Brief Perspective on Key Terms and Ideas in Responsible AI
April 2, 2020 Data Science Explainable AI Machine Learning Responsible AIINTRODUCTION As fields like explainable AI and ethical AI have continued to develop in academia and industry, we have seen a litany of new methodologies that can be applied to improve our ability to trust and understand our machine learning and deep learning models. As a result of this, we’ve seen several buzzwords emerge. In […]
Modelling Currently Infected Cases of COVID-19 Using H2O Driverless AI
March 30, 2020 AI4Good Explainable AI GLM H2O Driverless AI Healthcare Machine Learning Machine Learning Interpretability Responsible AI Technical Time SeriesIn response to the wake of the pandemic called COVID-19, H2O.ai organized a panel discussion to cover AI in healthcare, and some best practices to put in place in order to achieve better outcomes. The attendees had many questions that we did not have the time to cover thoroughly throughout the course of that 1-hour […]
Summary of a Responsible Machine Learning Workflow
March 20, 2020 Data Science Deep Learning Machine Learning Machine Learning Interpretability Neural Networks Python Responsible AIA paper resulting from a collaboration between H2O.AI and BLDS, LLC was recently published in a special “Machine Learning with Python” issue of the journal, Information (https://www.mdpi.com/2078-2489/11/3/137). In “A Responsible Machine Learning Workflow with Focus on Interpretable Models, Post-hoc Explanation, and Discrimination Testing,” coauthors, Navdeep Gill, Patrick Hall, Kim Montgomery, and Nicholas Schmidt compare model accuracy […]