Daniel E. Ho

Affiliation

Stanford University, Palo Alto, CA

Topic

Training Set,Aerial Images,Agricultural Census,Algorithmic Bias,Artificial Neural Network,Aspect Ratio,Auxiliary Dataset,Auxiliary Set,Background Class,Conditions Hold,Convolutional Neural Network,Demographic Attributes,Department Of Agriculture,Department Of Housing,Disparity Estimation,Disparity Values,Fair Model,Fairness Metrics,False Positive,False Positive Predictions,Filtering Step,Image Classification,Image Segmentation,Internal Revenue Service,Intersection Over Union,Learning Rate,Legal Obligations,Linear Approximation,Machine Learning,Magnitude Of Disparities,Measure Of Disparity,Measurement Methods,Measurement Techniques,Multispectral Images,National Map,Noisy Labels,Object Detection,OpenStreetMap Data,Outside Of Range,Poultry Operations,Prediction Probability,Probability Estimates,Protective Properties,Public Actors,Range Of Metrics,Rank-order Correlation,Residual Correlations,Road Network,Semantic Segmentation,Spearman Rank-order Correlation,

Biography

Daniel E. Ho received the J.D. degree from Yale Law School, New Haven, CT, USA, in 2005, and the Ph.D. degree in government from Harvard University, Cambridge, MA, USA, in 2004.
He is currently the William Benjamin Scott and Luna M. Scott Professor of Law with Stanford RegLab, Stanford Law School, Stanford, CA, USA, a Professor of Political Science, and a Senior Fellow with the Stanford Institute for Economic Policy Research, Stanford. He is also the Associate Director of the Stanford Institute for Human-Centered Artificial Intelligence, a Faculty Fellow with the Center for Advanced Study in the Behavioral Sciences, and the Director of the Regulation, Evaluation, and Governance Lab. He serves on the National Artificial Intelligence Advisory Commission, advising the White House on artificial intelligence, and as a Public Member of the Administrative Conference of the United States. He clerked for Judge Stephen F. Williams on the U.S. Court of Appeals, District of Columbia Circuit.