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As increasingly powerful generative AI systems are developed, the release method greatly varies.
Gradio: Hassle-free sharing and testing of ML models in the wild
A. Abid, A. Abdalla, A. Abid, D. Khan, A. Alfozan, and J. Y. Zou · 1906
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Let’s keep it safe: Designing user interfaces that allow everyone to contribute to ai safety, 2019
T. Mandel, J. Best, R. H. Tanaka, H. Temple, C. Haili, K. Schlectinger, and R. Szeto · 1907
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A. Ovadya and J. Whittlestone · 1907
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Release strategies and the social impacts of language models
I. Solaiman, M. Brundage, J. Clark, A. Askell, A. Herbert-Voss, J. Wu, A. Radford, and J. Wang · 1908
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Deep learning for deepfakes creation and detection
T. T. Nguyen, C. M. Nguyen, D. T. Nguyen, D. T. Nguyen, and S. Nahavandi · 1909
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Robust invisible video watermarking with attention
K. A. Zhang, L. Xu, A. Cuesta-Infante, and K. Veeramachaneni · 1909
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The tension between openness and prudence in AI research
J. Whittlestone and A. Ovadya · 1910
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The offense-defense balance of scientific knowledge: Does publishing AI research reduce misuse?
T. Shevlane and A. Dafoe · 2001
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Limits of detecting text generated by large-scale language models
L. R. Varshney, N. S. Keskar, and R. Socher · 2002
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Toward trustworthy ai development: Mechanisms for supporting verifiable claims, 2020
M. Brundage, S. Avin, J. Wang, H. Belfield, G. Krueger, G. Hadfield, H. Khlaaf, J. Yang, H. Toner, R. Fong, T. Maharaj, P. W. Koh, S. Hooker, J. Leung, A. Trask, E. Bluemke, J. Lebensold, C. O’Keefe, M. Koren, T. Ryffel, J. Rubinovitz, T. Besiroglu, F. Carugati, J. Clark, P. Eckersley, S. de Haas, M. Johnson, B. Laurie, A. Ingerman, I. Krawczuk, A. Askell, R. Cammarota, A. Lohn, D. Krueger, C. Stix, P. Henderson, L. Graham, C. Prunkl, B. Martin, E. Seger, N. Zilberman, S. Ó. hÉigeartaigh, F. Kroeger, G. Sastry, R. Kagan, A. Weller, B. Tse, E. Barnes, A. Dafoe, P. Scharre, A. Herbert-Voss, M. Rasser, S. Sodhani, C. Flynn, T. K. Gilbert, L. Dyer, S. Khan, Y. Bengio, and M. Anderljung · 2004
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Decolonial AI: decolonial theory as sociotechnical foresight in artificial intelligence
S. Mohamed, M. Png, and W. Isaac · 2007
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The radicalization risks of GPT-3 and advanced neural language models
K. McGuffie and A. Newhouse · 2009
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Crows-pairs: A challenge dataset for measuring social biases in masked language models
N. Nangia, C. Vania, R. Bhalerao, and S. R. Bowman · 2010
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Behavioral use licensing for responsible AI
D. Contractor, D. McDuff, J. K. Haines, J. Lee, C. Hines, and B. J. Hecht · 2011
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Automatic detection of machine generated text: A critical survey
G. Jawahar, M. Abdul-Mageed, and L. V. S. Lakshmanan · 2011
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DNN intellectual property protection: Taxonomy, methods, attack resistance, and evaluations
M. Xue, C. He, J. Wang, and W. Liu · 2011
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Extracting training data from large language models
N. Carlini, F. Tramèr, E. Wallace, M. Jagielski, A. Herbert-Voss, K. Lee, A. Roberts, T. B. Brown, D. Song, Ú. Erlingsson, A. Oprea, and C. Raffel · 2012
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Social coding in github: Transparency and collaboration in an open software repository
L. Dabbish, C. Stuart, J. Tsay, and J. Herbsleb · 2012
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The challenges of data quality and data quality assessment in the big data era
L. Cai and Y. Zhu · 2015
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Semantics derived automatically from language corpora contain human-like biases
A. Caliskan, J. J. Bryson, and A. Narayanan · 2017
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The moral machine experiment
E. Awad, S. Dsouza, R. Kim, J. Schulz, J. Henrich, A. Shariff, J. F. Bonnefon, and I. Rahwan · 2018
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Data statements for natural language processing: Toward mitigating system bias and enabling better science
E. M. Bender and B. Friedman · 2018
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The malicious use of artificial intelligence: Forecasting, prevention, and mitigation
