Dallas Card
Email: dalc@umich.edu
Office: North Quad 3421
GitHub,
Twitter,
Bluesky,
Blog
Google Scholar,
ORCiD
I am an assistant professor in the
School of Information at the University of Michigan. Before that, I was a postdoctoral researcher in the
Stanford NLP Group and the
Stanford Data Science Institute.
I received my Ph.D. from the
Machine Learning Department at Carnegie Mellon University, where I was advised by
Noah Smith.
My research centers on making machine learning more reliable and responsible, and on using machine learning and natural language processing to learn about society from text.
For prospective Ph.D. students
I am open to advising new Ph.D. students starting in Fall 2024. I am especially interested in students who are eager to work at the intersection of NLP, statistics, and historical or cultural analytics.
If you are interested in working with me, please apply to the University of Michigan School of Information and list me as a potential advisor. This is the best way to ensure that I will see your application.
For prospective postdocs
I would be interested in hiring a postdoc for Fall 2024 to work on knowledge infrastuctures, especialy if you would be eligble for the MIDAS Schmidt AI in Science postdoc program. If interested, please email me directly.
Updates
- October 2023: Our new paper on media storms has been accepted to Findings of EMNLP (preprint coming soon)
- October 2023: I will be attending the Workshop on Operationalizing the Measure Function of the NIST AI RMF in Washington, October 16-17th
- July 2023: I will be speaking about evaluation challenges at the MIDAS workshop on Generative AI for Research, July 25-26th
- July 2023: I will be attending the CASMI workshop on Sociotechnical Approaches to Measurement and Validation for Safety in AI, July 18-19th
- July 2023: I will be attending ACL 2023 in Toronto, July 9-14th, where I will be presenting a paper on Semantic Change Detection
- June 2023: I will be attending FAccT 2023 in Chicago, June 12-15th
- May 2023: I will be giving a keynote on May 16th at the MIDAS Forum on Building Ethical and Trustworthy AI
- May 2023: I will be speaking on May 12th about ChatGPT at the Ann Arbor District Library with Rada Mihalcea!
- May 2023: I will be presenting at the Cambridge Language Technology Lab seminar on May 4th.
- March 2023: Congratulations to my PhD student Lavinia Dunagan on being awarded an NSF GRFP!!
Current Ph.D. Students
Selected Publications
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Substitution-based Semantic Change Detection using Contextual Embeddings
Dallas Card
Association for Computational Linguistics (ACL), 2023
[code] [bib]
-
Whose Language Counts as High Quality? Measuring Language Ideologies in Text Data Selection
Suchin Gururangan, Dallas Card, Sarah K. Dreier, Emily K. Gade, Leroy Z. Wang, Zeyu Wang, Luke Zettlemoyer, Noah A. Smith
Empirical Methods in Natural Language Processing (EMNLP), 2022
[code] [bib]
-
Computational analysis of 140 years of US political speeches reveals more positive but increasingly polarized framing of immigration
Dallas Card, Serina Chang, Chris Becker, Julia Mendelsohn, Rob Voigt, Leah Boustan, Ran Abramitzky, Dan Jurafsky
Proceedings of the National Academy of Sciences 119(31), 2022
[data and code] [bib]
-
The Values Encoded in Machine Learning Research
Abeba Birhane, Pratyusha Kalluri, Dallas Card, William Agnew, Ravit Dotan, and Michelle Bao
ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2022
[data and code] [bib]
[Distinguished Paper Award]
-
Modular Domain Adaptation
Junshen Chen, Dallas Card, Dan Jurafsky
In Findings of the Association of Computational Linguistics (ACL), 2022
[blog post] [code] [bib]
-
Problems with Cosine as a Measure of Embedding Similarity for High Frequency Words
Kaitlyn Zhou, Kawin Ethayarajh, Dallas Card, Dan Jurafsky
Association for Computational Linguistics (ACL), 2022
[bib]
-
On the Opportunities and Risks of Foundation Models
Rishi Bommasani, Drew A. Hudson, Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S. Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, Erik Brynjolfsson, Shyamal Buch, Dallas Card, et al.
