Interpretable AI and ML - Polina Mosolova

We talked about: Polina's background How common it is for PhD students to build ML pipelines end-to-end Simultaneous PhD and industry experience Support from both the academic and industry sides How common the industrial PhD setup is and how to get into one Organizational trust theory How price relates to trust How trust relates to explainability The importance of actionability Explainability vs interpretability vs actionability Complex glass box models Does the explainability of a model follow explainability? What explainable AI bring to customers and end users Can all trust be turned into KPI? Links: LinkedIn: https://www.linkedin.com/in/polina-mosolova/ Neural Additive Models paper: https://proceedings.neurips.cc/paper/2021/file/251bd0442dfcc53b5a761e050f8022b8-Paper.pdf Neural Basis Model paper: https://arxiv.org/pdf/2205.14120.pdf Interpretable Feature Spaces paper: https://kdd.org/exploration_files/vol24issue1_1._Interpretable_Feature_Spaces_revised.pdf