Àá½Ã¸¸ ±â´Ù·Á ÁÖ¼¼¿ä. ·ÎµùÁßÀÔ´Ï´Ù.
KMID : 0986720190270020035
Korean Journal of Medicine and Law
2019 Volume.27 No. 2 p.35 ~ p.71
Consideration of legal issues related to the application of artificial intelligence in health care
Lee In-Young

Abstract
AI has the potential to be used in planning and resource allocation in health and social care services. Using AI to analyse clinical data, research publications, and professional guidelines could also help to inform decisions about treatment. AI has applications in fields that are subject to regulation, such as data protection, research, and healthcare. However, AI is developing in a fast-moving and entrepreneurial manner that might challenge these established frameworks. The use of AI raises ethical and legal issues, including: the potential for AI to make erroneous decisions; the question of who is responsible when AI is used to support decision-making; inherent biases in the data used to train AI systems; ensuring the protection of potentially sensitive data; securing public trust in the development and use of AI technologies. AI applications in healthcare make use of data that many would consider to be sensitive and private. Using data that raise privacy concerns should go beyond compliance with the law to take account of people¡¯s expectations about how their data will be used. Reliability and safety are key issues where AI is used to control equipment, deliver treatment, or make decisions in healthcare. Machine learning technologies can also be particularly opaque because of the way they continuously tweak their own parameters and rules as they learn. This creates problems for validating the outputs of AI systems, and identifying errors or biases in the data. Further challenges include the need to ensure that the way AI in healthcare is developed and used is transparent, accountable, and compatible with public interest, and balanced with the desire to drive innovation.
KEYWORD
AI algorithm, medical information big data, algorithm transparency, AI governance, data bias, watson for onology, surgical robot
FullTexts / Linksout information
Listed journal information
ÇмúÁøÈïÀç´Ü(KCI)