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
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