Regulatory challenges in ai-based diagnostics: Legal implications of ai use in medical diagnostics - Naili Yuris Tri; Mangkunegara Iis Setiawan; Purwono; Baballe Muhammad Ahmad (BIO Web of Conferences)
Artificial intelligence (AI) is being used more and more in medical diagnostics, with the potential to increase operational efficiency and diagnosis accuracy. But the use of AI also brings with it legal and regulatory ramifications, such as concerns about ethics, patient consent, and liability. The purpose of this study is to investigate how the legal system might be modified to clearly define obligations for healthcare professionals and technology innovators while defending patient rights. The approach was a thorough study of the literature that assessed the legal and regulatory implications of using AI in medical diagnosis. The research results indicated that algorithmic bias, data security, and the requirement for stringent rules to guarantee the ethical and safe application of AI are the primary obstacles. In order to guarantee equity and safety in medical practice, the study’s conclusion highlights the significance of stringent regulation and openness in the application of AI. The creation of a more stringent evaluation system, independent audits of AI algorithms, and greater transparency in data collection and use are among the regulatory policy recommendations. To enhance algorithms, modify the legal framework to safeguard patient rights, and clearly define the obligations of technology creators, more study is necessary.