{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,5]],"date-time":"2026-03-05T18:46:43Z","timestamp":1772736403704,"version":"3.50.1"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T00:00:00Z","timestamp":1726012800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T00:00:00Z","timestamp":1726012800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["AI &amp; Soc"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:title>Abstract<\/jats:title>\n          <jats:p>Debates about the development of artificial superintelligence and its potential threats to humanity tend to assume that such a system would be historically unprecedented, and that its behavior must be predicted from first principles. I argue that this is not true: we can analyze multiagent intelligent systems (the best candidates for practical superintelligence) by comparing them to states, which also unite heterogeneous intelligences to achieve superhuman goals. States provide a model for several problems discussed in the literature on superintelligence, such as principal-agent problems and Instrumental Convergence. Philosophical arguments about governance, therefore, provide possible solutions to these problems, or point out problems in previously suggested solutions. In particular, the liberal concept of checks and balances, and Hannah Arendt\u2019s concept of legitimacy, describe how state behavior is constrained by the preferences of constituents that could also apply to artificial systems. However, they also point out ways in which present-day computational developments could destabilize the international order by reducing the number of decision-makers involved in state actions. Thus, interstate competition not only serves as a model for the behavior of dangerous computational intelligences but also as the impetus for their development.<\/jats:p>","DOI":"10.1007\/s00146-024-02063-2","type":"journal-article","created":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T14:03:20Z","timestamp":1726063400000},"page":"2983-2993","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["The state as a model for AI control and alignment"],"prefix":"10.1007","volume":"40","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1432-2129","authenticated-orcid":false,"given":"Micha","family":"Elsner","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,9,11]]},"reference":[{"key":"2063_CR1","unstructured":"(attr. James Madison) P (1788) Federalist 51: The structure of the government must furnish the proper checks and balances between the different departments. The New York Packet"},{"key":"2063_CR2","volume-title":"On violence","author":"H Arendt","year":"1970","unstructured":"Arendt H (1970) On violence. Harcourt, Brace & World"},{"key":"2063_CR3","unstructured":"Atomic Heritage Foundation (2014). Computing and the manhattan project"},{"key":"2063_CR4","unstructured":"Bai Y, Kadavath S, Kundu S, Askell A, Kernion J, Jones A, Chen A, Goldie A, Mirhoseini A, McKinnon C et\u00a0al (2022) Constitutional ai: Harmlessness from AI feedback. arXiv preprint. arXiv:2212.08073"},{"key":"2063_CR5","unstructured":"Bender E\u00a0M (2023) Talking about a \u2018schism\u2019 is ahistorical. https:\/\/medium.com\/@emilymenonbender\/talking-about-a-schism-is-ahistorical-3c454a77220f, accessed May 2, 2024"},{"issue":"6698","key":"2063_CR6","doi-asserted-by":"publisher","first-page":"842","DOI":"10.1126\/science.adn0117","volume":"384","author":"Y Bengio","year":"2024","unstructured":"Bengio Y, Hinton G, Yao A, Song D, Abbeel P, Darrell T, Harari YN, Zhang Y-Q, Xue L, Shalev-Shwartz S et al (2024) Managing extreme AI risks amid rapid progress. Science 384(6698):842\u2013845","journal-title":"Science"},{"key":"2063_CR7","volume-title":"Race after technology: abolitionist tools for