Responsible and Explainable AI - Supreet Kaur

We talked about: Supreet’s background Responsible AI Example of explainable AI Responsible AI vs explainable AI Explainable AI tools and frameworks (glass box approach) Checking for bias in data and handling personal data Understanding whether your company needs certain type of data Data quality checks and automation Responsibility vs profitability The human touch in AI The trade-off between model complexity and explainability Is completely automated AI out of the question? Detecting model drift and overfitting How Supreet became interested in explainable AI Trustworthy AI Reliability vs fairness Bias indicators The future of explainable AI About DataBuzz The diversity of data science roles Ethics in data science Conclusion Links:  LinkedIn: https://www.linkedin.com/in/supreet-kaur1995/ Databuzz page: https://www.linkedin.com/company/databuzz-club/ Medium Blog Page: https://medium.com/@supreetkaur_66831 ML Zoomcamp: https://github.com/alexeygrigorev/mlbookcamp-code/tree/master/course-zoomcamp Join DataTalks.Club: https://datatalks.club/slack.html Our events: https://datatalks.club/events.html