Papers

3

Total Citations

18

H-Index

2

About

David Gros is a researcher at the forefront of ethical human-AI interaction, focusing on transparency and trust in conversational AI. His work critically examines how dialog systems can inadvertently deceive users through anthropomorphic language—responses that falsely imply human-like experiences, such as claiming a movie “made me cry.” Gros’s major contribution lies in identifying and mitigating this deception. He co-created the R-U-A-Robot dataset, a pioneering resource designed to help chatbots detect when users are questioning their non-human identity, enabling systems to respond honestly. His paper on this dataset (2021) and his companion work “Robots-Dont-Cry” (2022) each garnered 8 citations, establishing a foundational framework for responsible AI design. By addressing the ethical dilemma of machines simulating human emotion, Gros’s research directly impacts the development of safer, more transparent chatbots used in customer service, healthcare, and personal assistants. His work is essential reading for anyone building or studying dialog systems, as it provides both a diagnostic tool and a moral imperative: to ensure that AI never tricks users into forgetting they are talking to a machine.

Research Focus

Key Achievements

2
H-Index
3
Papers
18
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
The R-U-A-Robot Dataset: Helping Avoid Chatbot Deception by Detecting User Questions About Human or Non-Human Identity
8 citations · 2021
📈 Most Prolific Year: 2021 (2 Papers)
🤝 Key Collaborators: 5
🏛 Institutions: University of California, Davis, Columbia University

Top Papers

  1. 1
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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 16 days ago