the new Jim code","author":"R Benjamin","year":"2019","unstructured":"Benjamin R (2019) Race after technology: abolitionist tools for the new Jim code. Wiley"},{"key":"2063_CR8","unstructured":"Bianchini F (2013) Emergence from biology to cognition: the case of superorganisms. In: Synthetic modeling of life and cognition: open questions"},{"key":"2063_CR9","doi-asserted-by":"publisher","first-page":"71","DOI":"10.1007\/s11023-012-9281-3","volume":"22","author":"N Bostrom","year":"2012","unstructured":"Bostrom N (2012) The superintelligent will: motivation and instrumental rationality in advanced artificial agents. Mind Mach 22:71\u201385","journal-title":"Mind Mach"},{"issue":"4","key":"2063_CR10","doi-asserted-by":"publisher","first-page":"455","DOI":"10.1111\/1758-5899.12718","volume":"10","author":"N Bostrom","year":"2019","unstructured":"Bostrom N (2019) The vulnerable world hypothesis. Global Pol 10(4):455\u2013476","journal-title":"Global Pol"},{"key":"2063_CR11","unstructured":"Bowman S\u00a0R, Hyun J, Perez E, Chen E, Pettit C, Heiner S, Luko\u0161i\u016bt\u0117 K, Askell A, Jones A, Chen A, et\u00a0al (2022) Measuring progress on scalable oversight for large language models. arXiv preprint. arXiv:2211.03540"},{"key":"2063_CR12","doi-asserted-by":"crossref","unstructured":"Chalmers DJ (2016) The singularity: a philosophical analysis. In: Science fiction and philosophy: from time travel to superintelligence, pp. 171\u2013224","DOI":"10.1002\/9781118922590.ch16"},{"key":"2063_CR13","unstructured":"Colorado Legislature (2024) Concerning consumer protections in interactions with artificial intelligence systems"},{"issue":"5\u20136","key":"2063_CR14","first-page":"128","volume":"24","author":"J Corabi","year":"2017","unstructured":"Corabi J (2017) Superintelligence as moral philosopher. J Conscious Stud 24(5\u20136):128\u2013149","journal-title":"J Conscious Stud"},{"key":"2063_CR15","doi-asserted-by":"publisher","DOI":"10.12987\/9780300252392","volume-title":"The atlas of AI: power, politics, and the planetary costs of artificial intelligence","author":"K Crawford","year":"2021","unstructured":"Crawford K (2021) The atlas of AI: power, politics, and the planetary costs of artificial intelligence. Yale University Press"},{"key":"2063_CR16","doi-asserted-by":"crossref","unstructured":"Cugurullo F (2024) The obscure politics of artificial intelligence: a Marxian socio-technical critique of the AI alignment problem thesis. AI and Ethics, pages 1\u201313","DOI":"10.1007\/s43681-024-00476-9"},{"key":"2063_CR17","unstructured":"Dai J, Pan X, Sun R, Ji J, Xu X, Liu M, Wang Y, Yang Y (2024) Safe rlhf: safe reinforcement learning from human feedback. In: The Twelfth International Conference on Learning Representations (ICLR)"},{"issue":"3","key":"2063_CR18","doi-asserted-by":"publisher","first-page":"495","DOI":"10.1017\/S0140525X00058611","volume":"11","author":"DC Dennett","year":"1988","unstructured":"Dennett DC (1988) Pr\u00e9cis of the intentional stance. Behav Brain Sci 11(3):495\u2013505","journal-title":"Behav Brain Sci"},{"key":"2063_CR19","volume-title":"Automating inequality: how high-tech tools profile, police, and punish the poor","author":"V Eubanks","year":"2018","unstructured":"Eubanks V (2018) Automating inequality: how high-tech tools profile, police, and punish the poor. St. Martin\u2019s Press"},{"key":"2063_CR20","first-page":"456","volume-title":"Superintelligence does not imply benevolence","author":"J Fox","year":"2010","unstructured":"Fox J, Shulman C (2010) Superintelligence does not imply benevolence. ECAP, pp 456\u2013462"},{"key":"2063_CR21","unstructured":"Gallegos I\u00a0O, Rossi R\u00a0A, Barrow J, Tanjim M\u00a0M, Yu T, Deilamsalehy H, Zhang R, Kim S, Dernoncourt F (2024) Self-debiasing large language