Causal Learning for Socially Responsible AI

Cheng, Lu; Mosallanezhad, Ahmadreza; Sheth, Paras; Liu, Huan

doi:10.24963/ijcai.2021/598

Causal Learning for Socially Responsible AI

Lu Cheng, Ahmadreza Mosallanezhad, Paras Sheth, Huan Liu

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Survey Track. Pages 4374-4381.

https://doi.org/10.24963/ijcai.2021/598

Keywords

Uncertainty in AI: General
Machine learning: General
Multidisciplinary topics and applications: General
Humans and AI: General

Abstract

There have been increasing concerns about Artificial Intelligence (AI) due to its unfathomable potential power. To make AI address ethical challenges and shun undesirable outcomes, researchers proposed to develop socially responsible AI (SRAI). One of these approaches is causal learning (CL). We survey state-of-the-art methods of CL for SRAI. We begin by examining the seven CL tools to enhance the social responsibility of AI, then review how existing works have succeeded using these tools to tackle issues in developing SRAI such as fairness. The goal of this survey is to bring forefront the potentials and promises of CL for SRAI.

Lu Cheng, Ahmadreza Mosallanezhad, Paras Sheth, and Huan Liu. 2021. Causal Learning for Socially Responsible AI. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 4374–4381. https://doi.org/10.24963/ijcai.2021/598

@inproceedings{ijcai2021p598,
  title     = {Causal Learning for Socially Responsible AI},
  author    = {Cheng, Lu and Mosallanezhad, Ahmadreza and Sheth, Paras and Liu, Huan},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Prof. Zhi-Hua Zhou},
  pages     = {4374--4381},
  year      = {2021},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2021/598},
  url       = {https://doi.org/10.24963/ijcai.2021/598},
}

TY  - CPAPER
TI  - Causal Learning for Socially Responsible AI
AU  - Cheng, Lu
AU  - Mosallanezhad, Ahmadreza
AU  - Sheth, Paras
AU  - Liu, Huan
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 4374
EP  - 4381
DO  - 10.24963/ijcai.2021/598
UR  - https://doi.org/10.24963/ijcai.2021/598
ER  -