M. Brundage, S. Avin, J. Clark, H. Toner, P. Eckersley, B. Garfinkel, A. Dafoe, P. Scharre, T. Zeitzoff, B. Filar, H. S. Anderson, H. Roff, G. C. Allen, J. Steinhardt, C. Flynn, S. Ó. hÉigeartaigh, S. Beard, H. Belfield, S. Farquhar, C. Lyle, R. Crootof, O. Evans, M. Page, J. Bryson, R. Yampolskiy, and D. Amodei · 2018
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T. Gebru, J. Morgenstern, B. Vecchione, J. W. Vaughan, H. M. Wallach, H. D. III, and K. Crawford · 2018
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Model cards for model reporting
M. Mitchell, S. Wu, A. Zaldivar, P. Barnes, L. Vasserman, B. Hutchinson, E. Spitzer, I. D. Raji, and T. Gebru · 2018
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Algorithms of oppression how search engines reinforce racism
S. U. Noble · 2018
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Bias bounty programs as a method of combatting bias in ai, 2018
J. Rubinovitz · 2018
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Ai as the next gpt: a political-economy perspective
M. Trajtenberg · 2018
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Protecting intellectual property of deep neural networks with watermarking
J. Zhang, Z. Gu, J. Jang, H. Wu, M. P. Stoecklin, H. Huang, and I. Molloy · 2018
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Don’t let industry write the rules for ai
Y. Benkler · 2019
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GLTR: Statistical detection and visualization of generated text
S. Gehrmann, H. Strobelt, and A. Rush · 2019
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Openai trains language model, mass hysteria ensues, Feb 2019
Z. C. Lipton · 2019
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Gpt-2 model card, Nov 2019
OpenAI · 2019
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Race after technology: Abolitionist Tools for the new jim code
R. Benjamin · 2020
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Language (technology) is power: A critical survey of “bias” in NLP
S. L. Blodgett, S. Barocas, H. Daumé III, and H. Wallach · 2020
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Openai api, Jun 2020
G. Brockman, M. Murati, P. Welinder, and OpenAI · 2020
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Hardware-assisted intellectual property protection of deep learning models
A. Chakraborty, A. Mondal, and A. Srivastava · 2020
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Google told its scientists to ’strike a positive tone’ in ai research - documents
P. Dave and J. Dastin · 2020
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Don’t ask if artificial intelligence is good or fair, ask how it shifts power
P. Kalluri · 2020
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The ai-based cyber threat landscape: A survey
N. Kaloudi and J. Li · 2020
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Palm: Scaling language modeling with pathways, 2022
A. Chowdhery, S. Narang, J. Devlin, M. Bosma, G. Mishra, A. Roberts, P. Barham, H. W. Chung, C. Sutton, S. Gehrmann, P. Schuh, K. Shi, S. Tsvyashchenko, J. Maynez, A. Rao, P. Barnes, Y. Tay, N. Shazeer, V. Prabhakaran, E. Reif, N. Du, B. Hutchinson, R. Pope, J. Bradbury, J. Austin, M. Isard, G. Gur-Ari, P. Yin, T. Duke, A. Levskaya, S. Ghemawat, S. Dev, H. Michalewski, X. Garcia, V. Misra, K. Robinson, L. Fedus, D. Zhou, D. Ippolito, D. Luan, H. Lim, B. Zoph, A. Spiridonov, R. Sepassi, D. Dohan, S. Agrawal, M. Omernick, A. M. Dai, T. S. Pillai, M. Pellat, A. Lewkowycz, E. Moreira, R. Child, O. Polozov, K. Lee, Z. Zhou, X. Wang, B. Saeta, M. Diaz, O. Firat, M. Catasta, J. Wei, K. Meier-Hellstern, D. Eck, J. Dean, S. Petrov, and N. Fiedel · 2022
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Interactive model cards: A human-centered approach to model documentation
A. Crisan, M. Drouhard, J. Vig, and N. Rajani · 2022
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Proceedings of BigScience Episode #5 – Workshop on Challenges & Perspectives in Creating Large Language Models , virtual+Dublin, May 2022. Association for Computational Linguistics
A. Fan, S. Ilic, T. Wolf, and M. Gallé, editors · 2022
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Detection of AI-Generated Synthetic Faces , pages 191–212
D. Gragnaniello, F. Marra, and L. Verdoliva · 2022
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All the news that’s fit to fabricate: Ai-generated text as a tool of media misinformation
S. Kreps, R. M. McCain, and M. Brundage · 2020
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Gpt-3 model card, Sep 2020
OpenAI · 2020
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Closing the ai accountability gap: Defining an end-to-end framework for internal algorithmic auditing
I. D. Raji, A. Smart, R. N. White, M. Mitchell, T. Gebru, B. Hutchinson, J. Smith-Loud, D. Theron, and P. Barnes · 2020
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On the dangers of stochastic parrots: Can language models be too big?
