In the second part of his video series, Christian looks at the 'dirty data' that drives the decisions behind awful algorithms.
Key learning objectives:
What are the problems with using past data?
How might dirty data be a hindrance to diversity & inclusion?
When can AI go wrong?
The Basel Committee Perspective on Operational Risk
Peter Eisenhardt • 18:32