Addressing if, and how, machine learning and AI technologies can be used towards fair and equitable futures
Zeerak Talat
Chancellor’s Fellow in Responsible Machine Learning and Artificial Intelligence
Research Areas of Expertise:
Ethical and responsible natural language processing, machine learning, and artificial intelligence for socially contingent data.
Research Summary:
Zeerak’s research is motivated by the realisation that if we must have machine learning systems in our society, then we bear a responsible to identify desirable traits for such systems. Their work seeks to do this by viewing machine learning technologies through the lens of content moderation, as concerns and harms arising from technologies very quickly become apparent when the technologies might come to govern our speech. For this reason, Zeerak’s work understanding and critiquing machine learning systems borrows from multiple fields, including natural language processing, science and technology studies, and media studies. Zeerak’s work has been published in conferences such as the Annual Meetings of the Association of Computational Linguistics (ACL), the ACM Conference on Fairness, Accountability, and Transparency (FAccT), and in collected volumes on online harms and artificial intelligence.
Key Publications:
‘Impoverished Language Technology: The Lack of (Social) Class in NLP’. Cercas Curry, Amanda, Zeerak Talat, and Dirk Hovy. 2024. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), eds. Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, and Nianwen Xue. Torino, Italia: ELRA and ICCL, 8675–82. 🔗
‘The Perspectivist Paradigm Shift: Assumptions and Challenges of Capturing Human Labels’. Fleisig, Eve, Su Lin Blodgett, Dan Klein, and Zeerak Talat. 2024. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers), Mexico City, Mexico: Association for Computational Linguistics, 2279–92. 🔗
‘It’s Incomprehensible: On Machine Learning and Decoloniality’. Birhane, Abeba, and Zeerak Talat. 2023. In Handbook of Critical Studies of Artificial Intelligence, ed. Simon Lindgren. Edward Elgar Publishing, 128–40. 🔗
‘Mirages. On Anthropomorphism in Dialogue Systems’. Abercrombie, Gavin, Amanda Curry, Tanvi Dinkar, Verena Rieser, and Zeerak Talat. 2023. In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, Singapore: Association for Computational Linguistics, 4776–90. 🔗
‘A Federated Approach for Hate Speech Detection’. Gala, Jay, Deep Gandhi, Jash Mehta, and Zeerak Talat. 2023. In Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics, Dubrovnik, Croatia: Association for Computational Linguistics, 3248–59. 🔗
‘Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing’. Kaffee, Lucie-Aimée, Arnav Arora, Zeerak Talat, and Isabelle Augenstein. 2023. In Findings of the Association for Computational Linguistics: EMNLP 2023, Singapore: Association for Computational Linguistics, 13977–98. 🔗
‘Futures for Research on Hate Speech in Online Social Media Platforms’. Kirtz, Jaimie Lee, and Zeerak Talat. 2023. eds. Christian Strippel, Sünje Paasch-Colberg, Martin Emmer, and Joachim Trebbe. 🔗
‘Directions for NLP Practices Applied to Online Hate Speech Detection’. Fortuna, Paula, Monica Dominguez, Leo Wanner, and Zeerak Talat. 2022. In Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, Abu Dhabi, United Arab Emirates: Association for Computational Linguistics, 11794–805. 🔗
‘Data Governance in the Age of Large-Scale Data-Driven Language Technology’. Jernite, Yacine, Huu Nguyen, Stella Biderman, Anna Rogers, Maraim Masoud, Valentin Danchev, Samson Tan, et al. 2022. In 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul Republic of Korea: ACM, 2206–22. 🔗
‘On the Machine Learning of Ethical Judgments from Natural Language’. Talat, Zeerak, Hagen Blix, Josef Valvoda, Maya Indira Ganesh, Ryan Cotterell, and Adina Williams. 2022. In Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Seattle, United States: Association for Computational Linguistics, 769–79. 🔗
‘You Reap What You Sow: On the Challenges of Bias Evaluation under Multilingual Settings’. Talat, Zeerak, Aurélie Névéol, Stella Biderman, Miruna Clinciu, Manan Dey, Shayne Longpre, Sasha Luccioni, et al. 2022. In Proceedings of BigScience Episode #5 – Workshop on Challenges & Perspectives in Creating Large Language Models, virtual+Dublin: Association for Computational Linguistics, 26–41. 🔗
‘A Survey of Race, Racism, and Anti-Racism in NLP’. Field, Anjalie, Su Lin Blodgett, Zeerak Talat, and Yulia Tsvetkov. 2021. In Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers), Online: Association for Computational Linguistics, 1905–25. 🔗
‘Understanding Abuse: A Typology of Abusive Language Detection Subtasks’. Talat, Zeerak, Thomas Davidson, Dana Warmsley, and Ingmar Weber. 2017. In Proceedings of the First Workshop on Abusive Language Online, Vancouver, BC, Canada: Association for Computational Linguistics, 78–84. 🔗
Talat, Zeerak, and Dirk Hovy. 2016. ‘Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter’. In Proceedings of the NAACL Student Research Workshop, San Diego, California: Association for Computational Linguistics, 88–93. 🔗