Algorithmic Bias: How to understand, manage, and mitigate

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Presented by

Maor Ivgi, CTO, Stardat, Heather Dawe, UK Head of Data, UST & Adnan Masood, Chief Architect of AI and Machine Learning, UST

About this talk

Do you also feel concerned about the urgent need for consistency in data, transparency in algorithms, and the prevention of the underlying bias in AI/ML? Then join us for this live webinar discussion and learn how you can achieve Fairness, Accountability, and Transparency (FAT) in AI Systems. The following is the agenda of this discussion: • What are the different types of bias? • How to understand and monitor Data, throughout the AI Life-cycle? • How to deal with the trade-off between the accuracy and fairness of Machine Learning Algorithms? • How to address Engineering and Organizational challenges and build a culture for trust-worthy AI systems? Moderator: Megan Heath, Commercial Director for UK, UST Global Panelists: Maor Ivgi, Chief Technology Officer, Stardat Heather Dawe, UK Head of Data, UST Global Adnan Masood, Chief Architect of AI and Machine Learning, UST Global

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