DPO Presentation - Transparency
IEEE BigData 2020 Presentation
Presentation of our paper at the 2020 IEEE International Conference on Big Data. We compared our ML Interpretability method called MASHAP with the most well-known counterpart, i.e. LIME. Our experiments showed that MASHAP, while achieves similar consistency, is much faster than LIME. (Paper title: “Evaluating MASHAP as a faster alternative to LIME for model agnostic machine learning interpretability”).
Challenges we face in order to build trust
Although the trustworthiness of an algorithmic system is undoubtedly a desired property, there are several challenges that demote it to a nice-to-have feature instead of a priority one.