{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,24]],"date-time":"2026-06-24T05:58:14Z","timestamp":1782280694953,"version":"3.54.5"},"publisher-location":"New York, NY, USA","reference-count":71,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,8,8]],"date-time":"2023-08-08T00:00:00Z","timestamp":1691452800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,8,8]]},"DOI":"10.1145\/3600211.3604686","type":"proceedings-article","created":{"date-parts":[[2023,8,29]],"date-time":"2023-08-29T18:41:37Z","timestamp":1693334497000},"page":"146-161","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":37,"title":["The Ethical Implications of Generative Audio Models: A Systematic Literature Review"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3476-1110","authenticated-orcid":false,"given":"Julia","family":"Barnett","sequence":"first","affiliation":[{"name":"Northwestern University, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,8,29]]},"reference":[{"key":"e_1_3_2_1_1_1","volume-title":"The economics of artificial intelligence: An agenda","author":"Acemoglu Daron","unstructured":"Daron Acemoglu and Pascual Restrepo. 2018. Artificial intelligence, automation, and work. In The economics of artificial intelligence: An agenda. University of Chicago Press, 197\u2013236."},{"key":"e_1_3_2_1_2_1","volume-title":"MusicLM: Generating Music From Text. arXiv preprint arXiv:2301.11325","author":"Agostinelli Andrea","year":"2023","unstructured":"Andrea Agostinelli, Timo\u00a0I Denk, Zal\u00e1n Borsos, Jesse Engel, Mauro Verzetti, Antoine Caillon, Qingqing Huang, Aren Jansen, Adam Roberts, Marco Tagliasacchi, 2023. MusicLM: Generating Music From Text. arXiv preprint arXiv:2301.11325 (2023)."},{"key":"e_1_3_2_1_3_1","volume-title":"The growing influence of industry in AI research. Science 379, 6635","author":"Ahmed Nur","year":"2023","unstructured":"Nur Ahmed, Muntasir Wahed, and Neil\u00a0C Thompson. 2023. The growing influence of industry in AI research. Science 379, 6635 (2023), 884\u2013886."},{"key":"e_1_3_2_1_4_1","volume-title":"Carbontracker: Tracking and predicting the carbon footprint of training deep learning models. arXiv preprint arXiv:2007.03051","author":"F\u00a0Wolff Anthony Lasse","year":"2020","unstructured":"Lasse F\u00a0Wolff Anthony, Benjamin Kanding, and Raghavendra Selvan. 2020. Carbontracker: Tracking and predicting the carbon footprint of training deep learning models. arXiv preprint arXiv:2007.03051 (2020)."},{"key":"e_1_3_2_1_5_1","unstructured":"arXiv. 2023. About arXiv. https:\/\/info.arxiv.org\/about\/index.html"},{"key":"e_1_3_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/3503161.3547797"},{"key":"e_1_3_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514094.3534145"},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2117261118"},{"key":"e_1_3_2_1_9_1","volume-title":"Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models","author":"Bond-Taylor Sam","year":"2021","unstructured":"Sam Bond-Taylor, Adam Leach, Yang Long, and Chris\u00a0G Willcocks. 2021. Deep generative modelling: A comparative review of vaes, gans, normalizing flows, energy-based and autoregressive models. IEEE transactions on pattern analysis and machine intelligence (2021)."