Artificial Intelligence (AI) & Emerging Technologies
Chat GPT, Generative AI, and Machine Learning
Aideen Fay - Microsoft and the European Cyber Conflict Research Initiative
Angelina Gentaz - EffiSciences
Aideen Fay - Microsoft and the European Cyber Conflict Research Initiative.
Angélina Gentaz - EffiSciences
Targets: The topic of co-operative AI and its relevance to AI governance aligns with several Sustainable Development Goals (SDGs). By promoting collaboration, transparency, and accountability in AI development and deployment, we contribute to SDG 9 (Industry, Innovation, and Infrastructure) by fostering technological advancements that are inclusive, sustainable, and resilient. Additionally, by addressing the technical challenges and ethical concerns associated with AI, we contribute to SDG 16 (Peace, Justice, and Strong Institutions) by promoting responsible and ethical AI practices that uphold fairness, equality, and human rights. Furthermore, by safeguarding against the unintended proliferation of dangerous AI, we support SDG 3 (Good Health and Well-being) and SDG 11 (Sustainable Cities and Communities) by ensuring the safety and security of individuals and communities in the digital era. Overall, this talk underscores the significance of co-operative AI in advancing the SDGs and creating a more inclusive and sustainable future. It also plays a role in supporting SDG 5 (Gender Equality) by addressing and systematically removing biases from AI systems. AI technologies have the potential to perpetuate gender biases and reinforce societal inequalities if not properly developed and regulated. Co-operative AI emphasizes collaboration, transparency, and accountability, enabling us to identify and mitigate biases present in AI algorithms and data sets. By actively involving diverse stakeholders, including women, in the design, development, and evaluation of AI systems, we can ensure that these technologies are less likely to amplify harmful biases and stereotypes.
The talk will be presented in a dynamic and engaging manner, utilizing a combination of informative slides and interactive discussions. The speaker will begin by introducing the concept of cooperative AI and its relevance to AI governance. The technical challenges associated with implementing cooperative AI will be discussed, including issues such as data sharing, privacy concerns, and coordination among AI systems. The latest research advancements in the field will be highlighted, showcasing real-world examples of cooperative AI applications and their potential impact. The speaker will emphasize the importance of cooperation among AI systems for addressing complex societal challenges and advancing the field of AI in a responsible and ethical manner. To prevent the unintended spread of AI systems, the talk will explore complementary techniques and strategies. This will include discussing the role of regulation in governing advanced AI development and proposing policy considerations to ensure the responsible deployment of AI technologies. Throughout the talk, ample time will be dedicated to engaging the audience through interactive discussions and Q&A sessions. Attendees will have the opportunity to share their perspectives, ask questions, and contribute to the dialogue on cooperative AI, technical challenges, and governance. The goal is to foster a collaborative environment that encourages knowledge sharing and exchange of ideas among participants.
Co-operative AI involves multiple AI systems working effectively together, sometimes in a collaborative manner, to achieve complex tasks. To some extent, Co-operative AI also strives to steer the worldwide drive of AI governance and policy for collaboration in both AI development and oversight.
In this talk, we will delve into the fast-emerging field of co-operative AI, exploring its definition, technical challenges in implementation, the latest research advancements and its significance for AI governance. Through this talk, our objective is to provide attendees with a comprehensive understanding of cooperative AI, its challenges, governance ramifications, and strategies for a safe AI development.