Maarten Sap (he/him)

Positions

| | | | ------------------------------------------------------------ | -------------: | | **Carnegie Mellon University**: Language Technologies Institute | | | Assistant Professor | 2022 – present | | **Allen Institute for AI** | | | Visiting Research Scientist | 2022 – present | | Postdoctoral Researcher / Young Investigator | 2021 – 2022 | | Research Intern | 2018 – 2019 | | **Microsoft Research** | | | Research Intern | 2019 |

Education

| | | | ------------------------------------------------------------ | ----------: | | **University of Washington**: Paul G. Allen School of Computer Science & Engineering | 2015 – 2022 | | PhD in Computer Science & Engineering, research focus on Natural Language Processing | | | advised by Yejin Choi & Noah Smith | | | Thesis: [Positive AI with Social Commonsense Models](pdfs/sap2021positiveAIwithSocialCommonsenseModels.pdf) | | | **École Polytechnique Fédérale de Lausanne**: School of Computer and Communication Sciences | 2010 – 2014 | | BS in Communications and Information Systems | |

Advising

### PhD & MLT students | | | | | ------------------------------------------------------------ | ------- | --------------------: | | Joel Mire he/him | LTI MLT | 09/2023–present | | Jimin Mun she/her | LTI PhD | 09/2022–present | | [Akhila Yerukola](https://akhila-yerukola.github.io/) she/her | LTI PhD | 09/2022–present | | [Xuhui Zhou](https://xuhuizhou.github.io/) he/him | LTI PhD | 09/2022–present | ### Research Interns & Research Masters | | | | | ------------------------------------------------------------ | ------------------- | --------------------: | | [Kaitlyn Zhou](https://cs.stanford.edu/~katezhou/) she/her | AI2 Research Intern | 06/2023–present | | [Ashutosh Baheti](https://abaheti95.github.io/) he/him | AI2 Research Intern | 09/2022–present | | [Jocelyn Chen](https://jocelynshen.com/) she/her (*primarily advised by Cynthia Breazeal*) | MIT Media Lab | 09/2022–present | | [Yiming Zhang](https://y0mingzhang.github.io/) he/him (*co-advised with [Sherry Tongshuang Wu]()*) | UChicago MS | 09/2022–09/2023 | | [Athiya Deviyani](https://www.athiyadeviyani.com/) she/her | LTI MSAII | 09/2022–09/2023 | | [Julia Mendelsohn](https://juliamendelsohn.github.io/) she/her | AI2 Research Intern | 06/2022–01/2023 | | [Sebastin Santy](http://sebastinsanty.com/) he/him | AI2 Research Intern | 06/2022–01/2023 | ### Undergraduates & Professional Masters | | | | | ------------------------------------------------------------ | ------------------- | --------------------: | | Sravani Nanduri she/her (*co-advised with Liwei Jiang*) | UW CSE BS | 09/2021–10/2022 | | [Skyler Hallinan](https://skylerhallinan.com/) he/him | UW CSE BS | 01/2021–08/2022 | | Zhilin Wang he/him | UW CLMS | 01/2021–09/2021 | | Michelle Ma she/her (*co-advised with Hannah Rashkin*) | UW CSE BS | 09/2019–12/2020 | | Sam Gehman he/him | UW CSE MS | 09/2019–07/2020 | | Aishwarya Nirmal she/her | UW CSE MS | 01/2018–06/2019 | | Kenta Takatsu he/him | Cornell BS | 07/2018–03/2019 | | [Zachary Horvitz](https://zacharyhorvitz.github.io/) he/him (*co-advised with Antoine Bosselut*) | AI2 Research Intern | 07/2018–03/2019 | | Sarah Yu she/her | UW CSE BS | 03/2018–06/2018 | | Lanhao Wu he/him (*co-advised with Saadia Gabriel*) | UW CSE BS | 03/2018–06/2018 | | Boyan Li he/him (*co-advised with Saadia Gabriel*) | UW CSE BS | 01/2018–06/2018 | | Amy Shah she/her (*co-advised with Elizabeth Clark*) | UW CSE BS | 09/2017–06/2018 | | [Emily Allaway](https://emilyallaway.github.io/) she/her (*co-advised with Hannah Rashkin*) | UW CSE BS | 07/2017–06/2018 | | Marcela Cindy Prasetio she/her (*co-advised with Hannah Rashkin*) | UW CSE BS | 01/2016–06/2017 |