},{"key":"e_1_3_2_1_10_1","volume-title":"The malicious use of artificial intelligence: Forecasting, prevention, and mitigation. arXiv preprint arXiv:1802.07228","author":"Brundage Miles","year":"2018","unstructured":"Miles Brundage, Shahar Avin, Jack Clark, Helen Toner, Peter Eckersley, Ben Garfinkel, Allan Dafoe, Paul Scharre, Thomas Zeitzoff, Bobby Filar, 2018. The malicious use of artificial intelligence: Forecasting, prevention, and mitigation. arXiv preprint arXiv:1802.07228 (2018)."},{"key":"e_1_3_2_1_11_1","volume-title":"Quantifying memorization across neural language models. arXiv preprint arXiv:2202.07646","author":"Carlini Nicholas","year":"2022","unstructured":"Nicholas Carlini, Daphne Ippolito, Matthew Jagielski, Katherine Lee, Florian Tramer, and Chiyuan Zhang. 2022. Quantifying memorization across neural language models. arXiv preprint arXiv:2202.07646 (2022)."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.3152\/146155109X454285"},{"key":"e_1_3_2_1_13_1","volume-title":"Attributable Watermarking of Speech Generative Models. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 3069\u20133073","author":"Cho Yongbaek","year":"2022","unstructured":"Yongbaek Cho, Changhoon Kim, Yezhou Yang, and Yi Ren. 2022. Attributable Watermarking of Speech Generative Models. In ICASSP 2022-2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 3069\u20133073."},{"key":"e_1_3_2_1_14_1","volume-title":"Proceedings. Elmar-2004","author":"Delac Kresimir","year":"2004","unstructured":"Kresimir Delac and Mislav Grgic. 2004. A survey of biometric recognition methods. In Proceedings. Elmar-2004. 46th International Symposium on Electronics in Marine. IEEE, 184\u2013193."},{"key":"e_1_3_2_1_15_1","volume-title":"Naturalness-& Timbre-Preserving Real-Time Voice Anonymization. arXiv preprint arXiv:2210.15140","author":"Deng Jiangyi","year":"2022","unstructured":"Jiangyi Deng, Fei Teng, Yanjiao Chen, Xiaofu Chen, Zhaohui Wang, and Wenyuan Xu. 2022. V-Cloak: Intelligibility-, Naturalness-& Timbre-Preserving Real-Time Voice Anonymization. arXiv preprint arXiv:2210.15140 (2022)."},{"key":"e_1_3_2_1_16_1","volume-title":"Jukebox: A generative model for music. arXiv preprint arXiv:2005.00341","author":"Dhariwal Prafulla","year":"2020","unstructured":"Prafulla Dhariwal, Heewoo Jun, Christine Payne, Jong\u00a0Wook Kim, Alec Radford, and Ilya Sutskever. 2020. Jukebox: A generative model for music. arXiv preprint arXiv:2005.00341 (2020)."},{"key":"e_1_3_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1177\/1461444820925811"},{"key":"e_1_3_2_1_18_1","volume-title":"Energy Consumption of Deep Generative Audio Models. arXiv preprint arXiv:2107.02621","author":"Douwes Constance","year":"2021","unstructured":"Constance Douwes, Philippe Esling, and Jean-Pierre Briot. 2021. Energy Consumption of Deep Generative Audio Models. arXiv preprint arXiv:2107.02621 (2021)."},{"key":"e_1_3_2_1_19_1","unstructured":"Edelman. 2019. 2019 Edelman AI Survey."},{"key":"e_1_3_2_1_20_1","volume-title":"Challenges in creative generative models for music: a divergence maximization perspective. arXiv preprint arXiv:2211.08856","author":"Philippe Esling","year":"2022","unstructured":"Philippe Esling 2022. Challenges in creative generative models for music: a divergence maximization perspective. arXiv preprint arXiv:2211.08856 (2022)."},{"key":"e_1_3_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/3313831.3376514"},{"key":"e_1_3_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/3306346.3323028"},{"key":"e_1_3_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TMM.2020.3005033"},{"key":"e_1_3_2_1_24_1","volume-title":"Semi-supervised generative modeling for controllable speech synthesis. arXiv preprint arXiv:1910.01709","author":"Habib Raza","year":"2019","unstructured":"Raza Habib, Soroosh Mariooryad, Matt Shannon, Eric Battenberg, RJ Skerry-Ryan, Daisy Stanton, David Kao, and Tom Bagby. 