Assessing Political Prudence of Open-domain Chatbots
Yejin Bang, Nayeon Lee, Etsuko Ishii, Andrea Madotto, Pascale Fung
Abstract
Politically sensitive topics are still a challenge for open-domain chatbots. However, dealing with politically sensitive content in a responsible, non-partisan, and safe behavior way is integral for these chatbots. Currently, the main approach to handling political sensitivity is by simply changing such a topic when it is detected. This is safe but evasive and results in a chatbot that is less engaging. In this work, as a first step towards a politically safe chatbot, we propose a group of metrics for assessing their political prudence. We then conduct political prudence analysis of various chatbots and discuss their behavior from multiple angles through our automatic metric and human evaluation metrics. The testsets and codebase are released to promote research in this area.- Anthology ID:
- 2021.sigdial-1.57
- Volume:
- Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue
- Month:
- July
- Year:
- 2021
- Address:
- Singapore and Online
- Editors:
- Haizhou Li, Gina-Anne Levow, Zhou Yu, Chitralekha Gupta, Berrak Sisman, Siqi Cai, David Vandyke, Nina Dethlefs, Yan Wu, Junyi Jessy Li
- Venue:
- SIGDIAL
- SIG:
- SIGDIAL
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 548–555
- Language:
- URL:
- https://aclanthology.org/2021.sigdial-1.57
- DOI:
- 10.18653/v1/2021.sigdial-1.57
- Cite (ACL):
- Yejin Bang, Nayeon Lee, Etsuko Ishii, Andrea Madotto, and Pascale Fung. 2021. Assessing Political Prudence of Open-domain Chatbots. In Proceedings of the 22nd Annual Meeting of the Special Interest Group on Discourse and Dialogue, pages 548–555, Singapore and Online. Association for Computational Linguistics.
- Cite (Informal):
- Assessing Political Prudence of Open-domain Chatbots (Bang et al., SIGDIAL 2021)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2021.sigdial-1.57.pdf
- Code
- HLTCHKUST/chatbot-political-prudence-test