Publications

Journal

  1. Maarten Sap, Anna Jafarpour, Yejin Choi, Noah A. Smith, James W. Pennebaker & Eric Horvitz (2022) Quantifying the narrative flow of imagined versus autobiographical stories. PNAS.
  2. Gregory Park, H Andrew Schwartz, Maarten Sap, Margaret L Kern, Evan Weingarten, Johannes C Eichstaedt, Jonah Berger, David J Stillwell, Michal Kosinski, Lyle H Ungar & Martin E P Seligman (2017) Living in the Past, Present, and Future: Measuring Temporal Orientation with Language. Journal of Personality.
  3. Margaret L Kern, Gregory Park, Johannes C Eichstaedt, H Andrew Schwartz, Maarten Sap, Laura K, Smith & Lyle H Ungar (2016) Gaining Insights From Social Media Language: Methodologies and Challenges. Psychological Methods.
  4. Johannes C Eichstaedt, H Andrew Schwartz, Margaret L Kern, Gregory Park, Darwin R Labarthe, Raina M Merchant, Sneha Jha, Megha Agrawal, Lukasz A Dziurzynski, Maarten Sap, Christopher Weeg, Emily Larson, Lyle H Ungar & Martin E P Seligman (2015) Psychological Language on Twitter Predicts County-level Heart Disease Mortality. Psychological Science 26(2). SAGE Publications. 159--169.
  5. Charlene A Wong, Maarten Sap, Hansen Andrew Schwartz, Robert Town, Tom Baker, Lyle Ungar & Raina M Merchant (2015) Twitter Sentiment Predicts Affordable Care Act Marketplace Enrollment. Journal of Medical Internet Research 17(2). JMIR Publications Inc..
  6. Raina M. Merchant, Yoonhee P. Ha, Charlene A. Wong, H. Andrew Schwartz, Maarten Sap, Lyle H. Ungar & David A. Asch (2014) The 2013 US Government Shutdown (#Shutdown) and Health: An Emerging Role for Social Media. American Journal of Public Health 2014. e1--e3.

