{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,9,11]],"date-time":"2025-09-11T20:28:42Z","timestamp":1757622522830,"version":"3.44.0"},"publisher-location":"Cham","reference-count":83,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783032007995"},{"type":"electronic","value":"9783032008008"}],"license":[{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,8,7]],"date-time":"2025-08-07T00:00:00Z","timestamp":1754524800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026]]},"DOI":"10.1007\/978-3-032-00800-8_33","type":"book-chapter","created":{"date-parts":[[2025,8,6]],"date-time":"2025-08-06T06:55:52Z","timestamp":1754463352000},"page":"370-380","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Roadmap on\u00a0Incentive Compatibility for\u00a0AI Alignment and\u00a0Governance in\u00a0Sociotechnical Systems"],"prefix":"10.1007","author":[{"given":"Zhaowei","family":"Zhang","sequence":"first","affiliation":[]},{"given":"Fengshuo","family":"Bai","sequence":"additional","affiliation":[]},{"given":"Mingzhi","family":"Wang","sequence":"additional","affiliation":[]},{"given":"Haoyang","family":"Ye","sequence":"additional","affiliation":[]},{"given":"Chengdong","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Yaodong","family":"Yang","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,8,7]]},"reference":[{"issue":"10","key":"33_CR1","doi-asserted-by":"publisher","first-page":"4612","DOI":"10.1287\/mnsc.2019.3420","volume":"66","author":"S Alizamir","year":"2020","unstructured":"Alizamir, S., de V\u00e9ricourt, F., Wang, S.: Warning against recurring risks: an information design approach. Manage. Sci. 66(10), 4612\u20134629 (2020)","journal-title":"Manage. Sci."},{"issue":"1","key":"33_CR2","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1093\/jleo\/ewp036","volume":"28","author":"R Avraham","year":"2012","unstructured":"Avraham, R., Liu, Z.: Private information and the option to not sue: a reevaluation of contract remedies. J Law Econ Organ 28(1), 77\u2013102 (2012)","journal-title":"J Law Econ Organ"},{"key":"33_CR3","unstructured":"Bai, F., et al.: Efficient model-agnostic alignment via bayesian persuasion. arXiv preprint arXiv:2405.18718 (2024)"},{"key":"33_CR4","unstructured":"Bai, Y., et\u00a0al.: Training a helpful and harmless assistant with reinforcement learning from human feedback. arXiv preprint arXiv:2204.05862 (2022)"},{"issue":"5","key":"33_CR5","doi-asserted-by":"publisher","first-page":"586","DOI":"10.1257\/aer.p20161046","volume":"106","author":"D Bergemann","year":"2016","unstructured":"Bergemann, D., Morris, S.: Information design, bayesian persuasion, and bayes correlated equilibrium. Am. Econ. Rev. 106(5), 586\u2013591 (2016)","journal-title":"Am. Econ. Rev."},{"key":"33_CR6","unstructured":"Bolton, P., Dewatripont, M.: Contract Theory. MIT Press (2004)"},{"key":"33_CR7","unstructured":"Bubeck, S., et\u00a0al.: Sparks of artificial general intelligence: early experiments with gpt-4. arXiv preprint arXiv:2303.12712 (2023)"},{"key":"33_CR8","unstructured":"Burns, C., et\u00a0al.: Weak-to-strong generalization: eliciting strong capabilities with weak supervision. arXiv preprint arXiv:2312.09390 (2023)"},{"key":"33_CR9","first-page":"16188","volume":"33","author":"M Castiglioni","year":"2020","unstructured":"Castiglioni, M., Celli, A., Marchesi, A., Gatti, N.: Online bayesian persuasion. Adv. Neural. Inf. Process. Syst. 33, 16188\u201316198 (2020)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"33_CR10","first-page":"505","volume":"24","author":"C Cath","year":"2018","unstructured":"Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., Floridi, L.: Artificial intelligence and the \u2018good society\u2019: the us, eu, and uk approach. Sci. Eng. Ethics 24, 505\u2013528 (2018)","journal-title":"Sci. Eng. Ethics"},{"issue":"628","key":"33_CR11","doi-asserted-by":"publisher","first-page":"976","DOI":"10.1093\/ej\/ueaa002","volume":"130","author":"Y Chen","year":"2020","unstructured":"Chen, Y., Zhang, J.: Signalling by bayesian persuasion and pricing strategy. Econ. J. 130(628), 976\u20131007 (2020)","journal-title":"Econ. J."