Deep lattice networks and partial monotonic functions
Seungil You, David Ding, Kevin Canini, Jan Pfeifer, and Maya Gupta. 2017 · 2017
Cited alongside, same era.
An interpretable model with globally consistent explanations for credit risk
Original
Chaofan Chen, Kangcheng Lin, Cynthia Rudin, Yaron Shaposhnik, Sijia Wang, and Tong Wang. 2018 · 2018
Cited alongside, same era.
The accuracy, fairness, and limits of predicting recidivism
Julia Dressel and Hany Farid. 2018 · 2018
Cited alongside, same era.
Human decisions and machine predictions
Jon Kleinberg, Himabindu Lakkaraju, Jure Leskovec, Jens Ludwig, and Sendhil Mullainathan. 2018 · 2018
Cited alongside, same era.
How artificial intelligence and machine learning can impact market design
Paul R Milgrom and Steven Tadelis. 2018 · 2018
Cited alongside, same era.
Distill-and-compare: Auditing black-box models using transparent model distillation. In Proceedings of the 2018 AAAI/ACM Conference on AI, Ethics, and Society . 303–310
Sarah Tan, Rich Caruana, Giles Hooker, and Yin Lou. 2018 · 2018
Cited alongside, same era.
Guidelines for human-AI interaction. In Proceedings of the 2019 chi conference on human factors in computing systems . 1–13
Saleema Amershi, Dan Weld, Mihaela Vorvoreanu, Adam Fourney, Besmira Nushi, Penny Collisson, Jina Suh, Shamsi Iqbal, Paul N Bennett, Kori Inkpen, et al · 2019
Cited alongside, same era.
Machine learning methods that economists should know about
Susan Athey and Guido W Imbens. 2019 · 2019
Cited alongside, same era.
Fairness-aware machine learning: Practical challenges and lessons learned. In Proceedings of the twelfth ACM international conference on web search and data mining . 834–835
Sarah Bird, Krishnaram Kenthapadi, Emre Kiciman, and Margaret Mitchell. 2019 · 2019
Cited alongside, same era.
Explainable AI in industry. In Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery & data mining . 3203–3204
Krishna Gade, Sahin Cem Geyik, Krishnaram Kenthapadi, Varun Mithal, and Ankur Taly. 2019 · 2019
Cited alongside, same era.
XAI—Explainable artificial intelligence
David Gunning, Mark Stefik, Jaesik Choi, Timothy Miller, Simone Stumpf, and Guang-Zhong Yang. 2019 · 2019
Cited alongside, same era.
Explainable AI: A brief survey on history, research areas, approaches and challenges. In CCF international conference on natural language processing and Chinese computing . Springer, 563–574
Feiyu Xu, Hans Uszkoreit, Yangzhou Du, Wei Fan, Dongyan Zhao, and Jun Zhu. 2019 · 2019
Cited alongside, same era.