E. M. Bender, T. Gebru, A. McMillan-Major, and S. Shmitchell · 2021
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A systematic review on model watermarking for neural networks
F. Boenisch · 2021
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On the opportunities and risks of foundation models
R. Bommasani, D. A. Hudson, E. Adeli, R. Altman, S. Arora, S. von Arx, M. S. Bernstein, J. Bohg, A. Bosselut, E. Brunskill, E. Brynjolfsson, S. Buch, D. Card, R. Castellon, N. S. Chatterji, A. S. Chen, K. Creel, J. Q. Davis, D. Demszky, C. Donahue, M. Doumbouya, E. Durmus, S. Ermon, J. Etchemendy, K. Ethayarajh, L. Fei-Fei, C. Finn, T. Gale, L. Gillespie, K. Goel, N. D. Goodman, S. Grossman, N. Guha, T. Hashimoto, P. Henderson, J. Hewitt, D. E. Ho, J. Hong, K. Hsu, J. Huang, T. Icard, S. Jain, D. Jurafsky, P. Kalluri, S. Karamcheti, G. Keeling, F. Khani, O. Khattab, P. W. Koh, M. S. Krass, R. Krishna, R. Kuditipudi, and et al · 2021
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Why meta’s latest large language model survived only three days online, Nov 2022
W. D. Heaven · 2022
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A hazard analysis framework for code synthesis large language models, 2022
H. Khlaaf, P. Mishkin, J. Achiam, G. Krueger, and M. Brundage · 2022
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Foundation model tracker
T. Liao · 2022
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What do nlp researchers believe? results of the nlp community metasurvey, 2022
J. Michael, A. Holtzman, A. Parrish, A. Mueller, A. Wang, A. Chen, D. Madaan, N. Nangia, R. Y. Pang, J. Phang, and S. R. Bowman · 2022
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Microsoft turing academic program (ms-tap), Oct 2022
Microsoft · 2022
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Quick start guide, 2022
Midjourney · 2022
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Dall·e 2 preview - risks and limitations
P. Mishkin, L. Ahmad, M. Brundage, G. Krueger, and G. Sastry · 2022
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Stable diffusion public release, Sep 2022
E. Mostaque · 2022
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Training language models to follow instructions with human feedback, 2022
L. Ouyang, J. Wu, X. Jiang, D. Almeida, C. L. Wainwright, P. Mishkin, C. Zhang, S. Agarwal, K. Slama, A. Ray, J. Schulman, J. Hilton, F. Kelton, L. Miller, M. Simens, A. Askell, P. Welinder, P. Christiano, J. Leike, and R. Lowe · 2022
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System-level transparency of machine learning
C. Procope, A. Cheema, D. Adkins, B. Alsallakh, N. Green, E. McReynolds, G. Pehl, E. Wang, and P. Zvyagina · 2022
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Outsider oversight: Designing a third party audit ecosystem for ai governance
I. D. Raji, P. Xu, C. Honigsberg, and D. Ho · 2022
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Hierarchical text-conditional image generation with clip latents, 2022
A. Ramesh, P. Dhariwal, A. Nichol, C. Chu, and M. Chen · 2022
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Red-teaming the stable diffusion safety filter, 2022
J. Rando, D. Paleka, D. Lindner, L. Heim, and F. Tramèr · 2022
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Now ai can write students’ essays for them, will everyone become a cheat?, Nov 2022
R. Reich · 2022
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Stable-diffusion license, Aug 2022
R. Rombach and P. Esser · 2022