2019. Semi-supervised generative modeling for controllable speech synthesis. arXiv preprint arXiv:1910.01709 (2019)."},{"key":"e_1_3_2_1_25_1","volume-title":"It\u2019s time to do something: Mitigating the negative impacts of computing through a change to the peer review process. arXiv preprint arXiv:2112.09544","author":"Hecht Brent","year":"2021","unstructured":"Brent Hecht, Lauren Wilcox, Jeffrey\u00a0P Bigham, Johannes Sch\u00f6ning, Ehsan Hoque, Jason Ernst, Yonatan Bisk, Luigi De\u00a0Russis, Lana Yarosh, Bushra Anjum, 2021. It\u2019s time to do something: Mitigating the negative impacts of computing through a change to the peer review process. arXiv preprint arXiv:2112.09544 (2021)."},{"key":"e_1_3_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.3152\/095820211X12941371876788"},{"key":"e_1_3_2_1_27_1","volume-title":"Monica Dinculescu, and Carrie\u00a0J Cai.","author":"Huang Zhi\u00a0Anna","year":"2020","unstructured":"Cheng-Zhi\u00a0Anna Huang, Hendrik\u00a0Vincent Koops, Ed Newton-Rex, Monica Dinculescu, and Carrie\u00a0J Cai. 2020. AI song contest: Human-AI co-creation in songwriting. arXiv preprint arXiv:2010.05388 (2020)."},{"key":"e_1_3_2_1_28_1","volume-title":"Music transformer. arXiv preprint arXiv","author":"Huang Zhi\u00a0Anna","year":"1809","unstructured":"Cheng-Zhi\u00a0Anna Huang, Ashish Vaswani, Jakob Uszkoreit, Noam Shazeer, Ian Simon, Curtis Hawthorne, Andrew\u00a0M Dai, Matthew\u00a0D Hoffman, Monica Dinculescu, and Douglas Eck. 2018. Music transformer. arXiv preprint arXiv: 1809.04281 (2018)."},{"key":"e_1_3_2_1_29_1","volume-title":"Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models. arXiv preprint arXiv:2301.12661","author":"Huang Rongjie","year":"2023","unstructured":"Rongjie Huang, Jiawei Huang, Dongchao Yang, Yi Ren, Luping Liu, Mingze Li, Zhenhui Ye, Jinglin Liu, Xiang Yin, and Zhou Zhao. 2023. Make-An-Audio: Text-To-Audio Generation with Prompt-Enhanced Diffusion Models. arXiv preprint arXiv:2301.12661 (2023)."},{"key":"e_1_3_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1145\/3383652.3423911"},{"key":"e_1_3_2_1_31_1","unstructured":"Paul Keller. 2023. Protecting creatives or impeding progress? Machine Learning and the EU Copyright Framework."},{"key":"e_1_3_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1145\/3461702.3462605"},{"key":"e_1_3_2_1_33_1","doi-asserted-by":"publisher","DOI":"10.1121\/1.1937211"},{"key":"e_1_3_2_1_34_1","first-page":"8067","article-title":"Glow-TTS: A generative flow for text-to-speech via monotonic alignment search","volume":"33","author":"Kim Jaehyeon","year":"2020","unstructured":"Jaehyeon Kim, Sungwon Kim, Jungil Kong, and Sungroh Yoon. 2020. Glow-TTS: A generative flow for text-to-speech via monotonic alignment search. Advances in Neural Information Processing Systems 33 (2020), 8067\u20138077.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"e_1_3_2_1_35_1","volume-title":"International Conference on Machine Learning. PMLR, 5530\u20135540","author":"Kim Jaehyeon","year":"2021","unstructured":"Jaehyeon Kim, Jungil Kong, and Juhee Son. 2021. Conditional variational autoencoder with adversarial learning for end-to-end text-to-speech. In International Conference on Machine Learning. PMLR, 5530\u20135540."