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Large language models (LLMs) may not equitably represent diverse global perspectives on societal issues.
Fine-tuning language models from human preferences
Daniel M. Ziegler, Nisan Stiennon, Jeffrey Wu, Tom B. Brown, Alec Radford, Dario Amodei, Paul F. Christiano, and Geoffrey Irving · 1909
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Identity and interaction: a sociocultural linguistic approach
Mary Bucholtz and Kira Hall · 2005
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Studies in public opinion: Attitudes, nonattitudes, measurement error, and change
Paul Whiteley · 2005
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The weirdest people in the world?
Joseph Henrich, Steven J. Heine, and Ara Norenzayan · 2010
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Evaluating the output of machine translation systems
Alon Lavie · 2010
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Subjective natural language problems: Motivations, applications, characterizations, and implications
Cecilia Ovesdotter Alm · 2011
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Big data’s disparate impact
Solon Barocas and Andrew D. Selbst · 2016
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Measuring public opinion with surveys
Adam J. Berinsky · 2017
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Deep reinforcement learning from human preferences
Paul F Christiano, Jan Leike, Tom Brown, Miljan Martic, Shane Legg, and Dario Amodei · 2017
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Identifying and reducing gender bias in word-level language models
Shikha Bordia and Samuel R. Bowman · 2019
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Fairness and abstraction in sociotechnical systems
Andrew D. Selbst, Danah Boyd, Sorelle A. Friedler, Suresh Venkatasubramanian, and Janet Vertesi · 2019
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The woman worked as a babysitter: On biases in language generation
Emily Sheng, Kai-Wei Chang, Premkumar Natarajan, and Nanyun Peng · 2019
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Language (technology) is power: A critical survey of “bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach · 2020
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Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei · 2020
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The whiteness of ai
Stephen Cave and Kanta Dihal · 2020
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Western civilization, our tradition, Nov 2020
Fad-Admin · 2020
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Artificial intelligence, values, and alignment
Iason Gabriel · 2020
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RealToxicityPrompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A. Smith · 2020
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Social biases in NLP models as barriers for persons with disabilities
Ben Hutchinson, Vinodkumar Prabhakaran, Emily Denton, Kellie Webster, Yu Zhong, and Stephen Denuyl · 2020
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The state and fate of linguistic diversity and inclusion in the NLP world
Pratik Joshi, Sebastin Santy, Amar Budhiraja, Kalika Bali, and Monojit Choudhury · 2020
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Don’t ask if artificial intelligence is good or fair, ask how it shifts power
Pratyusha Kalluri · 2020
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Words Matter: Meaning and Power
S. McConnell-Ginet · 2020
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Why You Should Do NLP Beyond English
Sebastian Ruder · 2020
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Social bias frames: Reasoning about social and power implications of language
Maarten Sap, Saadia Gabriel, Lianhui Qin, Dan Jurafsky, Noah A. Smith, and Yejin Choi · 2020
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Learning to summarize with human feedback
Nisan Stiennon, Long Ouyang, Jeffrey Wu, Daniel Ziegler, Ryan Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul F Christiano · 2020
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Persistent anti-muslim bias in large language models
Abubakar Abid, Maheen Farooqi, and James Zou · 2021
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A general language assistant as a laboratory for alignment, 2021
Amanda Askell, Yuntao Bai, Anna Chen, Dawn Drain, Deep Ganguli, Tom Henighan, Andy Jones, Nicholas Joseph, Ben Mann, Nova DasSarma, Nelson Elhage, Zac Hatfield-Dodds, Danny Hernandez, Jackson Kernion, Kamal Ndousse, Catherine Olsson, Dario Amodei, Tom Brown, Jack Clark, Sam McCandlish, Chris Olah, and Jared Kaplan · 2021
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On the dangers of stochastic parrots: Can language models be too big?
