ML Anthology

AI Explainability 360: Impact and Design

Vijay Arya, Rachel K. E. Bellamy, Pin-Yu Chen, Amit Dhurandhar, Michael Hind, Samuel C. Hoffman, Stephanie Houde, Q. Vera Liao, Ronny Luss, Aleksandra Mojsilovic, Sami Mourad, Pablo Pedemonte, Ramya Raghavendra, John T. Richards, Prasanna Sattigeri, Karthikeyan Shanmugam, Moninder Singh, Kush R. Varshney, Dennis Wei, Yunfeng Zhang
AAAI 2022 pp. 12651-12657
doi:10.1609/AAAI.V36I11.21540 /aaai/2022/arya2022aaai-ai/

Abstract

As artificial intelligence and machine learning algorithms become increasingly prevalent in society, multiple stakeholders are calling for these algorithms to provide explanations. At the same time, these stakeholders, whether they be affected citizens, government regulators, domain experts, or system developers, have different explanation needs. To address these needs, in 2019, we created AI Explainability 360, an open source software toolkit featuring ten diverse and state-of-the-art explainability methods and two evaluation metrics. This paper examines the impact of the toolkit with several case studies, statistics, and community feedback. The different ways in which users have experienced AI Explainability 360 have resulted in multiple types of impact and improvements in multiple metrics, highlighted by the adoption of the toolkit by the independent LF AI & Data Foundation. The paper also describes the flexible design of the toolkit, examples of its use, and the significant educational material and documentation available to its users.

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Cite

Text

Arya et al. "AI Explainability 360: Impact and Design." AAAI Conference on Artificial Intelligence, 2022. doi:10.1609/AAAI.V36I11.21540

Markdown

[Arya et al. "AI Explainability 360: Impact and Design." AAAI Conference on Artificial Intelligence, 2022.](https://mlanthology.org/aaai/2022/arya2022aaai-ai/) doi:10.1609/AAAI.V36I11.21540

BibTeX

@inproceedings{arya2022aaai-ai,
  title     = {{AI Explainability 360: Impact and Design}},
  author    = {Arya, Vijay and Bellamy, Rachel K. E. and Chen, Pin-Yu and Dhurandhar, Amit and Hind, Michael and Hoffman, Samuel C. and Houde, Stephanie and Liao, Q. Vera and Luss, Ronny and Mojsilovic, Aleksandra and Mourad, Sami and Pedemonte, Pablo and Raghavendra, Ramya and Richards, John T. and Sattigeri, Prasanna and Shanmugam, Karthikeyan and Singh, Moninder and Varshney, Kush R. and Wei, Dennis and Zhang, Yunfeng},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {2022},
  pages     = {12651-12657},
  doi       = {10.1609/AAAI.V36I11.21540},
  url       = {https://mlanthology.org/aaai/2022/arya2022aaai-ai/}
}