The governance of generative artificial intelligence (AI) technologies in medicine
has become a major topic of discussion due to concerns about their rapid development
and use, which have outpaced existing regulatory measures.1 Findings from a recent
large-scale survey underscore the urgency of renewed oversight, revealing that one
(20%) in five of the UK-based general practitioners surveyed use large language model
(LLM) chatbots for clinical tasks.2 Although much attention has been focused on popular
and widely available LLM-based chatbots, such as ChatGPT (OpenAI and Microsoft), addressing
unresolved challenges related to privacy, bias, accuracy, and accountability requires
a standardised frameworks that goes beyond the regulation of chatbot as conversational
tools and considers the wider AI capabilities for data generation.
Via Lionel Reichardt / le Pharmageek
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The governance of generative artificial intelligence (AI) technologies in medicine has become a major topic of discussion due to concerns about their rapid development and use, which have outpaced existing regulatory measures.
1 Findings from a recent large-scale survey underscore the urgency of renewed oversight, revealing that one in five (20%) of the UK-based general practitioners surveyed use large language model (LLM) chatbots for clinical tasks.
2 Although much attention has been focused on popular and widely available LLM-based chatbots, such as ChatGPT (OpenAI and Microsoft), addressing unresolved challenges related to privacy, bias, accuracy, and accountability requires a standardised framework that goes beyond the regulation of chatbots as conversational tools and considers the wider AI capabilities for data generation.