Privacy and confidentiality of big data and ethical Artificial Intelligence (AI) are becoming a key concern in the development of AI worldwide. Many AI techniques rely on the continual availability of data, but data users are required to be increasingly cautious when unlocking the value in the data. The European Union’s General Data Protection Regulation (GDPR), for example, brings new legislative challenges to the AI community, which is starting to be concerned about the legal and societal implications of ethical AI and regulations. These new issues are complex and span multiple dimensions beyond technology alone, while new solutions to comply with the law, such as Federated Machine Learning (FML) and Privacypreserving machine learning, are emerging on the horizon. These new challenges come in multiple dimensions beyond technology, touching on social, cultural, ethical and legal aspects.
This panel will invite experts from diverse backgrounds to explore and debate on the aforementioned issues and challenges. We hope to create a level ground where all voices are heard on the issues of AI advancement in the era of user privacy, data confidentiality and ethical development of AI. Potential questions include: How to make AI GDPR-compliant? How to quantify data values and the economics of data federation? What are some effective safety and security issues for AI solutions? What are some standards of data privacy and security? We hope to invite the audience to participate and contribute questions as well.
August 12-15, 2019 Macao SAR, China
Dr. Qiang Yang, AI Director at WeBank, China and Chair Professor at Hong Kong University of Science and Technology, Hong Kong