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• Crowdsourced PAC Learning under Classification Noise

  Shelby Heinecke, Lev Reyzin

  41-49

  2019-10-28

• Human Evaluation of Models Built for Interpretability

  Isaac Lage, Emily Chen, Jeffrey He, Menaka Narayanan, Been Kim, Samuel J. Gershman, Finale Doshi-Velez

  59-67

  2019-10-28

• What You See Is What You Get? The Impact of Representation Criteria on Human Bias in Hiring

  Andi Peng, Besmira Nushi, Emre Kıcıman, Kori Inkpen, Siddharth Suri, Ece Kamar

  125-134

  2019-10-28

• AI-Based Request Augmentation to Increase Crowdsourcing Participation

  Junwon Park, Ranjay Krishna, Pranav Khadpe, Li Fei-Fei, Michael Bernstein

  115-124

  2019-10-28

• Fair Work: Crowd Work Minimum Wage with One Line of Code

  Mark E. Whiting, Grant Hugh, Michael S. Bernstein

  197-206

  2019-10-28

• The Effects of Meaningful and Meaningless Explanations on Trust and Perceived System Accuracy in Intelligent Systems

  Mahsan Nourani, Samia Kabir, Sina Mohseni, Eric D. Ragan

  97-105

  2019-10-28

• Beyond Accuracy: The Role of Mental Models in Human-AI Team Performance

  Gagan Bansal, Besmira Nushi, Ece Kamar, Walter S. Lasecki, Daniel S. Weld, Eric Horvitz

  2-11

  2019-10-28

• Learning to Predict Population-Level Label Distributions

  Tong Liu, Akash Venkatachalam, Pratik Sanjay Bongale, Christopher M. Homan

  68-76

  2019-10-28