},{"key":"e_1_3_2_1_36_1","volume-title":"Guided-TTS 2: A diffusion model for high-quality adaptive text-to-speech with untranscribed data. arXiv preprint arXiv:2205.15370","author":"Kim Sungwon","year":"2022","unstructured":"Sungwon Kim, Heeseung Kim, and Sungroh Yoon. 2022. Guided-TTS 2: A diffusion model for high-quality adaptive text-to-speech with untranscribed data. arXiv preprint arXiv:2205.15370 (2022)."},{"key":"e_1_3_2_1_37_1","doi-asserted-by":"publisher","DOI":"10.1145\/3460120.3484755"},{"key":"e_1_3_2_1_38_1","doi-asserted-by":"publisher","DOI":"10.1002\/asi.22693"},{"key":"e_1_3_2_1_39_1","volume-title":"How much do language models copy from their training data? evaluating linguistic novelty in text generation using raven. arXiv preprint arXiv:2111.09509","author":"McCoy R\u00a0Thomas","year":"2021","unstructured":"R\u00a0Thomas McCoy, Paul Smolensky, Tal Linzen, Jianfeng Gao, and Asli Celikyilmaz. 2021. How much do language models copy from their training data? evaluating linguistic novelty in text generation using raven. arXiv preprint arXiv:2111.09509 (2021)."},{"key":"e_1_3_2_1_40_1","doi-asserted-by":"publisher","DOI":"10.1093\/jiplp\/jpz167"},{"key":"e_1_3_2_1_41_1","doi-asserted-by":"publisher","DOI":"10.1145\/3442188.3445935"},{"key":"e_1_3_2_1_42_1","volume-title":"Article 7 (jan","author":"Mirsky Yisroel","year":"2021","unstructured":"Yisroel Mirsky and Wenke Lee. 2021. The Creation and Detection of Deepfakes: A Survey. ACM Comput. Surv. 54, 1, Article 7 (jan 2021), 41\u00a0pages."},{"key":"e_1_3_2_1_43_1","doi-asserted-by":"publisher","DOI":"10.7326\/0003-4819-151-4-200908180-00135"},{"key":"e_1_3_2_1_44_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.eap.2021.01.012"},{"key":"e_1_3_2_1_45_1","doi-asserted-by":"publisher","DOI":"10.1145\/3461702.3462608"},{"key":"e_1_3_2_1_46_1","unstructured":"OpenAI. 2022. Introducing ChatGPT. https:\/\/openai.com\/blog\/chatgpt"},{"key":"e_1_3_2_1_47_1","volume-title":"Image Transformer. In Proceedings of the 35th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a080)","author":"Parmar Niki","year":"2018","unstructured":"Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, and Dustin Tran. 2018. Image Transformer. In Proceedings of the 35th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol.\u00a080), Jennifer Dy and Andreas Krause (Eds.). PMLR, 4055\u20134064."},{"key":"e_1_3_2_1_48_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICASSP39728.2021.9414853"},{"key":"e_1_3_2_1_49_1","volume-title":"Unsupervised cross-domain singing voice conversion. arXiv preprint arXiv:2008.02830","author":"Polyak Adam","year":"2020","unstructured":"Adam Polyak, Lior Wolf, Yossi Adi, and Yaniv Taigman. 2020. Unsupervised cross-domain singing voice conversion. arXiv preprint arXiv:2008.02830 (2020)."},{"key":"e_1_3_2_1_50_1","volume-title":"Hierarchical text-conditional image generation with clip latents. arXiv preprint arXiv:2204.06125","author":"Ramesh Aditya","year":"2022","unstructured":"Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. 2022. Hierarchical text-conditional image generation with clip latents. arXiv preprint arXiv:2204.06125 (2022)."},{"key":"e_1_3_2_1_51_1","doi-asserted-by":"publisher","DOI":"10.1080\/02691720903364035"},{"key":"e_1_3_2_1_52_1","volume-title":"Ethics and creativity in computer vision. arXiv preprint arXiv:2112.03111","author":"Rostamzadeh Negar","year":"2021","unstructured":"Negar Rostamzadeh, Emily Denton, and Linda Petrini. 