models: zero-shot recognition and reduction of stereotypes. arXiv preprint. arXiv:2402.01981"},{"key":"2063_CR22","unstructured":"Ganguli D, Askell A, Schiefer N, Liao T\u00a0I, Luko\u0161i\u016bt\u0117 K, Chen A, Goldie A, Mirhoseini A, Olsson C, Hernandez D, et\u00a0al (2023) The capacity for moral self-correction in large language models. arXiv preprint. arXiv:2302.07459"},{"key":"2063_CR23","doi-asserted-by":"crossref","unstructured":"Gebru T, Torres \u00c9\u00a0P (2024) The tescreal bundle: Eugenics and the promise of utopia through artificial general intelligence. First Monday","DOI":"10.5210\/fm.v29i4.13636"},{"key":"2063_CR24","volume-title":"Mismeasure of man","author":"SJ Gould","year":"1996","unstructured":"Gould SJ (1996) Mismeasure of man. WW Norton & company"},{"key":"2063_CR25","unstructured":"Gulcehre C, Paine T\u00a0L, Srinivasan S, Konyushkova K, Weerts L, Sharma A, Siddhant A, Ahern A, Wang M, Gu C et\u00a0al (2023) Reinforced self-training (rest) for language modeling. arXiv preprint. arXiv:2308.08998"},{"key":"2063_CR26","doi-asserted-by":"crossref","unstructured":"Hacker P, Engel A, Mauer M (2023) Regulating chatgpt and other large generative AI models. In: Proceedings of the 2023 ACM conference on fairness, accountability, and transparency, pages 1112\u20131123","DOI":"10.1145\/3593013.3594067"},{"issue":"1","key":"2063_CR27","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1108\/FS-04-2018-0039","volume":"21","author":"O H\u00e4ggstr\u00f6m","year":"2018","unstructured":"H\u00e4ggstr\u00f6m O (2018) Challenges to the omohundro-bostrom framework for AI motivations. Foresight 21(1):153\u2013166","journal-title":"Foresight"},{"issue":"1","key":"2063_CR28","first-page":"57","volume":"6","author":"F Heylighen","year":"2007","unstructured":"Heylighen F (2007) The global superorganism: an evolutionary-cybernetic model of the emerging network society. Soc Evolut History 6(1):57\u2013117","journal-title":"Soc Evolut History"},{"key":"2063_CR29","unstructured":"Hinton G (2023) The so-called \u201cgodfather of the AI\u201d joins the lead to offer a dire warning about the dangers of artificial intelligence"},{"key":"2063_CR30","volume-title":"The superorganism: the beauty elegance and strangeness of insect societies","author":"B Holldobler","year":"2009","unstructured":"Holldobler B, Wilson EO (2009) The superorganism: the beauty elegance and strangeness of insect societies. W. W. Norton & Company"},{"key":"2063_CR31","volume-title":"Inventing Los Alamos: the growth of an atomic community","author":"J Hunner","year":"2007","unstructured":"Hunner J (2007) Inventing Los Alamos: the growth of an atomic community. University of Oklahoma Press"},{"key":"2063_CR32","unstructured":"Inan H, Upasani K, Chi J, Rungta R, Iyer K, Mao Y, Tontchev M, Hu Q, Fuller B, Testuggine D et\u00a0al (2023) Llama guard: Llm-based input-output safeguard for human-AI conversations. arXiv preprint. arXiv:2312.06674"},{"issue":"2","key":"2063_CR33","doi-asserted-by":"publisher","first-page":"167","DOI":"10.2307\/2009958","volume":"30","author":"R Jervis","year":"1978","unstructured":"Jervis R (1978) Cooperation under the security dilemma. World Politics 30(2):167\u2013214","journal-title":"World Politics"},{"key":"2063_CR34","unstructured":"Ji J, Qiu T, Chen B, Zhang B, Lou H, Wang K, Duan Y, He Z, Zhou J, Zhang Z, Zeng F, Ng K\u00a0Y, Dai J, Pan X, O\u2019Gara A, Lei Y, Xu H, Tse B, Fu J, McAleer S, Yang Y, Wang Y, Zhu S-C, Guo Y, Gao W (2024) Ai alignment: a comprehensive survey"},{"key":"2063_CR35","doi-asserted-by":"crossref","unstructured":"Korinek A, Balwit A (2022) Aligned with whom? direct and social goals for AI systems. Technical report, National Bureau of Economic Research","DOI":"10.3386\/w30017"},{"key":"2063_CR36","unstructured":"Kundu