Conversational AI: Social and Ethical Considerations
By Elayne Ruane, Abeba Birhane, Anthony Ventresque. 2019
114 citations recorded by the source corpus.
Subfields: Natural Language Processing, Safety, Robustness & Interpretability
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Natural Language Processing
In Safety, Robustness & Interpretability
- Kai-Wei Chang
- Dirk Hovy
- Emily Sheng
- Nanyun Peng
- Su Lin Blodgett
- Y-Lan Boureau
- Premkumar Natarajan
- Hal Daumé Iii
Citations in the corpus
- Language (Technology) is Power: A Critical Survey of “Bias” in NLP (2020, background): “…(2019); James-Sorenson and Alvarez-Melis (2019); Kurita et al. (2019); Mayfield et al. (2019); Pujari et al. (2019); Romanov et al. (2019); Ruane et al. (2019); Sedoc and Ungar (2019); Sun et al. (2019); Zmigrod et al. (2019); Hutchinson et al. (2020); Papakyriakopoulos et al. (2020);…”
- Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling (2021, background): “Trust and relationships In order to maintain trust, Ruane et al. (2019) emphasize the importance of transparency concerning agents’ non-human, automatic status.”
- SafetyKit: First Aid for Measuring Safety in Open-domain Conversational Systems (2022, background): “In the first scenario, there is a lack of transparency concerning the agent’s non-human, automatic status (Ruane et al., 2019; European Commission).”
- “Nice Try, Kiddo”: Investigating Ad Hominems in Dialogue Responses (2021, background): “Ruane et al. (2019) caution about harms that can result from using conversational systems and propose striving for trust and transparency; Roller et al. (2020) suggest techniques for chatbot safety.”
- Role play with large language models (2023, background): “This puts the user at risk of all sorts of emotional manipulation 16 .”