2021. Ethics and creativity in computer vision. arXiv preprint arXiv:2112.03111 (2021)."},{"key":"e_1_3_2_1_53_1","doi-asserted-by":"publisher","DOI":"10.18653\/v1\/N18-2074"},{"key":"e_1_3_2_1_54_1","volume-title":"Emilio Garcia","author":"Shelby Renee","year":"2022","unstructured":"Renee Shelby, Shalaleh Rismani, Kathryn Henne, AJung Moon, Negar Rostamzadeh, Paul Nicholas, N\u2019Mah Yilla, Jess Gallegos, Andrew Smart, Emilio Garcia, 2022. Sociotechnical Harms: Scoping a Taxonomy for Harm Reduction. arXiv preprint arXiv:2210.05791 (2022)."},{"key":"e_1_3_2_1_55_1","volume-title":"An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning. 29 (nov","author":"Sisman Berrak","year":"2020","unstructured":"Berrak Sisman, Junichi Yamagishi, Simon King, and Haizhou Li. 2020. An Overview of Voice Conversion and Its Challenges: From Statistical Modeling to Deep Learning. 29 (nov 2020), 132\u2013157."},{"key":"e_1_3_2_1_56_1","volume-title":"Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. arXiv preprint arXiv:2212.03860","author":"Somepalli Gowthami","year":"2022","unstructured":"Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, and Tom Goldstein. 2022. Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. arXiv preprint arXiv:2212.03860 (2022)."},{"key":"e_1_3_2_1_57_1","volume-title":"Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems","author":"Youngblom Emily","year":"2021","unstructured":"Minhyang\u00a0(Mia) Suh, Emily Youngblom, Michael Terry, and Carrie\u00a0J Cai. 2021. AI as Social Glue: Uncovering the Roles of Deep Generative AI during Social Music Composition. In Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems (Yokohama, Japan) (CHI \u201921). Association for Computing Machinery, New York, NY, USA, Article 582, 11\u00a0pages."},{"key":"e_1_3_2_1_58_1","volume-title":"Public health and online misinformation: challenges and recommendations.Annual review of public health 41","author":"Swire-Thompson Briony","year":"2019","unstructured":"Briony Swire-Thompson and David Lazer. 2019. Public health and online misinformation: challenges and recommendations.Annual review of public health 41 (2019), 433\u2013451."},{"key":"e_1_3_2_1_59_1","volume-title":"EdiTTS: Score-based editing for controllable text-to-speech. arXiv preprint arXiv:2110.02584","author":"Tae Jaesung","year":"2021","unstructured":"Jaesung Tae, Hyeongju Kim, and Taesu Kim. 2021. EdiTTS: Score-based editing for controllable text-to-speech. arXiv preprint arXiv:2110.02584 (2021)."},{"key":"e_1_3_2_1_60_1","doi-asserted-by":"publisher","DOI":"10.1145\/3478513.3480570"},{"key":"e_1_3_2_1_61_1","volume-title":"Attention is all you need. Advances in neural information processing systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan\u00a0N Gomez, \u0141ukasz Kaiser, and Illia Polosukhin. 2017. Attention is all you need. Advances in neural information processing systems 30 (2017)."},{"key":"e_1_3_2_1_62_1","volume-title":"Provable Copyright Protection for Generative Models. arXiv preprint arXiv:2302.10870","author":"Vyas Nikhil","year":"2023","unstructured":"Nikhil Vyas, Sham Kakade, and Boaz Barak. 2023. Provable Copyright Protection for Generative Models. arXiv preprint arXiv:2302.10870 (2023)."