| Challenge: | This tutorial will provide an overview of ethical research tools and ethical implications of language technologies. |
| Approach: | This tutorial will provide an overview of ethical research and practical examples . it will discuss ethical tools to ensure data, algorithms, and models are socially responsible . |
| Outcome: | This tutorial will provide an overview of ethical research tools and methods . it will discuss philosophical foundations of ethical work along with state of the art techniques . |
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How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact (2021.findings-acl)
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| Challenge: | Recent years have seen many breakthroughs in natural language processing (NLP), transitioning it from a mostly theoretical field to one with many real-world applications. |
| Approach: | They propose a moral philosophy definition of social good and a framework to evaluate the direct and indirect real-world impact of NLP tasks. |
| Outcome: | The proposed framework evaluates the direct and indirect real-world impact of NLP tasks and adopts the methodology of global priorities research to identify priority causes for NLP research. |
Navigating Ethical Challenges in NLP: Hands-on strategies for students and researchers (2025.acl-tutorials)
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Luciana Benotti, Fanny Ducel, Karën Fort, Guido Ivetta, Zhijing Jin, Min-Yen Kan, Seunghun J. Lee, Minzhi Li, Margot Mieskes, Adriana Pagano
| Challenge: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . participants will gain practical experience on when to flag a paper for ethics review . |
| Approach: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . participants will gain practical experience on when to flag a paper for ethics review . |
| Outcome: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . participants will gain practical experience on when to flag a paper for ethics review . |
Understanding Ethics in NLP Authoring and Reviewing (2023.eacl-tutorials)
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| Challenge: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . |
| Approach: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . the methodology is interactive and participatory, including case studies and working in groups . |
| Outcome: | This tutorial will equip participants with basic guidelines for thinking deeply about ethical issues . the methodology is interactive and participatory, including case studies and working in groups. |
Values, Ethics, Morals? On the Use of Moral Concepts in NLP Research (2023.findings-emnlp)
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| Challenge: | Recent studies have focused on the ethical aspects of NLP, but little to no discussion of the terminology and theories underpinning those efforts and their implications. |
| Approach: | They propose to provide an overview of some important ethical concepts stemming from philosophy and to survey the existing literature on moral NLP w.r.t. their findings show that most papers neither provide a clear definition of the terms they use nor adhere to definitions from philosophy. |
| Outcome: | The findings show that most papers neither provide a clear definition of the terms they use nor adhere to definitions from philosophy. |
Integrating Ethics into the NLP Curriculum (2020.acl-tutorials)
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| Challenge: | a tutorial aims to teach students how to ethically apply NLP . the tutorial will focus on examples for university classrooms, but ideas can extend to company-internal workshops or tutorials in a variety of organizations. |
| Approach: | a tutorial aims to empower NLP researchers and practitioners to teach others about ethical NLP . the tutorial will focus on examples for university classrooms, but ideas can extend to company-internal workshops . |
| Outcome: | a tutorial aims to teach students how to ethically apply NLP techniques . the tutorial will include examples for university classrooms, but ideas can extend to company-internal workshops . |
Mitigating Societal Harms in Large Language Models (2023.emnlp-tutorial)
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| Challenge: | Recent studies have highlighted societal harms that can be caused by language generation models deployed in the wild. |
| Approach: | They propose to use a typology of technical approaches to mitigating harms of language generation models to provide an overview of potential social issues in language generation including toxicity, social biases, misinformation, factual inconsistency, and privacy violations. |
| Outcome: | The proposed typology addresses toxicity, biases, misinformation, factual inconsistency, and privacy violations in language generation models. |
‘Just What do You Think You’re Doing, Dave?’ A Checklist for Responsible Data Use in NLP (2021.findings-emnlp)
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| Challenge: | a key part of the NLP ethics movement is responsible use of data, but what that means is unclear . a proposed checklist for responsible data (re-)use could standardise peer review of submissions . |
| Approach: | They propose a checklist for responsible data use that could standardise peer review . they propose implementing a standard for data (re-)use across NLP conferences . |
| Outcome: | The proposed checklist would standardise peer review of submissions and enable more in-depth view of published research across the community. |
NLP for Social Good: A Survey and Outlook of Challenges, Opportunities and Responsible Deployment (2026.eacl-long)
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Antonia Karamolegkou, Angana Borah, Eunjung Cho, Sagnik Ray Choudhury, Martina Galletti, Pranav Gupta, Oana Ignat, Priyanka Kargupta, Neema Kotonya, Hemank Lamba, Sun-Joo Lee, Arushi Mangla, Ishani Mondal, Fatima Zahra Moudakir, Deniz Nazar, Poli Nemkova, Dina Pisarevskaya, Naquee Rizwan, Nazanin Sabri, Keenan Samway, Dominik Stammbach, Anna Steinberg Schulten, David Tomás, Steven R Wilson, Bowen Yi, Jessica H Zhu, Arkaitz Zubiaga, Anders Søgaard, Alexander Fraser, Zhijing Jin, Rada Mihalcea, Joel R. Tetreault, Daryna Dementieva
| Challenge: | This paper surveys work in "NLP for Social Good" across nine domains relevant to global development and risk agendas. |
| Approach: | This paper analyzes work in "NLP for Social Good" across nine domains relevant to global development and risk agendas. |
| Outcome: | The paper analyzes work in "NLP for Social Good" across nine domains relevant to global development and risk agendas. |
On the Machine Learning of Ethical Judgments from Natural Language (2022.naacl-main)
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| Challenge: | a recent study examines the morality of NLP models that can take in arbitrary text and output a moral judgment . a Delphi project is a popular system for moral prediction, but it has received criticism . |
| Approach: | They propose to critique NLP methods for automating ethical decision-making . they examine a nascent task of predicting moral and ethical decisions from text . |
| Outcome: | The proposed model is unsafe at any accuracy, the authors argue . they argue that the proposed model could be useful in NLP, but not in AI. |
Use of Formal Ethical Reviews in NLP Literature: Historical Trends and Current Practices (2021.findings-acl)
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| Challenge: | Ethical aspects of research in language technologies have received much attention recently . do we observe a rise in formal ethical reviews of NLP studies? |
| Approach: | They conduct a qualitative and quantitative analysis of the ethics of NLP research . they compare the ethical reviews of NLAs to those of related disciplines . |
| Outcome: | The results compare the ACL Anthology to other related disciplines in the field . the results show that there is a heightened awareness of ethical issues that was previously lacking . |