How to use Responsible AI for financial services

A common issue with most educational content on the responsible use of AI is that they are too theoretical and text-heavy. While these resources do contain valuable ideas, the format can be less engaging and digestable for practitioners. In the Responsible AI masterclass I conducted recently for learners from the IBFSG - The Institute of Banking & Finance Singapore - Technology in Finance Immersion Programme (TFIP) program, I shifted the focus towards practical, hands-on learning within the context of financial services. I introduced three open-source libraries, each targeting a different aspect: fairness and transparency diagnosis, debiasing algorithms, and guardrails for large language models (LLMs). ① 𝐕𝐞𝐫𝐢𝐭𝐚𝐬 (by Monetary Authority of Singapore (MAS) and finance industry partners): Provides us with the capability to easily assess fairness and transparency of machine learning models ② 𝐀𝐈 𝐅𝐚𝐢𝐫𝐧𝐞𝐬𝐬 360 (by IBM): Allows us to readily detect and mitigate bias in machine learning models across the AI application lifecycle ③ 𝐍𝐞𝐌𝐨 𝐆𝐮𝐚𝐫𝐝𝐫𝐚𝐢𝐥𝐬 (by NVIDIA): Enables us to easily add programmable guardrails to LLM-based conversational systems I have publicly released the lesson Colab notebook on the Veritas toolkit, available here: https://lnkd.in/geRhwwKP My thoughts on 𝐕𝐞𝐫𝐢𝐭𝐚𝐬: - Great starting point for understanding and implementing the concepts of fairness evaluation (easier to get started than the AIF360 toolkit which has poor integration with sklearn) - However, it is >1 year since the last commit (pretty much stale) and the documentation can be much improved (prompting me to develop the Colab notebook) I hope this is useful for anyone conducting future lessons on responsible AI. I’m also eager to hear from others in the field: Are there other resources you've found effective for applying responsible AI principles in practical settings? Link to GitHub repo: https://lnkd.in/gxmgYdT8 #datascience #machinelearning #responsibleAI #generativeai #bcg #artificialintelligence #rai RISE by BCG U

  • data science machine learning ds ml responsible ai artificial intelligence generative ai genai kenneth leung bcg deep learning dl rai data scientist tech kennethleungty llm nemo guardrails veritas mas ai fairness transparency ethics

Kenneth Leung to teach with learners in mind is indeed important. Kudos 👏

Thanks for sharing! This is very useful! Bookmarking this for my future learners!

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