arXiv:2108.07258, 2021
[bib] [VentureBeat]
-
Expected Validation Performance and Estimation of a Random Variable's Maximum
Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, Noah A. Smith
Findings of Empirical Methods in Natural Language Processing (EMNLP), 2021
[bib]
-
Causal Effects of Linguistic Properties
Reid Pryzant, Dallas Card, Dan Jurafsky, Victor Veitch, and Dhanya Sridhar
North American Chapter of the Association for Computational Linguistics (NAACL), 2021
[bib]
-
With Little Power Comes Great Responsibility
Dallas Card, Peter Henderson, Urvashi Khandelwal, Robin Jia, Kyle Mahowald, and Dan Jurafsky
Empirical Methods in Natural Language Processing (EMNLP), 2020
[code] [bib]
-
Detecting Stance in Media On Global Warming
Yiwei Luo, Dallas Card, and Dan Jurafsky
Findings of Empirical Methods in Natural Language Processing (EMNLP), 2020
[code] [bib]
-
Explain like I am a Scientist: The Linguistic Barriers of Entry to r/science
Tal August, Dallas Card, Gary Hsieh, Noah A. Smith, and Katharina Reinecke
Human Factors in Computing Systems (CHI), 2020
[bib]
-
On Consequentialism and Fairness
Dallas Card and Noah A. Smith
Frontiers in Artificial Intelligence, 2020
[bib]
-
Show Your Work: Improved Reporting of Experimental Results
Jesse Dodge, Suchin Gururangan, Dallas Card, Roy Schwartz, and Noah A. Smith
Empirical Methods in Natural Language Processing (EMNLP), 2019
[code] [bib] [WIRED]
-
Variational Pretraining for Semi-supervised Text Classification
Suchin Gururangan, Tam Dang, Dallas Card, and Noah A. Smith
Association for Computational Linguistics (ACL), 2019
[code] [bib]
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The Risk of Racial Bias in Hate Speech Detection
Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi, and Noah A. Smith
Association for Computational Linguistics (ACL), 2019
[bib] [VOX]
-
Deep Weighted Averaging Classifiers
Dallas Card, Michael Zhang, and Noah A. Smith
ACM Conference on Fairness, Accountability, and Transparency (FAccT), 2019
[code] [blog post] [bib]
-
Neural Models for Documents with Metadata
Dallas Card, Chenhao Tan, and Noah A. Smith
Association for Computational Linguistics (ACL), 2018
[code] [tutorial] [bib]
-
Friendships, Rivalries, and Trysts: Characterizing Relations between Ideas in Texts
Chenhao Tan, Dallas Card, and Noah A. Smith
Association for Computational Linguistics (ACL), 2017
[blog post] [bib]
-
Analyzing Framing through the Casts of Characters in the News
Dallas Card, Justin H. Gross, Amber E. Boydstun, and Noah A. Smith
Empirical Methods in Natural Language Processing (EMNLP), 2016
[bib]
-
The Media Frames Corpus: Annotations of Frames Across Issues
Dallas Card, Amber E. Boydstun, Justin H. Gross, Philip Resnik, and Noah A. Smith
Association for Computational Linguistics (ACL), 2015
[bib]
Recent Professional Service
- FAccT steering committee member (2023)
- Co-organizer of the NLP+CSS workshop, to be held at NAACL 2024
- Area Chair for ACL (2023), ACL Rolling Review (2023), FAccT (2023), NAACL (2021)
- Reviewer for ACL Rolling Review (2022, 2021), ACL (2022, 2021), EMNLP (2022, 2021), NAACL (2022, 2021) TACL (2023, 2022, 2021), EMNLP Ethics reviewer (2023, 2022, 2021), FAccT (2022), AAAI (2022, 2021), AIES (2023), The Web Conference (2023), Philosophy and Technology (2021), PeerJ (2021)
About me
I am an occasional guest on
The Reality Check podcast. You can hear me in episodes
#466 (biased algorithms),
#382 (deep learning),
#362 (Simpson's paradox), and
#227 (fMRI and vegetative states).