The Data Exchange Podcast: Alejandro Saucedo on explainability, MLOps, adversarial robustness, and privacy.
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In this episode of the Data Exchange I speak with Alejandro Saucedo, Engineering Director at Seldon, a startup building tools for productionizing machine learning. Alejandro is also Chief Scientist at The Institute for Ethical AI & Machine Learning, a UK-based research center that conducts “research into processes and frameworks that support the responsible development, deployment and operation of machine learning systems”.
Our conversation covered Alejandro’s work at both Seldon and the Institute for Ethical AI & Machine Learning:
- We discussed topic areas that the Institute focuses on including explainability, MLOps, adversarial robustness, and privacy-preserving machine learning
- We covered some of the recent output from the Institute including the machine learning maturity model, their open source explainable AI library, their AI-RFX Procurement Framework, and their list of Principles for Responsible AI
- We also discussed his role at Seldon, and areas that Seldon has been focused on.
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[Image: “Tower of London Poppies 1” by Dean Wampler; used with permission.]