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ASE 2020
Mon 21 - Fri 25 September 2020 Melbourne, Australia
Wed 23 Sep 2020 00:40 - 00:50 at Kangaroo - Software Engineering for AI (1) Chair(s): Song Wang

Machine learning software is being used in many applications (finance, hiring, admissions, criminal justice) having a huge social impact. But sometimes the behavior of this software is biased and it shows discrimination based on some sensitive attributes such as sex, race etc. Prior works concentrated on finding and mitigating bias in ML models. A recent trend is using instance-based model agnostic explanation methods such as LIME[1] to find out bias in the model prediction. Our work concentrates on finding shortcomings of current bias measures and explanation methods. We show how our proposed method based on K nearest neighbors can overcome those shortcomings and find the underlying bias of black-box models. Our results are more trustworthy and helpful for the practitioners. Finally, We describe our future framework combining explanation and planning to build fair software

Wed 23 Sep

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00:00 - 01:00
Software Engineering for AI (1)NIER track / Research Papers at Kangaroo
Chair(s): Song Wang York University, Canada
Multiple-Boundary Clustering and Prioritization to Promote Neural Network Retraining
Research Papers
Weijun Shen Nanjing University, Yanhui Li Department of Computer Science and Technology, Nanjing University, Lin Chen Nanjing University, YuanLei Han Nanjing University, Yuming Zhou Nanjing University, Baowen Xu State Key Laboratory for Novel Software Technology, Nanjing University
MARBLE: Model-Based Robustness Analysis of Stateful Deep Learning Systems
Research Papers
Xiaoning Du Nanyang Technological University, Yi Li Nanyang Technological University, Singapore, Xiaofei Xie Nanyang Technological University, Lei Ma Kyushu University, Yang Liu Nanyang Technological University, Singapore, Jianjun Zhao Kyushu University
Making Fair ML Software using Trustworthy Explanation
NIER track
Joymallya Chakraborty North Carolina State University, USA, Kewen Peng North Carolina State University, Tim Menzies North Carolina State University, USA
Link to publication DOI Pre-print Media Attached