To learn more about our data set and what we do to help create a healthier world, please contactYvonne Ridge
Head of Product, JJ竞技 Knowledge Centre
The JJ竞技 Knowledge Centre produces a range of digital resources in clinical decision support and medical education (including JJ竞技 Best Practice ). Over the past few years, we have seen an increasing interest in how our digital resources can be used in the context of machine learning and artificial intelligence. We are keen to ensure that our resources play a part in these innovations.
However, we are equally keen to ensure that what we do is ethical and safe. This is especially so in the area of active clinical decision support. We have gathered a team of external experts who we can call upon to guide us.
1. Clarifying, reviewing, and developing policies relating to artificial intelligence, clinical decision support, and digital health
2. Advising the JJ竞技 Knowledge Centre team on ethical questions that might arise during existing or new lines of work.
3. Advising the JJ竞技 Knowledge Centre team on new partnerships that it might develop with organisations that are creating artificial intelligence software
4. Taking part in roundtables on important issues or controversies related to artificial intelligence in healthcare
Members of the JJ竞技 Knowledge Centre ethics committee correspond and meet on an as-needed basis when the JJ竞技 Knowledge Centre needs advice. Individuals are contacted on the basis of their individual expertise in areas such as avoiding harm, patient autonomy, transparency and explicability, human agency and oversight, safety, security, legality, confidentiality, or data governance. The group will also meet – but no more than once per year. Meetings take place at the JJ竞技 office in London, with remote participation possible.
Trusted AI 101: A Guide to Building Trustworthy and Ethical AI Systems
AI4People—An Ethical Framework for a Good AI Society: Opportunities, Risks, Principles, and Recommendations
AI4People – 7 AI Global Frameworks
Understanding artificial intelligence ethics and safety
State of implementation of the OECD AI principles
Big data, artificial intelligence, machine learning and data protection
Good Machine Learning Practice for Medical Device Development: Guiding Principles
NHSX: Artificial Intelligence: How to get it right. Putting policy into practice for safe data-driven innovation in health and care
Ethics and governance of artificial intelligence for health. WHO guidance
Recommendation on the ethics of artificial intelligence