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When Should AI Step Aside? Understanding Cultural Values in AI Systems

NYU Center for Data Science

CDS Faculty Fellow Umang Bhatt l eading a practical workshop on Responsible AI at Deep Learning Indaba 2023 in Accra In Uganda’s banking sector, AI models used for credit scoring systematically disadvantage citizens by relying on traditional Western financial metrics that don’t reflect local economic realities.

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Using Self-Critiquing Chains in LangChain

Heartbeat

Whether you’re building conversational agents, question-answer systems, or any AI tool, the self-critique chain offers an added layer of assurance. This feature emphasizes the commitment to responsible AI, which provides accurate answers and ensures the content adheres to broader societal values.

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Learn to Build — Towards AI Community Newsletter #1

Towards AI

-Louis Bouchard, Towards AI Co-founder & Head of Community What’s AI Weekly In this week’s What’s AI Podcast episode, Louis Bouchard interviewed Paige Bailey, Lead product manager at Google DeepMind and previously working at Microsoft GitHub building Copilot. Meme of the week!

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Definite Guide to Building a Machine Learning Platform

The MLOps Blog

Responsible AI and explainability. Responsible AI and explainability component To fully trust ML systems, it’s important to interpret these predictions. Model serving. Monitoring and observability. When certain thresholds are passed in the computed metrics, an alerting service can send a message.