Top Tweets for #algoexpla17
Neat to see a conference on humans ability to #understand and interpret #MachineLearning and #Artificialintelligence models #algoexpla17 https://t.co/A1YVh7GMRq
Do we need legislative oversight for algorithmic decisions?
Recap — @ILI_NYU's #algoexpla17: https://t.co/bGoHDv4wku #algos
Now on TAP — Recapping @ILI_NYU's Algorithms and Explanations Conference: https://t.co/bGoHDv4wku | @nyulaw #algoexpla17 #transparency
Videos and slides from our Algorithms and Explanations conference are now available: https://t.co/0JuUOKhStj #algoexpla17
Chief Dean Esserman "the average cop couldn’t care less about #predictivepolicing. Stats don't affect their promotion" #algoexpla17
"Judges should squarely feel the burden of caging a human being, the [Compass] algorithm gives them an out." Paul Rifejl @ #algoexpla17
Andrea Roth rightly notes that there is a black box problem with human experts too #algoexpla17
Panel #7: @julius_adebayo, Paul Rifelj, & Andrea Roth on algorithmic explainability in the courts, moderated by @levendowski #algoexpla17
"Transparency is about the what behind an algorithm and explanation is about the how of an algorithmic decision" @ndiakopoulos #algoexpla17
#algoexpla17 transparency is different than explanation
"Businesses are concerned about the high costs of Information production for algorithmic transparency" @ndiakopoulos #algoexpla17
#algoexpla17 levels at which we could disclose information about automated systems
"Our role is to help our audience to navigate the complex, polluted information environment" says @gilgul #algoexpla17
Panel #7: @gilgul, @ndiakopoulos, & Brad Greenberg on algorithms explainability in the media, moderated by Madelyn Sanfilippo #algoexpla17
#Epistemicsclerosis is a cognitive bias: relationship btw input/output of a ML model is neither true nor stable. F Cabitza at #algoexpla17
Does current ML research empower a higher awareness of the uncertainty intrinsic to medicine, or rather hinders it? F Cabitza #algoexpla17
#algoexpla17 reading list ++
#algoexpla17 some historical notes on deep learning
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