Ethics of AI in Radiology (2021)-M5-CIN09-2021

Video Transcription

Video Summary

The provided transcript discusses the ethical and practical considerations in using clinical data for AI, focusing on balancing data utility with privacy. Initially, an ethical framework was established to guide data use and sharing, emphasizing clinical data as a public good benefiting future patients. Ethical obligations for healthcare participants include respecting patient dignity, providing optimal care, and enabling continuous learning to improve healthcare quality.<br /><br />Key topics include data stewardship, where anyone handling the data must commit to ensuring privacy and using data for societal benefit. The concept of treating clinical data as a public good is highlighted, wherein data's primary value is fulfilled when used for clinical care, and secondary uses should focus on public benefit without commercialization of raw data. Concerns about re-identification risks and data monetization ethics are noted, advocating transparency and informed consent about data use.<br /><br />Additionally, the notion of academic-industrial partnerships was explored, emphasizing symbiotic collaborations that align with ethical principles. Challenges, like the myth of anonymization and the fallacy of consent, showcase the complexities of maintaining privacy while harnessing AI technologies, advocating for better de-identification methods and exploring balanced data-sharing practices guided by ethical AI deployment.

Keywords

clinical data

AI ethics

data privacy

public good

data stewardship

re-identification

informed consent

academic-industrial partnerships

ethical AI