Participation in AI by groups that are traditionally underrepresented in computer science is a fraction of what is needed to have an AI workforce that reflects the diversity in society. The panel will address the lack of diversity in AI, including diversity of races, ethnicities, genders, ages, religions, disabilities, sexual orientations, socioeconomic status, and cultural background.
The main goals of the panel are to (1) promote awareness of the situation and how it is detrimental to the field; (2) discuss potential actions to improve the situation and help broaden participation in the field; and (3) find ways to enlist supporters and allies, especially those who are in privileged positions and who can therefore exert the most influence.
Tuesday, August 13th, 10:50 - 12:35
Marie des Jardins, University of Maryland, Baltimore County, USA
AI has been rapidly gaining momentum in the last years, and is today widely regarded as a key technology for future economic and societal development. Since its early beginnings, IJCAI has been a leading forum to gather researchers and developers for the presentation, exchange, and discussion of novel ideas and approaches to AI, sometimes even in difficult circumstances. The question to be explored by this panel is whether AI is in the middle of a radical change in direction, which is or will lead to rapid growth in new directions and abandoning older lines of investigation, or are the long-term objectives mostly the same, but the means to getting there changing.
Wednesday, August 14th, 11:00 - 12:30
Ray Perrault, Stanford Research Institute
Due to a rapidly increasing number of submissions, running the paper selection process at large AI conferences has become more and more challenging, and the results may not be fully satisfactory to multiple parties. This panel is devoted to discussing issues around this: how to cope with thousands of submissions, and how to warrant quality of reviews? How does this increase in numbers affect the relative role of conferences and journals, especially in connection with funding and academic promotion?
Thursday, August 15th, 11:00 - 12:30
Carles Sierra, Artificial Intelligence Research Institute (IIIA), Spain
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.
Friday, August 16th, 11:00 - 12:3
Qiang Yang, AI Director at WeBank, China and Chair Professor at Hong Kong University of Science and Technology, Hong Kong