people in 150+ countries who subscribe to my newsletter on AI policy, compliance & regulation, including outstanding research papers (link below).