},{"key":"e_1_3_2_1_63_1","volume-title":"Voice Preserving Translation of Videos. arXiv preprint arXiv:2206.04523","author":"Waibel Alexander","year":"2022","unstructured":"Alexander Waibel, Moritz Behr, Fevziye\u00a0Irem Eyiokur, Dogucan Yaman, Tuan-Nam Nguyen, Carlos Mullov, Mehmet\u00a0Arif Demirtas, Alperen Kantarc\u0131, Stefan Constantin, and Haz\u0131m\u00a0Kemal Ekenel. 2022. Face-Dubbing++: Lip-Synchronous, Voice Preserving Translation of Videos. arXiv preprint arXiv:2206.04523 (2022)."},{"key":"e_1_3_2_1_64_1","doi-asserted-by":"publisher","DOI":"10.1145\/3394171.3413716"},{"key":"e_1_3_2_1_65_1","volume-title":"Ethical and social risks of harm from language models. arXiv preprint arXiv:2112.04359","author":"Weidinger Laura","year":"2021","unstructured":"Laura Weidinger, John Mellor, Maribeth Rauh, Conor Griffin, Jonathan Uesato, Po-Sen Huang, Myra Cheng, Mia Glaese, Borja Balle, Atoosa Kasirzadeh, 2021. Ethical and social risks of harm from language models. arXiv preprint arXiv:2112.04359 (2021)."},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1145\/3414685.3417838"},{"key":"e_1_3_2_1_67_1","volume-title":"Restoring degraded speech via a modified diffusion model. arXiv preprint arXiv:2104.11347","author":"Zhang Jianwei","year":"2021","unstructured":"Jianwei Zhang, Suren Jayasuriya, and Visar Berisha. 2021. Restoring degraded speech via a modified diffusion model. arXiv preprint arXiv:2104.11347 (2021)."},{"key":"e_1_3_2_1_68_1","volume-title":"Vertical-Horizontal Structured Attention for Generating Music with Chords. arXiv preprint arXiv:2011.09078","author":"Zhao Yizhou","year":"2020","unstructured":"Yizhou Zhao, Liang Qiu, Wensi Ai, Feng Shi, and Song-Chun Zhu. 2020. Vertical-Horizontal Structured Attention for Generating Music with Chords. arXiv preprint arXiv:2011.09078 (2020)."},{"key":"e_1_3_2_1_69_1","volume-title":"Voice conversion with conditional SampleRNN. arXiv preprint arXiv:1808.08311","author":"Zhou Cong","year":"2018","unstructured":"Cong Zhou, Michael Horgan, Vivek Kumar, Cristina Vasco, and Dan Darcy. 2018. Voice conversion with conditional SampleRNN. arXiv preprint arXiv:1808.08311 (2018)."},{"key":"e_1_3_2_1_70_1","doi-asserted-by":"publisher","DOI":"10.1145\/3485664"},{"key":"e_1_3_2_1_71_1","volume-title":"Exploring ai ethics of chatgpt: A diagnostic analysis. arXiv preprint arXiv:2301.12867","author":"Zhuo Terry\u00a0Yue","year":"2023","unstructured":"Terry\u00a0Yue Zhuo, Yujin Huang, Chunyang Chen, and Zhenchang Xing. 2023. Exploring ai ethics of chatgpt: A diagnostic analysis. arXiv preprint arXiv:2301.12867 (2023)."}],"event":{"name":"AIES '23: AAAI\/ACM Conference on AI, Ethics, and Society","location":"Montr\u00e9al QC Canada","acronym":"AIES '23","sponsor":["SIGAI ACM Special Interest Group on Artificial Intelligence"]},"container-title":["Proceedings of the 2023 AAAI\/ACM Conference on AI, Ethics, and Society"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3600211.3604686","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3600211.3604686","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T16:37:39Z","timestamp":1750178259000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3600211.3604686"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,8]]},"references-count":71,"alternative-id":["10.1145\/3600211.3604686","10.1145\/3600211"],"URL":"https:\/\/doi.org\/10.1145\/3600211.3604686","relation":{},"subject":[],"published":{"date-parts":[[2023,8,8]]},"assertion":[{"value":"2023-08-29","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}