S, Bai Y, Kadavath S, Askell A, Callahan A, Chen A, Goldie A, Balwit A, Mirhoseini A, McLean B, et\u00a0al (2023) Specific versus general principles for constitutional AI. arXiv preprint. arXiv:2310.13798"},{"key":"2063_CR37","unstructured":"Liu Y, Yao Y, Ton J-F, Zhang X, Guo R, Cheng H, Klochkov Y, Taufiq M\u00a0F, Li H (2023) Trustworthy llms: a survey and guideline for evaluating large language models\u2019 alignment. In: Socially Responsible Language Modelling Research"},{"key":"2063_CR38","unstructured":"McClain C (2024) Americans\u2019 use of chatgpt is ticking up, but few trust its election information"},{"key":"2063_CR39","doi-asserted-by":"crossref","unstructured":"McIntosh T\u00a0R, Susnjak T, Liu T, Watters P, Halgamuge M\u00a0N (2024) The inadequacy of reinforcement learning from human feedback-radicalizing large language models via semantic vulnerabilities. IEEE Trans Cogn Develop Syst","DOI":"10.1109\/TCDS.2024.3377445"},{"key":"2063_CR40","volume-title":"To save everything, click here: the folly of technological solutionism","author":"E Morozov","year":"2013","unstructured":"Morozov E (2013) To save everything, click here: the folly of technological solutionism. Public Affairs"},{"key":"2063_CR41","unstructured":"Nardo C (2023) The waluigi effect"},{"key":"2063_CR42","unstructured":"Ngo R, Chan L, Mindermann S (2022) The alignment problem from a deep learning perspective. arXiv preprint. arXiv:2209.00626"},{"key":"2063_CR43","unstructured":"O\u2019Neill C, Miller J, Ciuca I, Ting Y-S, Bui T (2023) Adversarial fine-tuning of language models: an iterative optimisation approach for the generation and detection of problematic content. arXiv preprint. arXiv:2308.13768"},{"key":"2063_CR44","unstructured":"OpenAI, Achiam J, Adler S, Agarwal S, Ahmad L, Akkaya I, Aleman F.\u00a0L, Almeida D, Altenschmidt J, Altman S, Anadkat S, Avila R, Babuschkin I, Balaji S, Balcom V, Baltescu P, Bao H, Bavarian M, Belgum J, Bello I, Berdine J, Bernadett-Shapiro G, Berner C, Bogdonoff L, Boiko O, Boyd M, Brakman A.-L, Brockman G, Brooks T, Brundage M, Button K, Cai T, Campbell R, Cann A, Carey B, Carlson C, Carmichael R, Chan B, Chang C, Chantzis F, Chen D, Chen S, Chen R, Chen J, Chen M, Chess B, Cho C, Chu C, Chung H.\u00a0W, Cummings D, Currier J, Dai Y, Decareaux C, Degry T, Deutsch N, Deville D, Dhar A, Dohan D, Dowling S, Dunning S, Ecoffet A, Eleti A, Eloundou T, Farhi D, Fedus L, Felix N, Fishman S.\u00a0P, Forte J, Fulford I, Gao L, Georges E, Gibson C, Goel V, Gogineni T, Goh G, Gontijo-Lopes R, Gordon J, Grafstein M, Gray S, Greene R, Gross J, Gu S.\u00a0S, Guo Y, Hallacy C, Han J, Harris J, He Y, Heaton M, Heidecke J, Hesse C, Hickey A, Hickey W, Hoeschele P, Houghton B, Hsu K, Hu S, Hu X, Huizinga J, Jain S, Jain S, Jang J, Jiang A, Jiang R, Jin H, Jin D, Jomoto S, Jonn B, Jun H, Kaftan T, Lukasz Kaiser Kamali A, Kanitscheider I, Keskar N.\u00a0S, Khan T, Kilpatrick L, Kim J.\u00a0W, Kim C, Kim Y, Kirchner J.\u00a0H, Kiros J, Knight M, Kokotajlo D, Lukasz Kondraciuk Kondrich A, Konstantinidis A, Kosic K, Krueger G, Kuo V, Lampe M, Lan I, Lee T, Leike J, Leung J, Levy D, Li C.\u00a0M, Lim R, Lin M, Lin S, Litwin M, Lopez T, Lowe R, Lue P, Makanju A, Malfacini K, Manning S, Markov T, Markovski Y, Martin B, Mayer K, Mayne A, McGrew B, McKinney S.\u00a0M, McLeavey C, McMillan P, McNeil J, Medina D, Mehta A, Menick J, Metz L, Mishchenko A, Mishkin P, Monaco V, Morikawa E, Mossing D, Mu T, Murati M, Murk O, M\u00e9ly D, Nair A, Nakano R, Nayak R, Neelakantan A, Ngo R, Noh H, Ouyang L, O\u2019Keefe C, Pachocki J, Paino A, Palermo J, Pantuliano A, Parascandolo G, Parish J, Parparita E, Passos A, Pavlov M, Peng A, Perelman A, de\u00a0Avila Belbute\u00a0Peres F, Petrov M, de\u00a0Oliveira\u00a0Pinto H.\u00a0P, Michael Pokorny Pokrass M, Pong V.