Conference

  1. Xuhui Zhou, Hao Zhu, Akhila Yerukola, Thomas Davidson, Jena D. Hwang, Swabha Swayamdipta & Maarten Sap (2023) COBRA Frames: Contextual Reasoning about Effects and Harms of Offensive Statements. Findings of ACL.
  2. Julia Mendelsohn, Ronan Le Bras, Yejin Choi & Maarten Sap (2023) From Dogwhistles to Bullhorns: Unveiling Coded Rhetoric with Language Models. ACL.
  3. Sebastin Santy*, Jenny T. Liang*, Ronan Le Bras, Katharina Reinecke & Maarten Sap (2023) NLPositionality: Characterizing Design Biases of Datasets and Models. ACL.
  4. Skyler Hallinan, Alisa Liu, Yejin Choi & Maarten Sap (2023) Detoxifying Text with MaRCo: Controllable Revision with Experts and Anti-Experts. ACL.
  5. Hyunwoo Kim, Youngjae Yu, Liwei Jiang, Ximing Lu, Daniel Khashabi, Gunhee Kim, Yejin Choi & Maarten Sap (2022) ProsocialDialog: A Prosocial Backbone for Conversational Agents. EMNLP.
  6. Maarten Sap, Ronan Le Bras, Daniel Fried & Yejin Choi (2022) Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs. EMNLP.
  7. Zhijing Jin, Sydney Levine, Fernando Gonzalez Adauto, Ojasv Kamal, Maarten Sap, Mrinmaya Sachan, Rada Mihalcea, Joshua B. Tenenbaum & Bernhard Schölkopf (2022) When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment. NeurIPS.
  8. Maarten Sap, Swabha Swayamdipta, Laura Vianna, Xuhui Zhou, Yejin Choi & Noah A. Smith (2022) Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection. NAACL.
  9. Prithviraj Ammanabrolu, Liwei Jiang, Maarten Sap, Hanna Hajishirzi, Yejin Choi & Noah A. Smith (2022) Aligning to Social Norms and Values in Interactive Narratives. NAACL.
  10. Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray & Ece Kamar (2022) ToxiGen: Controlling Language Models to Generate Implied and Adversarial Toxicity. ACL.
  11. Saadia Gabriel, Skyler Hallinan, Maarten Sap, Pemi Nguyen, Franziska Roesner, Eunsol Choi & Yejin Choi (2022) Misinfo Reaction Frames: Reasoning about Readers' Reactions to News Headlines. ACL.
  12. Jesse Dodge, Maarten Sap, Ana Marasović, William Agnew, Gabriel Ilharco, Dirk Groeneveld, Margaret Mitchell & Matt Gardner (2021) Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus. EMNLP.
  13. Ashutosh Baheti, Maarten Sap, Alan Ritter & Mark Riedl (2021) Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts. EMNLP.
  14. Alisa Liu, Maarten Sap, Ximing Lu, Swabha Swayamdipta, Chandra Bhagavatula, Noah A. Smith & Yejin Choi (2021) DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts. ACL.
  15. Albert Xu, Eshaan Pathak, Eric Wallace, Suchin, Gururangan, Maarten Sap & Dan Klein (2021) Detoxifying Language Models Risks Marginalizing Minority Voices. NAACL.
  16. Xuhui Zhou, Maarten Sap, Swabha Swayamdipta, Yejin Choi & Noah A. Smith (2021) Challenges in Automated Debiasing for Toxic Language Detection. EACL.
  17. Xinyao Ma*, Maarten Sap*, Hannah Rashkin & Yejin Choi (2020) PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction. EMNLP.
  18. Sam Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi & Noah A Smith (2020) RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models. Findings of EMNLP.
  19. Maxwell Forbes, Jena D. Hwang, Vered Shwartz, Maarten Sap & Yejin Choi (2020) Social Chemistry 101: Learning to Reason about Social and Moral Norms. EMNLP.
  20. Maarten Sap, Eric Horvitz, Yejin Choi, Noah A Smith & James W. Pennebaker (2020) Recollection versus Imagination: Exploring Human Memory and Cognition via Neural Language Models. ACL.
  21. Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A Smith & Yejin Choi (2020) Social Bias Frames: Reasoning about Social and Power Implications of Language. ACL.
  22. Maarten Sap*, Hannah Rashkin*, Derek Chen, Ronan LeBras & Yejin Choi (2019) Social IQa: Commonsense Reasoning about Social Interactions. EMNLP.
  23. Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi & Noah A Smith (2019) The Risk of Racial Bias in Hate Speech Detection. ACL.
  24. Antoine Bosselut, Hannah Rashkin, Maarten Sap, Chaitanya Malaviya, Asli Celikyilmaz & Yejin Choi (2019) COMET: Commonsense Transformers for Automatic Knowledge Graph Construction. ACL.
  25. Maarten Sap, Ronan LeBras, Emily Allaway, Chandra Bhagavatula, Nicholas Lourie, Hannah Rashkin, Brendan Roof, Noah A Smith & Yejin Choi (2019) ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning. AAAI.
  26. Hannah Rashkin, Antoine Bosselut, Maarten Sap, Kevin Knight & Yejin Choi (2018) Modeling Naive Psychology of Characters in Simple Commonsense Stories. ACL.
  27. Hannah Rashkin*, Maarten Sap*, Emily Allaway, Noah A. Smith & Yejin Choi (2018) Event2Mind: Commonsense Inference on Events, Intents, and Reactions. ACL.
  28. Maarten Sap, Marcella Cindy Prasetio, Ari Holtzman, Hannah Rashkin & Yejin Choi (2017) Connotation Frames of Power and Agency in Modern Films. EMNLP.
  29. Roy Schwartz, Maarten Sap, Ioannis Konstas, Li Zilles, Yejin Choi & Noah A Smith (2017) The Effect of Different Writing Tasks on Linguistic Style: A Case Study of the ROC Story Cloze Task. CoNLL.
  30. H. Andrew Schwartz, Gregory Park, Maarten Sap, Evan Weingarten, Johannes Eichstaedt, Margaret Kern, David Stillwell, Michal Kosinski, Jonah Berger, Martin Seligman & Lyle Ungar (2015) Extracting Human Temporal Orientation from Facebook Language. NAACL.
  31. Maarten Sap, Gregory Park, Johannes C. Eichstaedt, Margaret L. Kern, David J. Stillwell, Michal Kosinski, Lyle H. Ungar & Hansen Andrew Schwartz (2014) Developing Age and Gender Predictive Lexica over Social Media. EMNLP.

Workshop

  1. Emily Allaway, Nina Taneja, Sarah-Jane Leslie & Maarten Sap (2022) Towards Countering Essentialism through Social Bias Reasoning. EMNLP workshop on NLP for Positive Impact.
  2. Zhilin Wang, Anna Jafarpour & Maarten Sap (2022) Uncovering Surprising Event Boundaries in Narratives. Workshop on Narrative Understanding.
  3. Tal August, Maarten Sap, Elizabeth Clark, Katharina Reinecke & Noah A. Smith (2020) Exploring the Effect of Author and Reader Identity in Online Story Writing: the StoriesInTheWild Corpus. Workshop on Narrative Understanding, Storylines, and Events (NUSE)@ ACL.
  4. Roy Schwartz, Maarten Sap, Ioannis Konstas, Li Zilles, Yejin Choi & Noah A Smith (2017) Story Cloze task: UW NLP System. EACL Workshop LSD Sem. 52--55.
  5. Daniel Preotiuc-Pietro, Maarten Sap, H Andrew Schwartz & Lyle Ungar (2015) Mental Illness Detection at the World Well-Being Project for the CLPsych 2015 Shared Task. NAACL Workshop on CLPsych.
  6. Daniel Preotiuc-Pietro, Johannes Eichstaedt, Gregory Park, Maarten Sap, Laura Smith, Victoria Tobolsky, H Andrew Schwartz & Lyle Ungar (2015) The Role of Personality, Age and Gender in Tweeting about Mental Illnesses. NAACL Workshop on CLPsych.
  7. H Andrew Schwartz, Johannes Eichstaedt, Margaret L Kern, Gregory Park, Maarten Sap, David Stillwell, Michal Kosinski & Lyle Ungar (2014) Towards Assessing Changes in Degree of Depression through Facebook. ACL Workshop on CLPsych. 118--125.