Emily M. Bender, Timnit Gebru, Angelina McMillan-Major, and Shmargaret Shmitchell · 2021
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Measuring diversity of artificial intelligence conferences
Ana Freire, Lorenzo Porcaro, and Emilia Gómez · 2021
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The challenge of value alignment: from fairer algorithms to AI safety
Iason Gabriel and Vafa Ghazavi · 2021
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World values survey: Round seven – country-pooled datafile version 5.0.0, 2022
Christian Haerpfer, Ronald Inglehart, Alejandro Moreno, Christian Welzel, Kseniya Kizilova, Jaime Diez-Medrano, Milena Lagos, Pippa Norris, Eduard Ponarin, and Bianca Puranen · 2022
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ToxiGen: A large-scale machine-generated dataset for adversarial and implicit hate speech detection
Thomas Hartvigsen, Saadia Gabriel, Hamid Palangi, Maarten Sap, Dipankar Ray, and Ece Kamar · 2022
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CommunityLM: Probing partisan worldviews from language models
Hang Jiang, Doug Beeferman, Brandon Roy, and Deb Roy · 2022
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The ghost in the machine has an american accent: value conflict in gpt-3, 2022
Rebecca L Johnson, Giada Pistilli, Natalia Menédez-González, Leslye Denisse Dias Duran, Enrico Panai, Julija Kalpokiene, and Donald Jay Bertulfo · 2022
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Language models (mostly) know what they know, 2022
Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield-Dodds, Nova DasSarma, Eli Tran-Johnson, Scott Johnston, Sheer El-Showk, Andy Jones, Nelson Elhage, Tristan Hume, Anna Chen, Yuntao Bai, Sam Bowman, Stanislav Fort, Deep Ganguli, Danny Hernandez, Josh Jacobson, Jackson Kernion, Shauna Kravec, Liane Lovitt, Kamal Ndousse, Catherine Olsson, Sam Ringer, Dario Amodei, Tom Brown, Jack Clark, Nicholas Joseph, Ben Mann, Sam McCandlish, Chris Olah, and Jared Kaplan · 2022
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The disagreement deconvolution: Bringing machine learning performance metrics in line with reality
Mitchell L. Gordon, Kaitlyn Zhou, Kayur Patel, Tatsunori Hashimoto, and Michael S. Bernstein · 2021
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Aligning {ai} with shared human values
Dan Hendrycks, Collin Burns, Steven Basart, Andrew Critch, Jerry Li, Dawn Song, and Jacob Steinhardt · 2021
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The importance of modeling social factors of language: Theory and practice
Dirk Hovy and Diyi Yang · 2021
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Towards understanding and mitigating social biases in language models
Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, and Ruslan Salakhutdinov · 2021
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Gender and representation bias in GPT-3 generated stories
Li Lucy and David Bamman · 2021
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StereoSet: Measuring stereotypical bias in pretrained language models
Moin Nadeem, Anna Bethke, and Siva Reddy · 2021
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Data and its (dis)contents: A survey of dataset development and use in machine learning research
Amandalynne Paullada, Inioluwa Deborah Raji, Emily M. Bender, Emily Denton, and Alex Hanna · 2021
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Estimating the Personality of White-Box Language Models
Saketh Reddy Karra, Son The Nguyen, and Theja Tulabandhula · 2022
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Holistic evaluation of language models, 2022
Percy Liang, Rishi Bommasani, Tony Lee, Dimitris Tsipras, Dilara Soylu, Michihiro Yasunaga, Yian Zhang, Deepak Narayanan, Yuhuai Wu, Ananya Kumar, Benjamin Newman, Binhang Yuan, Bobby Yan, Ce Zhang, Christian Cosgrove, Christopher D. Manning, Christopher Ré, Diana Acosta-Navas, Drew A. Hudson, Eric Zelikman, Esin Durmus, Faisal Ladhak, Frieda Rong, Hongyu Ren, Huaxiu Yao, Jue Wang, Keshav Santhanam, Laurel Orr, Lucia Zheng, Mert Yuksekgonul, Mirac Suzgun, Nathan Kim, Neel Guha, Niladri Chatterji, Omar Khattab, Peter Henderson, Qian Huang, Ryan Chi, Sang Michael Xie, Shibani Santurkar, Surya Ganguli, Tatsunori Hashimoto, Thomas Icard, Tianyi Zhang, Vishrav Chaudhary, William Wang, Xuechen Li, Yifan Mai, Yuhui Zhang, and Yuta Koreeda · 2022
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Fantastically ordered prompts and where to find them: Overcoming few-shot prompt order sensitivity
Yao Lu, Max Bartolo, Alastair Moore, Sebastian Riedel, and Pontus Stenetorp · 2022
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Social simulacra: Creating populated prototypes for social computing systems
Joon Sung Park, Lindsay Popowski, Carrie Cai, Meredith Ringel Morris, Percy Liang, and Michael S. Bernstein · 2022
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A human rights-based approach to responsible ai, 2022
Vinodkumar Prabhakaran, Margaret Mitchell, Timnit Gebru, and Iason Gabriel · 2022
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Characteristics of harmful text: Towards rigorous benchmarking of language models, 2022
Maribeth Rauh, John Mellor, Jonathan Uesato, Po-Sen Huang, Johannes Welbl, Laura Weidinger, Sumanth Dathathri, Amelia Glaese, Geoffrey Irving, Iason Gabriel, William Isaac, and Lisa Anne Hendricks · 2022
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Annotators with attitudes: How annotator beliefs and identities bias toxic language detection
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Moral mimicry: Large language models produce moral rationalizations tailored to political identity, 2022
Gabriel Simmons · 2022
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Manifestations of xenophobia in ai systems, 2022
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Taxonomy of risks posed by language models
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Probing pre-trained language models for cross-cultural differences in values
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