Trustworthy AI series: Fairness in AI and its relation to social well-being

In this SGS Live Replay, our experts explore the connection between Artificial Intelligence (AI) systems and their impact on social well-being. This session kicks off our series, Trustworthy AI: Current Areas of Research and Challenges, where we dive into the importance of building trust in AI. Join Tomislav Nad, Lead Innovation Technologist at SGS, Willy Fabritius, Global Head of Strategy & Business Development Information Security at SGS, and Simone Kopeinik, Deputy Research Area Manager - Fair AI at Know Center, as they discuss key research areas, emerging challenges, and the evolving standards shaping the future of AI.(00:00:16)- Introduction.(00:04:50)- Why has Fairness just now become such a popularly discussed topic? (00:06:52)- What is the difference between Fairness and Bias?  (00:20:07)- How can we measure Bias in AI?(00:24:06)- Are there tools that support checking for Bias in AI? (00:26:33)- Some examples of how Bias in AI can be addressed or even mitigated(00:30:21)- The biggest challenges in the field(00:34:04)- Q&A(00:41:40)- Is fairness also an issue if my application does not work in sensitive or high-risk domains?About our “Trustworthy AI: current areas of research and challenges” series:The need for trustworthy Artificial Intelligence systems is recognized by many organizations, from governments, to industries and academia. As AI systems become more widely used by both organizations and individuals, it is important to establish trust in them. To establish this trust, numerous white papers, proposals and standards have been published and are still in development to educate organizations on the need for and uses of AI systems. Join us for our series as our experts discuss a variety of topics related to building trust and understanding of AI systems.

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