Demo

  1. Maria Antoniak, Anjalie Field, Ji Min Mun, Melanie Walsh, Lauren F. Klein & Maarten Sap (2023) Riveter: Measuring Power and Social Dynamics Between Entities. ACL demonstrations.
  2. Hao Fang, Hao Cheng, Maarten Sap, Elizabeth Clark, Ariel Holtzman, Yejin Choi, Noah A Smith & Mari Ostendorf (2018) Sounding Board: A User-Centric and Content-Driven Social Chatbot. NAACL System Demonstrations.
  3. H Andrew Schwartz, Salvatore Giorgi, Maarten Sap, Patrick Crutchley, Lyle Ungar & Johannes Eichstaedt (2017) DLATK: Differential Language Analysis ToolKit. EMNLP System Demonstrations. 55--60.

Other

  1. Organizers Of QueerinAI, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherl, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, J Hetvi, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, A Pranav, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi An, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emily Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo-Lopes, Alex Markham, Evyn Dǒng, Jackie Kay, Manu Saraswat, Nikhil Vytla & Luke Stark (2023) Queer In AI: A Case Study in Community-Led Participatory AI. Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency.
  2. Maarten Sap (2021) Positive AI with Social Commonsense Models.
  3. Hao Fang, Hao Cheng, Elizabeth Clark, Ariel Holtzman, Maarten Sap, Mari Ostendorf, Yejin Choi & Noah A Smith (2017) Sounding Board - University of Washington’s Alexa Prize Submission. Alexa Prize Proceedings.
  4. H Andrew Schwartz, Maarten Sap, Margaret L Kern, Johannes C Eichstaedt, Adam Kapelner, Megha Agrawal, Eduardo Blanco, Lukasz Dziurzynski, Gregory Park, David Stillwell, Michal Kosinski, Martin E P Seligman & Lyle H Ungar (2016) Predicting individual well-being through the language of social media. Biocomputing 2016: Proceedings of the Pacific Symposium. 516--527.

Preprint

  1. Taylor Sorensen, Liwei Jiang, Jena Hwang, Sydney Levine, Valentina Pyatkin, Peter West, Nouha Dziri, Ximing Lu, Kavel Rao, Chandra Bhagavatula, Maarten Sap, John Tasioulas & Yejin Choi (2023) Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties. arXiv.
  2. Natalie Shapira, Mosh Levy, Hossein Seyed Alavi, Xuhui Zhou, Yejin Choi, Yoav Goldberg, Maarten Sap & Vered Shwartz (2023) Clever Hans or Neural Theory of Mind? Stress Testing Social Reasoning in Large Language Models. arXiv.
  3. Ashutosh Baheti, Ximing Lu, Faeze Brahman, Le Ronan Bras, Maarten Sap & Mark Riedl (2023) Improving Language Models with Advantage-based Offline Policy Gradients. arXiv.
  4. Akhila Yerukola, Xuhui Zhou & Maarten Sap (2023) ``Don't Take This Out of Context!'' On the Need for Contextual Models and Evaluations for Stylistic Rewriting. arXiv.
  5. Yiming Zhang, Sravani U. Nanduri, Liwei Jiang, Tongshuang Wu & Maarten Sap (2023) ``Thinking Slow'' in Toxic Language Annotation with Explanations of Implied Social Biases. arXiv.
  6. Jocelyn Shen, Maarten Sap, Pedro Colon-Hernandez, Hae Won Park & Cynthia Breazeal (2023) Modeling Empathic Similarity in Personal Narratives. arXiv.
  7. Hyunwoo Kim, Jack Hessel, Liwei Jiang, Peter West, Ximing Lu, Youngjae Yu, Pei Zhou, Ronan Le Bras, Malihe Alikhani, Gunhee Kim, Maarten Sap & Yejin Choi (2023) SODA: Million-scale Dialogue Distillation with Social Commonsense Contextualization. arXiv.
  8. Liwei Jiang, Jena D Hwang, Chandra Bhagavatula, Ronan Le Bras, Jenny Liang, Jesse Dodge, Keisuke Sakaguchi, Maxwell Forbes, Jon Borchardt, Saadia Gabriel, Yulia Tsvetkov, Oren Etzioni, Maarten Sap, Regina Rini & Yejin Choi (2021) Can Machines Learn Morality? The Delphi Experiment. arXiv.

