The field of Responsible AI recently received a lot more attention, especially after the release of many Generative AI systems—such as ChatGPT. This interest has also been compounded by the incoming and proposed regulations across the world, demanding for more transparency and accountability of models. Yet most machine learning practitioners aren’t sure where to begin or how to approach this important field. In this short, one-week class, we will give a brief introduction to the field, see its main challenge and work through case studies based on real-world scenarios faced by today's leading practitioners.
Course taught by expert instructors
UC Berkeley Tech Policy Fellow & AI Fellow, National Institute of Standards and Technology (NIST) &
Luca Belli is a Visiting NIST AI Fellow, a UC Berkeley Tech Policy Fellow and the founder of Sator Labs. At NIST he’s co-leading the Red Team effort for the Generative AI Public working group and thinking about socio-technical evaluations for Recommender Systems. Luca was also selected as an expert by the European Commission, to help with the delegated act of Article 40 of the DSA. Previously he was the co-founder and Research Lead for Twitter's Machine learning Ethics, Transparency and Accountability (META) team where he guided industry leading approaches for responsible ML practices and product changes. Before that he operated as a Data Scientist and Machine Learning Engineer at Conversant and WolframAlpha. His research interests lie at the intersection of feedback loops, algorithmic amplification, and algorithmic audits.
Learn and apply skills with real-world projects.
Anyone who is a stakeholder in a Machine learning pipeline, including but not limited to data scientist, machine learning engineers, PMs, and folks from the legal and Trust and Safety teams.
Try these prep courses first
- What is Responsible AI (RAI) and why is so important right now
- A brief history of the field and how we got here
- Where—and how—we should embed RAI in the ML lifecycle
- By exploring many real world examples, learn some of the concerns and solutions that have been adopted
- Understand why Recommender Systems are more complicated
- How to think about RAI in the Generative AI and LLM world
- How the new (proposed and passed) regulations might impact the field
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Accelerate your learning with projects that mirror the work done at industry-leading tech companies. Put your skills to the test and start applying them today.
Flexible schedule for busy professionals
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Each course comes with a certificate for learners to add to their resume.
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