\u00a0H, Powell T, Power A, Power B, Proehl E, Puri R, Radford A, Rae J, Ramesh A, Raymond C, Real F, Rimbach K, Ross C, Rotsted B, Roussez H, Ryder N, Saltarelli M, Sanders T, Santurkar S, Sastry G, Schmidt H, Schnurr D, Schulman J, Selsam D, Sheppard K, Sherbakov T, Shieh J, Shoker S, Shyam P, Sidor S, Sigler E, Simens M, Sitkin J, Slama K, Sohl I, Sokolowsky B, Song Y, Staudacher N, Such F.\u00a0P, Summers N, Sutskever I, Tang J, Tezak N, Thompson M.\u00a0B, Tillet P, Tootoonchian A, Tseng E, Tuggle P, Turley N, Tworek J, Uribe J, F.\u00a0C, Vallone A, Vijayvergiya A, Voss C, Wainwright C, Wang J.\u00a0J, Wang A, Wang B, Ward J, Wei J, Weinmann C, Welihinda A, Welinder P, Weng J, Weng L, Wiethoff M, Willner D, Winter C, Wolrich S, Wong H, Workman L, Wu S, Wu J, Wu M, Xiao K, Xu T, Yoo S, Yu K, Yuan Q, Zaremba W, Zellers R, Zhang C, Zhang M, Zhao S, Zheng T, Zhuang J, Zhuk W, Zoph B (2024) Gpt-4 technical report"},{"key":"2063_CR45","first-page":"27730","volume":"35","author":"L Ouyang","year":"2022","unstructured":"Ouyang L, Wu J, Jiang X, Almeida D, Wainwright C, Mishkin P, Zhang C, Agarwal S, Slama K, Ray A et al (2022) Training language models to follow instructions with human feedback. Adv Neural Inf Process Syst (NeurIPS) 35:27730\u201327744","journal-title":"Adv Neural Inf Process Syst (NeurIPS)"},{"key":"2063_CR46","doi-asserted-by":"crossref","unstructured":"Park P\u00a0S, Goldstein S, O\u2019Gara A, Chen M, Hendrycks D (2024) AI deception: a survey of examples, risks, and potential solutions. Patterns 5(5)","DOI":"10.1016\/j.patter.2024.100988"},{"key":"2063_CR47","unstructured":"Parliament T\u00a0E, the Council of\u00a0the European\u00a0Union (2024).Regulation (eu) 2024\/1689 of the European parliament and of the council of 13 June 2024 laying down Harmonised rules on artificial intelligence and amending regulations (ec) no 300\/2008, (eu) no 167\/2013, (eu) no 168\/2013, (eu) 2018\/858, (eu) 2018\/1139 and (eu) 2019\/2144 and directives 2014\/90\/eu, (eu) 2016\/797 and (eu) 2020\/1828 (artificial intelligence act)"},{"key":"2063_CR48","unstructured":"Phelps S, Ranson R (2023) Of models and tin men\u2013a behavioural economics study of principal-agent problems in AI alignment using large-language models. arXiv preprint. arXiv:2307.11137"},{"key":"2063_CR49","unstructured":"Phute M, Helbling A, Hull MD, Peng S, Szyller S, Cornelius C, Chau DH (2023) LLM self defense: by self examination, LLMs know they are being tricked. In: The second tiny papers track at ICLR, p 2024"},{"key":"2063_CR50","unstructured":"Plato t B\u00a0J (2021) The Republic"},{"key":"2063_CR51","unstructured":"Rafailov R, Sharma A, Mitchell E, Manning C\u00a0D, Ermon S, Finn C (2024) Direct preference optimization: your language model is secretly a reward model. Adv Neural Inf Process Syst 36"},{"key":"2063_CR52","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-45734-1","volume-title":"Manhattan project: the story of the century","author":"BC Reed","year":"2020","unstructured":"Reed BC (2020) Manhattan project: the story of the century. Springer Nature"},{"key":"2063_CR53","unstructured":"Renatus F\u00a0V (2007) Epitoma rei militaris. IntraText Digital Library, ii (lat0189) edition"},{"key":"2063_CR54","volume-title":"Artificial intelligence: a modern approach","author":"SJ Russell","year":"2016","unstructured":"Russell SJ, Norvig P (2016) Artificial intelligence: a modern approach. Pearson"},{"key":"2063_CR55","unstructured":"Scheurer J, Balesni M, Hobbhahn M (2024) Large language models can strategically deceive their users when put under pressure. In: ICLR 2024 Workshop on Large Language Model (LLM) Agents"},{"issue":"1","key":"2063_CR56","doi-asserted-by":"publisher","first-page":"60","DOI":"10.1080\/17579961.2023.2184135","volume":"15","author":"J