Awards

### Paper awards | | | | | --------------------------- | ------------------------------------------------------------ | ----------: | | Outstanding Paper | [NLPositionality: Characterizing Design Biases of Datasets and Models](./publications.html#santy2023nlpositionality) | ACL 2023 | | Best Paper | [Queer In AI: A Case Study in Community-Led Participatory AI](./publications.html#OrganizersOfQueerin2023QueerAI) | FAccT 2023 | | Best Paper | [Social Bias Frames: Reasoning about Social and Power Implications of Language](./publications.html#sap2020socialbiasframes) | WeCNLP 2020 | | Best Short Paper Nomination | [The Risk of Racial Bias in Hate Speech Detection](./publications.html#sap2019risk) | ACL 2019 | ### Other | | | | | ---------------------------------------- | ------------------------------------------------------------ | ---: | | William Chan Memorial Dissertation Award | [Positive AI with Social Commonsense Models](./publications.html#sap2021positiveAIwithSocialCommonsenseModels) | 2021 | | Amazon Alexa Prize | [Sounding Board](https://sounding-board.github.io/): [A User-Centric and Content-Driven Social Chatbot](./publications.html#fang2017alexatechreport) | 2017 |

Thesis Committees

| | | | | | ---- | --------------- | --------------------- | ---: | | PhD | Ashutosh Baheti | Mark Rield, GATech | 2024 | | PhD | Kaixin Ma | Eric Nyberg, CMU | 2023 | | PhD | Prakhar Gupta | Jeff Bingham, CMU | 2023 | | Ms | Jocelyn Chen | Cytnhia Breazeal, MIT | 2023 | | PhD | Chan Young Park | Yulia Tsvetkov, UW | 2023 | | PhD | Paul Röttger | Scott Hale, University of Oxford | 2023 |

Teaching

### Courses |||| |-|-|-:| |[11-361 Data Science Seminar](https://mcds-cmu.github.io/11631/f23/)||Fall 2023| | [11-830 Computational Ethics](http://maartensap.com/11-830-Spring2023/) | | Spring 2023 | ### Guest lectures & Tutorials | | | | | ------------------------------------------------------------ | -------------------- | ----------: | | Bias in Natural Language Processing | 05-899 Guest Lecture | Spring 2023 | | Bias in Natural Language Processing | 15-884 Guest Lecture | Fall 2022 | | "[Crowdsourcing Beyond Annotation](https://nlp-crowdsourcing.github.io/)" | Tutorial | EMNLP 2021 | | "[Commonsense Reasoning in Natural Language Processing](./acl2020-commonsense/index.html)" | Tutorial | ACL 2020 |

Service

### Workshops | | | | | ------------------------------------------------------------ | ------------------ | ---------: | | [Multimodal Content Moderation Workshop](https://multimodal-content-moderation.github.io/) | co-organizer | CVPR 2023 | | [NLP for Positive Impact Workshop](https://sites.google.com/view/nlp4positiveimpact) | steering committee | EMNLP 2022 | | [NLP for Positive Impact Workshop](https://sites.google.com/view/nlp4positiveimpact/previous-workshops/acl-2021-workshop) | co-organizer | ACL 2021 | ### Committees | | | | | ------------------------------------------------ | ------- | --------------: | | Diversity, Equity, and Inclusion committee | CMU LTI | 2022-present | | PhD & MLT admissions committee | CMU LTI | 2022-present | | Socio-cultural diversity and inclusion committee | ACL | 2020 | | Diversity committee | UW CSE | 2016–2020 | | Graduate student advisory council (G5PAC) | UW CSE | 01/2018–12/2020 | #### Senior program committees | | | | ------------------ | -----------: | | ACL rolling review | 2020–present | | AAAI | 2021 | #### Reviewing | | | | ------------------------------------------------------------ | -----------: | | *Journals & conferences* | | | ACL rolling review | 2020–present | | ACL | 2019–present | | EMNLP | 2018–2023 | | Journal of Psycholinguistic Research | 2023 | | Computing Survey | 2023 | | Transactions of ACL | 2020, 2022 | | AAAI | 2020 | | ICWSM | 2021 | | Dementia and Geriatric Cognitive Disorders Journal | 2020 | | Computational Linguistic | 2019, 2020 | | Humanities and Social Sciences Communications | 2019 | | Journal of Artificial Intelligence Research | 2019 | | IEEE Transactions on Cognitive and Developmental Systems | 2019 | | Social Psychological and Personality Science | 2018 | | *Workshops* | | | Workshop on NLP for Positive Impact | 2022 | | Workshop on NLP for Causal Inference | 2021 | | NAACL Student Research Workshop | 2019 | | CLPsych workshop | 2016–2018 | | Stylistic Variation workshop | 2018 | ### Panels & other service or outreach | | | | ------------------------------------------------------------ | --------------------: | | Panelist at the [AAAI Workshop on Responsible Language Models](https://sites.google.com/vectorinstitute.ai/relm2024/) | 02/2024 | | [Responsible AI](https://www.cmu.edu/block-center/responsible-ai/index.html) salon on generative AI at CMU | 03/2023 | | Presentation to U.S. congressional appropriations committee about risks and implications of AI and LLMs | 03/2023 | | [Red-teaming GPT-4](https://cdn.openai.com/papers/gpt-4-system-card.pdf) for OpenAI | 09/2022–12/2022 |