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High-resolution image synthesis with latent diffusion models
R. Rombach, A. Blattmann, D. Lorenz, P. Esser, and B. Ommer · 2022
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Photorealistic text-to-image diffusion models with deep language understanding, 2022
C. Saharia, W. Chan, S. Saxena, L. Li, J. Whang, E. Denton, S. K. S. Ghasemipour, B. K. Ayan, S. S. Mahdavi, R. G. Lopes, T. Salimans, J. Ho, D. J. Fleet, and M. Norouzi · 2022
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Sociotechnical harms: Scoping a taxonomy for harm reduction, 2022
R. Shelby, S. Rismani, K. Henne, A. Moon, N. Rostamzadeh, P. Nicholas, N. Yilla, J. Gallegos, A. Smart, E. Garcia, and G. Virk · 2022
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Structured access: an emerging paradigm for safe ai deployment, 2022
T. Shevlane · 2022
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Make-a-video: Text-to-video generation without text-video data, 2022
U. Singer, A. Polyak, T. Hayes, X. Yin, J. An, S. Zhang, Q. Hu, H. Yang, O. Ashual, O. Gafni, D. Parikh, S. Gupta, and Y. Taigman · 2022
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Publication norms for responsible ai, Dec 2022
P. Staff · 2022
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You reap what you sow: On the challenges of bias evaluation under multilingual settings
Z. Talat, A. Névéol, S. Biderman, M. Clinciu, M. Dey, S. Longpre, S. Luccioni, M. Masoud, M. Mitchell, D. Radev, S. Sharma, A. Subramonian, J. Tae, S. Tan, D. Tunuguntla, and O. Van Der Wal · 2022
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Lamda: Language models for dialog applications, 2022
R. Thoppilan, D. De Freitas, J. Hall, N. Shazeer, A. Kulshreshtha, H.-T. Cheng, A. Jin, T. Bos, L. Baker, Y. Du, Y. Li, H. Lee, H. S. Zheng, A. Ghafouri, M. Menegali, Y. Huang, M. Krikun, D. Lepikhin, J. Qin, D. Chen, Y. Xu, Z. Chen, A. Roberts, M. Bosma, V. Zhao, Y. Zhou, C.-C. Chang, I. Krivokon, W. Rusch, M. Pickett, P. Srinivasan, L. Man, K. Meier-Hellstern, M. R. Morris, T. Doshi, R. D. Santos, T. Duke, J. Soraker, B. Zevenbergen, V. Prabhakaran, M. Diaz, B. Hutchinson, K. Olson, A. Molina, E. Hoffman-John, J. Lee, L. Aroyo, R. Rajakumar, A. Butryna, M. Lamm, V. Kuzmina, J. Fenton, A. Cohen, R. Bernstein, R. Kurzweil, B. Aguera-Arcas, C. Cui, M. Croak, E. Chi, and Q. Le · 2022
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Automated trolling: The case of gpt-4chan when artificial intelligence is as easy as writing
A. Vee · 2022
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Limits and possibilities for “ethical ai” in open source: A study of deepfakes
D. G. Widder, D. Nafus, L. Dabbish, and J. Herbsleb · 2022
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Opt: Open pre-trained transformer language models, 2022
S. Zhang, S. Roller, N. Goyal, M. Artetxe, M. Chen, S. Chen, C. Dewan, M. Diab, X. Li, X. V. Lin, T. Mihaylov, M. Ott, S. Shleifer, K. Shuster, D. Simig, P. S. Koura, A. Sridhar, T. Wang, and L. Zettlemoyer · 2022
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J. A. Goldstein, G. Sastry, M. Musser, R. DiResta, M. Gentzel, and K. Sedova · 2023
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A watermark for large language models, 2023
J. Kirchenbauer, J. Geiping, Y. Wen, J. Katz, I. Miers, and T. Goldstein · 2023
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The social impact of natural language processing
D. Hovy and S. L. Spruit · 2096
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