Schuett","year":"2023","unstructured":"Schuett J (2023) Defining the scope of AI regulations. Law Innov Technol 15(1):60\u201382","journal-title":"Law Innov Technol"},{"key":"2063_CR57","doi-asserted-by":"crossref","unstructured":"Shaikh O, Zhang H, Held W, Bernstein M, Yang D (2023) On second thought, let\u2019s not think step by step! bias and toxicity in zero-shot reasoning. In: Rogers A, Boyd-Graber J and Okazaki N (eds) Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics, Toronto, pp 4454\u20134470","DOI":"10.18653\/v1\/2023.acl-long.244"},{"issue":"1","key":"2063_CR58","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1080\/17579961.2021.1898300","volume":"13","author":"NA Smuha","year":"2021","unstructured":"Smuha NA (2021) From a \u2018race to AI\u2019 to a \u2018race to AI regulation\u2019: regulatory competition for artificial intelligence. Law Innov Technol 13(1):57\u201384","journal-title":"Law Innov Technol"},{"key":"2063_CR59","unstructured":"Utah General Assembly (2024) Artificial intelligence amendments"},{"key":"2063_CR60","unstructured":"Wei A, Haghtalab N, Steinhardt J (2024) Jailbroken: How does llm safety training fail? Adv Neural Inf Process Syst 36"},{"key":"2063_CR61","doi-asserted-by":"crossref","unstructured":"Wright L, Muenster R\u00a0M, Vecchione B, Qu T, Cai P\u00a0S, Smith A, Investigators C S, Metcalf J, Matias J\u00a0N (2024) Null compliance: Nyc local law 144 and the challenges of algorithm accountability. In: Proceedings of the 2024 ACM Conference on Fairness, Accountability, and Transparency, FAccT \u201924. Association for Computing Machinery, New York, pp 1701\u20131713","DOI":"10.1145\/3630106.3658998"},{"issue":"3","key":"2063_CR62","doi-asserted-by":"publisher","first-page":"244","DOI":"10.1093\/ppmgov\/gvab006","volume":"4","author":"MM Young","year":"2019","unstructured":"Young MM, Himmelreich J, Bullock JB, Kim K-C (2019) Artificial intelligence and administrative evil. Perspect Public Manage Governance 4(3):244\u2013258","journal-title":"Perspect Public Manage Governance"},{"issue":"2","key":"2063_CR63","doi-asserted-by":"publisher","first-page":"457","DOI":"10.1086\/684365","volume":"78","author":"AV Zakharov","year":"2016","unstructured":"Zakharov AV (2016) The loyalty-competence trade-off in dictatorships and outside options for subordinates. J Politics 78(2):457\u2013466","journal-title":"J Politics"},{"key":"2063_CR64","doi-asserted-by":"crossref","unstructured":"Zeng Y, Lin H, Zhang J, Yang D, Jia R, Shi W (2024) How johnny can persuade llms to jailbreak them: rethinking persuasion to challenge AI safety by humanizing llms. CoRR. arxiv:abs\/2401.06373","DOI":"10.18653\/v1\/2024.acl-long.773"}],"container-title":["AI &amp; SOCIETY"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00146-024-02063-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00146-024-02063-2\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00146-024-02063-2.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,5,15]],"date-time":"2025-05-15T02:38:19Z","timestamp":1747276699000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00146-024-02063-2"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,9,11]]},"references-count":64,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,4]]}},"alternative-id":["2063"],"URL":"https:\/\/doi.org\/10.1007\/s00146-024-02063-2","relation":{},"ISSN":["0951-5666","1435-5655"],"issn-type":[{"value":"0951-5666","type":"print"},{"value":"1435-5655","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,9,11]]},"assertion":[{"value":"10 June 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"30 August 2024","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"11 September 2024","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}