Talks

| | | | ------------------------------------------------------------ | ------: | | Towards Socially Aware AI with Pragmatic Competence | | | [ICML workshop on Theory of Mind](https://tomworkshop.github.io/) (*invited speaker*) | 07/2023 | | The Pivotal Role of Social Context in Toxic Language Detection | | | [ACL workshop on online abuse and harms](https://www.workshopononlineabuse.com/) (*invited speaker*) | 07/2023 | | Toward Prosocial NLP: Reasoning About And Responding to Toxicity in Language | | | MIT Media Lab Breazeal Group Meeting | 11/2022 | | CMU S3D Computational Social Science Seminar | 11/2022 | | Amazon Alexa Trust & Privacy | 11/2022 | | University of Minnesota NLP seminar | 10/2022 | | Detecting and Rewriting Social Biases in Language | | | Pinterest NLP seminar | 09/2022 | | UIUC Responsible Data Science Seminar Series | 02/2022 | | MilaNLP seminar at Università Bocconi | 10/2021 | | [PAN workshop at CLEF](https://pan.webis.de/clef21/pan21-web/index.html) (*invited speaker*) | 09/2021 | | Annotators with Attitudes: How Annotator Beliefs And Identities Bias Toxic Language Detection | | | NAACL | 07/2022 | | Text As Data (TADA) | 10/2021 | | Positive AI with Social Commonsense Models | | | The Web Conf [Workshop UserNLP: User-centered Natural Language Processing Workshop](https://caisa.informatik.uni-marburg.de/user_nlp.html) (*invited speaker*) | 04/2022 | | AKBC [Workshop on Commonsense Reasoning](https://akbc-cskb.github.io/) (*invited speaker*) | 10/2021 | | University of Toronto Computer Science | 04/2021 | | MIT EECS | 03/2021 | | CMU LTI/MLD | 03/2021 | | UChicago CS | 03/2021 | | TTIC | 02/2021 | | Emory CS | 02/2021 | | Vanderbilt CS | 02/2021 | | EPFL I&C | 01/2021 | | Yale Data Science & Statistics seminar | 01/2021 | | PowerTransformer: Unsupervised Controllable Revision for Biased Language Correction | | | EMNLP conference | 11/2020 | | Social Bias Frames: Reasoning About Social and Power Dynamics | | | WeCNLP Summit | 10/2020 | | ACL Conference | 07/2020 | | Reasoning about Social Dynamics and Social Bias in Language | | | SRI seminar | 01/2021 | | Georgia Tech NLP seminar | 10/2020 | | Berkeley NLP seminar | 02/2020 | | Stanford NLP seminar | 02/2020 | | Social and Ethical Considerations in English Toxic Language Detection | | | NLP with Friends | 08/2020 | | Recollection versus Imagination: Exploring Human Memory and Cognition via Neural Language Models | | | ACL Conference | 07/2020 | | COMET: Commonsense Transformers for Automatic Knowledge Graph Construction | | | DARPA Communicating with Computers grant meeting | 11/2019 | | Social IQa: Commonsense Reasoning about Social Interactions | | | EMNLP conference | 11/2019 | | The Risk of Racial Bias in Hate Speech Detection | | | ACL Conference | 07/2019 | | ICML Queer in AI workshop (*invited speaker*) | 06/2019 | | ATOMIC: An Atlas of Machine Commonsense for If-Then Reasoning | | | AAAI conference | 01/2019 | | AI2 seminar | 01/2019 | | Event2Mind: Commonsense Inference on Events, Intents, and Reactions | | | DARPA Communicating with Computers grant meeting | 07/2018 | | Detecting Implicit Bias in Text through Connotative Language | | | UW Social Psychology seminar | 04/2018 |

