The once-nascent field of explainable AI has been gaining traction as societies and industries grapple with the opaque nature of algorithms, and how to explain their outputs. While there are myriad benefits to AI/ML applications, there is also risk of bias on the communities they are intended to serve. In this talk, three machine learning experts will offer perspectives on the importance of explainability, ethics, fairness and responsibility in the field.



Programming descriptions are generated by participants and do not necessarily reflect the opinions of SXSW.