Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values

Zijie J. Wang, Alex Kale, Harsha Nori, Peter Stella, Mark E. Nunnally, Duen Horng Chau, Mihaela Vorvoreanu, Jennifer Wortman Vaughan, Rich Caruana 0001. Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values. In Aidong Zhang, Huzefa Rangwala, editors, KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022. pages 4132-4142, ACM, 2022. [doi]

@inproceedings{WangKNSNCVV022,
  title = {Interpretability, Then What? Editing Machine Learning Models to Reflect Human Knowledge and Values},
  author = {Zijie J. Wang and Alex Kale and Harsha Nori and Peter Stella and Mark E. Nunnally and Duen Horng Chau and Mihaela Vorvoreanu and Jennifer Wortman Vaughan and Rich Caruana 0001},
  year = {2022},
  doi = {10.1145/3534678.3539074},
  url = {https://doi.org/10.1145/3534678.3539074},
  researchr = {https://researchr.org/publication/WangKNSNCVV022},
  cites = {0},
  citedby = {0},
  pages = {4132-4142},
  booktitle = {KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14 - 18, 2022},
  editor = {Aidong Zhang and Huzefa Rangwala},
  publisher = {ACM},
  isbn = {978-1-4503-9385-0},
}