News Coverage

##### [NLPositionality: Characterizing Design Biases of Datasets and Models](publications.html#santy2023NLPositionality) (2023) - [marktechpost.com](https://web.archive.org/web/20230717174128/https://www.marktechpost.com/2023/07/14/a-research-group-from-cmu-ai2-and-university-of-washington-introduces-nlpositionality-an-ai-framework-for-characterizing-design-biases-and-quantifying-the-positionality-of-nlp-datasets-and-models/) ##### [ProsocialDialog: A Prosocial Backbone for Conversational Agents](publications.html#kim2022prosocialDialog) (2022) - [sciencefocus.com](https://web.archive.org/web/20230327201644/https://www.sciencefocus.com/news/chatgpt-ted-lasso-internet-hate-speech/) ##### [Neural Theory-of-Mind? On the Limits of Social Intelligence in Large LMs](publications.html#sap2022neuralToM) (2022) - [nytimes.com](https://web.archive.org/web/20230327184321/https://www.nytimes.com/2023/03/27/science/ai-machine-learning-chatbots.html) ##### [Delphi: Towards Machine Ethics and Norms](publications.html#jiang2021delphi) (2021) - [nytimes.com](https://web.archive.org/web/20230305234708/https://www.nytimes.com/2021/11/19/technology/can-a-machine-learn-morality.html) - [vox.com](https://web.archive.org/web/20221229172748/https://www.vox.com/future-perfect/2021/10/27/22747333/artificial-intelligence-ethics-delphi-ai) - [theguardian.com](https://web.archive.org/web/20230213231329/https://www.theguardian.com/technology/2021/nov/02/delphi-online-ai-bot-philosophy) - [wired.com](https://web.archive.org/web/20230329222042/https://www.wired.com/story/program-give-ai-ethics-sometimes/) - [geekwire.com(https://web.archive.org/web/20230310030100/https://www.geekwire.com/2021/teaching-artificial-intelligence-right-from-wrong-new-tool-from-ai2-aims-to-model-ethical-judgments/) - [futurism.com](https://web.archive.org/web/20230325165850/https://www.futurism.com/delphi-ai-ethics-racist) ##### [Documenting Large Webtext Corpora: A Case Study on the Colossal Clean Crawled Corpus](publications.html#dodge2021documentingC4) (2021) - [washingtonpost.com](https://web.archive.org/web/20230419120558/https://www.washingtonpost.com/technology/interactive/2023/ai-chatbot-learning/) - [wired.com](https://web.archive.org/web/20230330110735/https://www.wired.com/story/review-ai-chatbots-bing-bard-chat-gpt/) - [wired.com](https://web.archive.org/web/20230314202533/https://www.wired.com/story/efforts-make-text-ai-less-racist-terrible/) - [unite.ai](https://web.archive.org/web/20230321034425/https://www.unite.ai/minority-voices-filtered-out-of-google-natural-language-processing-models/) ##### [Just Say No: Analyzing the Stance of Neural Dialogue Generation in Offensive Contexts](publications.html#baheti2021justSayNo) (2021) - [thenextweb.com](https://web.archive.org/web/20230404211115/https://www.thenextweb.com/news/gpt-3-and-humans-twice-as-likely-agree-with-offensive-reddit-comments-chatbots) ##### [DExperts: Decoding-Time Controlled Text Generation with Experts and Anti-Experts](publications.html#liu2021dexperts) (2021) - [geekwire.com](https://web.archive.org/web/20230404211810/https://www.geekwire.com/2021/researchers-develop-new-way-help-machine-generated-language-systems-reduce-toxic-language/) ##### [RealToxicityPrompts: Evaluating Neural Toxic Degeneration in Language Models](publications.html#gehman2020realtoxicityprompts) (2020) - [ieee.org](https://web.archive.org/web/20230321062841/https://spectrum.ieee.org/open-ais-powerful-text-generating-tool-is-ready-for-business) - [fortune.com](https://web.archive.org/web/20230404205249/https://www.fortune.com/2020/09/29/artificial-intelligence-openai-gpt3-toxic/) - [geekwire.com](https://web.archive.org/web/20230404212031/https://www.geekwire.com/2021/curse-neural-toxicity-ai2-uw-researchers-help-computers-watch-language/) - [wired.com](https://web.archive.org/web/20230314171124/https://www.wired.com/story/ai-fueled-dungeon-game-got-much-darker/) ##### [The Risk of Racial Bias in Hate Speech