Legal, regulatory, and ethical frameworks for development of standards in artificial intelligence (AI) and autonomous robotic surgery
By Shane O'Sullivan, Nathalie Nevejans, Colin Allen, Andrew Blyth, S. Léonard, U. Pagallo, Katharina Holzinger, Andreas Holzinger, Mohammed Imran Sajid, H. Ashrafian. 2019
336 citations recorded by the source corpus.
This paper aims to move the debate forward regarding the potential for artificial intelligence (AI) and autonomous robotic surgery with a particular focus on ethics, regulation and legal aspects (such as civil law, international law, tort law, liability, medical malpractice, privacy and product/device legislation, among other aspects).
Subfields: Artificial Intelligence, Health Informatics, Safety Research
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
- Przemyslaw Biecek
- Anna Saranti
- Andreas Holzinger
- Christoph Molnar
- Amna Khan
- Wojciech Samek
- K. Müller
- Grgoire Montavon
In Health Informatics
- Harry P. Hallock
- Amna Khan
- Przemyslaw Biecek
- Wojciech Samek
- Gabriel Beltrao
- Sónia Cláudia Da Costa Sousa
- Tita Alissa Bach
In Safety Research
- Harry P. Hallock
- Amna Khan
- Wojciech Samek
- Gabriel Beltrao
- Sónia Cláudia Da Costa Sousa
- Christoph Molnar
- Tita Alissa Bach
Citations in the corpus
- Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine (2024, background): “Finally, regulatory and ethical considerations will become by far more important as AI technologies become more integrated into pharmaceutical practices to ensure the transparency, fairness, and accountability of AI systems as well as maintain trust and compliance within the industry [178–186].”
- Explainable AI Methods - A Brief Overview (2020, background): “, due to the new European General Data Protection Regulation (GDPR, in force since May 2018), complicate the use of black-box approaches, particularly in domains that affect human life, such as the medical field [56], [63], [73], [76].”
- A Systematic Literature Review of User Trust in AI-Enabled Systems: An HCI Perspective (2022, methodology): “Setting up ethical-legal boundaries of AI-enabled systems was consistently seen as a significant challenge due to unclear accountability between involved parties and unclar-ity of a determinant if harm occurred to the users (O ’ Sullivan et al., 2019).”
- Ethical principles for artificial intelligence in education (2022, background): “Whereas learning analytics are governed by data ethics, many AIs are forms of intelligence expressed by some artifact (Bryson & Theodorou, 2019) that interacts with humans at various levels, such as robots and self-driving cars (Manoharan, 2019; O’Sullivan et al., 2019).”