Scholar
Su Lin Blodgett
Google Scholar ID: 8jbAkOUAAAAJ
Microsoft Research Montréal
Citations & Impact
Citations
3,928
H-index
20
i10-index
31
Publications
20
Co-authors
23
list available
Publications
Resume (English only)
Academic Achievements
- May 2024: Two papers accepted to ACL 2024 (led by Yu Lu Liu) and Findings of ACL (led by Jay Cunningham).
- Mar. 2024: Two papers accepted to NAACL 2024 on fair NLG behaviors (Lucy Li) and evolving practices around disagreement in data labeling.
- Oct. 2023: Paper on responsible AI in text summarization (Yu Lu Liu) accepted to Findings of EMNLP 2023.
- July 2023: Keynote at WOAH workshop at ACL 2023.
- June 2023: Keynote at Workshop on Algorithmic Injustice (University of Amsterdam) and panel at SPUI25.
- May 2023: Three papers accepted to ACL/Findings of ACL on fairness harms in generation (Eve Fleisig), NLP task conceptualizations (Arjun Subramonian), and prompt-based bias measurement.
- Nov. 2022: Paper on representational harms in image tagging accepted to AAAI 2023.
- June 2022: Keynotes at workshops on Language Technology for EDI and Perspectivist NLP.
- May 2022: Ethics co-chair for ACL 2022; co-organized CHI panel on responsible language technologies; paper on NLG evaluation practices (Kaitlyn Zhou) accepted to NAACL 2022.
- Dec. 2021: Named one of the 100 Brilliant Women in AI Ethics for 2022.
- Co-organizing the third HCI-NLP bridging workshop at NAACL 2024.
- Co-organizing a tutorial on human-centered evaluation of language technologies at EMNLP 2024.
Background
- Senior researcher in the Fairness, Accountability, Transparency, and Ethics in AI (FATE) group at Microsoft Research Montréal.
- Broadly interested in the social and ethical implications of natural language processing (NLP) technologies.
- Develops approaches to anticipate, measure, and mitigate harms from language technologies, with a focus on the complexities of language in social contexts.
- Supports NLP practitioners in ethical work.
- Has also worked on computational sociolinguistics, e.g., modeling language variation on social media.