Detection](publications.html#sap2019risk) (2019) - [forbes.com](https://web.archive.org/web/20221218082924/https://www.forbes.com/sites/nicolemartin1/2019/08/13/googles-artificial-intelligence-hate-speech-detector-is-racially-biased/?sh=37fa3a53326c) - [vox.com](https://web.archive.org/web/20230404205546/https://www.vox.com/recode/2019/8/15/20806384/social-media-hate-speech-bias-black-african-american-facebook-twitter) - [observer.com](https://web.archive.org/web/20220818104542/https://www.observer.com/2019/08/google-ai-hate-speech-detector-black-racial-bias-twitter-study/) - [fortune.com](https://web.archive.org/web/20221206075315/https://www.fortune.com/2019/08/16/google-jigsaw-perspective-racial-bias/) - [techcrunch.com](https://web.archive.org/web/20221130020534/https://www.techcrunch.com/2019/08/14/racial-bias-observed-in-hate-speech-detection-algorithm-from-google/) - [newscientist.com](https://www.newscientist.com/article/2213064-googles-hate-speech-detecting-ai-appears-to-be-racially-biased/) - [breitbart.com](http://web.archive.org/web/20200620080022/https://www.breitbart.com/tech/2019/08/17/ai-is-1-5-times-more-likely-to-flag-social-media-posts-by-black-people-as-offensive/) ##### [Connotation Frames of Power and Agency in Modern Films](publications.html#sap2017connotation) (2017) - [futurity.org](https://web.archive.org/web/20211205141552/https://www.futurity.org/movie-scripts-gender-bias-1605212/) - [kuow.org](https://web.archive.org/web/20230404210655/https://www.kuow.org/stories/record-wednesday-november-15-2017/) - [technologynetworks.com](https://web.archive.org/web/20221007062604/https://www.technologynetworks.com/informatics/news/scientists-use-machine-learning-to-analyze-language-in-movies-294179) - [dailymail.co.uk](https://www.dailymail.co.uk/femail/article-5081501/How-Hollywood-films-FUEL-sexism.html) - [phys.org](https://phys.org/news/2017-11-ai-tool-quantifies-power-imbalance.html) - [electronics360.globalspec.com](https://electronics360.globalspec.com/article/10344/analyzing-gender-bias-with-ai) ##### [Sounding Board - University of Washington’s Alexa Prize Submission](publications.html#fang2017alexatechreport) (2017) - [theverge.com](https://www.theverge.com/2018/6/13/17453994/amazon-alexa-prize-2018-competition-conversational-ai-chatbots) - [geekwire.com](https://www.geekwire.com/2018/secrets-500k-amazon-alexa-prize-winner-inside-univ-washingtons-socialbot/) - [wired.com](https://www.wired.com/story/inside-amazon-alexa-prize/) - [q13fox.com](http://q13fox.com/2018/01/08/uw-students-create-conversational-amazon-alexa-device/) - [dailyuw.com](http://www.dailyuw.com/science/article_bc135d10-f0f7-11e7-a1ab-0be114c44429.html) - [seattletimes.com](https://www.seattletimes.com/seattle-news/education/uw-students-teach-alexa-to-have-a-little-chat-with-us/) - [komonews.com](http://komonews.com/news/local/uw-team-wins-500000-prize-from-amazon-for-conversational-bot) - [amazon.com](https://developer.amazon.com/blogs/alexa/post/1a6a19d8-e45d-4b3b-981d-776a378ba625/university-of-washington-students-win-inaugural-alexa-prize) - [komonews.com](http://komonews.com/news/local/uw-team-finalist-for-1-million-prize-to-hold-20-minute-conversation-amazons-alexa) - [geekwire.com](https://www.geekwire.com/2017/amazon-reveals-3-university-finalists-2-5m-alexa-prize-including-one-uw/) ##### Miscellaneous - 2023 - On "Sparks of AGI": [nytimes.com](https://web.archive.org/web/20230516091858/https://www.nytimes.com/2023/05/16/technology/microsoft-ai-human-reasoning.html) - On AI social coaches: [techcrunch.com](https://web.archive.org/web/20230520020144/https://techcrunch.com/2023/05/13/ai-relationship-building-amorai/) - On GPT-4 red-teaming: [financialtimes.com](https://web.archive.org/web/20230414132856/https://www.ft.com/content/0876687a-f8b7-4b39-b513-5fee942831e8?accessToken=zwAAAYd_9J4skc8Idmh6-LdLOdO1E1_ulCgx6A.MEQCIFehPSHqO7vjyrQmUHmZGujI6tVxlndevV5vIQGnWzENAiBJg7ltMLzzeyNNXxQC36cpuLwYQ9BB26_O2upfGLGyyw&segmentId=e95a9ae7-622c-6235-5f87-51e412b47e97&shareType=enterprise) - On users falling in love with ChatGPT: [time.com](https://web.archive.org/web/20230224153642/https://www.time.com/6257790/ai-chatbots-love/) - 2022 - On openness of large LMs: [spectrum.ieee.org](https://web.archive.org/web/20230321062817/https://spectrum.ieee.org/large-language-models-meta-openai)