Venue: Imperial College London
1 day course, 4 September 2025, 09:00 - 17:00
Learning objectives:
- Issues of Bias and Fairness in machine learning models and AI systems.
- Applying statistical and computational methods to detect and mitigate AI Bias.
- Adopting a sub-population harm detection approach for legal compliance.
Topics
- Bias in data: source, detection and mitigation.
- AI Bias detection and tools.
- SPAVA: A novel approach to detecting bias in sub-populations.
- Adhering to the Equality Act 2010 for protected characteristics in deploying AI.
Audience
This masterclass is designed for data scientists, business analysts and project managers who are have already attended the AI assurance course and want to know more about bias in AI systems. Attendees should have some familiarity in python coding at least to entry level. We will provide certification of completion of AI Assurance Masterclass.
Course format
Participants will explore various forms of bias and discrimination in AI, along with a novel approach to detecting accuracy bias in sub-populations. We will also discuss strategies for mitigating these risks to ensure fair and responsible AI deployment. The masterclass combines lectures, hands-on workshops, and case studies to provide practical approaches to adopt an AI assurance approach back in the workplace. Participants will engage in group discussions and projects to reinforce learning and encourage collaboration. We are also delighted to have subject matter experts including Professor David Hand (Imperial College London) and Dr Mark Kennedy (Data Science Institute, Imperial College London) providing personal insights into topics such as statistical bias metrics and how to operationalise AI bias detection.
Prices
- OR Society Member £495 + VAT
- Non-Member £625 + VAT
- Student Member £370 + VAT
- For group booking discounts please contact [email protected]
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Responsible AI Masterclass (2 Days)