},{"key":"33_CR12","unstructured":"Christiano, P., Shlegeris, B., Amodei, D.: Supervising strong learners by amplifying weak experts. arXiv preprint arXiv:1810.08575 (2018)"},{"key":"33_CR13","unstructured":"Christiano, P.F., Leike, J., Brown, T., Martic, M., Legg, S., Amodei, D.: Deep reinforcement learning from human preferences. In: Advances in Neural Information Processing Systems, vol. 30 (2017)"},{"key":"33_CR14","doi-asserted-by":"publisher","first-page":"17","DOI":"10.1007\/BF01726210","volume":"11","author":"EH Clarke","year":"1971","unstructured":"Clarke, E.H.: Multipart pricing of public goods. Public Choice 11, 17\u201333 (1971)","journal-title":"Public Choice"},{"issue":"7857","key":"33_CR15","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1038\/d41586-021-01170-0","volume":"593","author":"A Dafoe","year":"2021","unstructured":"Dafoe, A., Bachrach, Y., Hadfield, G., Horvitz, E., Larson, K., Graepel, T.: Cooperative ai: machines must learn to find common ground. Nature 593(7857), 33\u201336 (2021)","journal-title":"Nature"},{"key":"33_CR16","unstructured":"Dafoe, A., et al.: Open problems in cooperative AI. arXiv preprint arXiv:2012.08630 (2020)"},{"key":"33_CR17","doi-asserted-by":"publisher","first-page":"185","DOI":"10.2307\/2297045","volume":"46","author":"P Dasgupta","year":"1979","unstructured":"Dasgupta, P., Hammond, P.J., Maskin, E.: The implementation of social choice rules: Some general results on incentive compatibility. Rev. Econ. Stud. 46, 185\u2013216 (1979)","journal-title":"Rev. Econ. Stud."},{"key":"33_CR18","doi-asserted-by":"crossref","unstructured":"Dasgupta, P., Maskin, E.: Strategy-proofness, independence of irrelevant alternatives, and majority rule. Insights, Am. Econ. Rev. (2020)","DOI":"10.1257\/aeri.20200178"},{"issue":"10","key":"33_CR19","doi-asserted-by":"publisher","first-page":"6350","DOI":"10.1287\/mnsc.2021.4016","volume":"67","author":"F De V\u00e9ricourt","year":"2021","unstructured":"De V\u00e9ricourt, F., Gurkan, H., Wang, S.: Informing the public about a pandemic. Manage. Sci. 67(10), 6350\u20136357 (2021)","journal-title":"Manage. Sci."},{"issue":"2","key":"33_CR20","doi-asserted-by":"publisher","first-page":"62","DOI":"10.1109\/TTS.2021.3074097","volume":"2","author":"S Dean","year":"2021","unstructured":"Dean, S., Gilbert, T.K., Lambert, N., Zick, T.: Axes for sociotechnical inquiry in AI research. IEEE Trans. Technol. Soc. 2(2), 62\u201370 (2021)","journal-title":"IEEE Trans. Technol. Soc."},{"key":"33_CR21","unstructured":"Di\u00a0Langosco, L.L., Koch, J., Sharkey, L.D., Pfau, J., Krueger, D.: Goal misgeneralization in deep reinforcement learning. In: International Conference on Machine Learning, pp. 12004\u201312019. PMLR (2022)"},{"key":"33_CR22","unstructured":"Dong, H., Zhang, J., Wang, T., Zhang, C.: Symmetry-aware robot design with structured subgroups. In: International Conference on Machine Learning, pp. 8334\u20138355. PMLR (2023)"},{"issue":"2","key":"33_CR23","doi-asserted-by":"publisher","first-page":"828","DOI":"10.1287\/mnsc.2020.3580","volume":"67","author":"K Drakopoulos","year":"2021","unstructured":"Drakopoulos, K., Jain, S., Randhawa, R.: Persuading customers to buy early: the value of personalized information provisioning. Manage. Sci. 67(2), 828\u2013853 (2021)","journal-title":"Manage. Sci."},{"key":"33_CR24","first-page":"101994","volume":"57","author":"YK Dwivedi","year":"2021","unstructured":"Dwivedi, Y.K., et al.: Artificial intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int. J. Inf. Manage. 57, 101994 (2021)","journal-title":"Int. J. Inf. Manage."},{"key":"33_CR25","unstructured":"Fu, Z., Zhao, T.Z., Finn, C.: Mobile aloha: learning bimanual mobile manipulation with low-cost whole-body teleoperation. arXiv preprint arXiv:2401.02117 (2024)"},{"issue":"1","key":"33_CR26","doi-asserted-by":"publisher","first-page":"9","DOI":"10.1080\/00029890.1962.11989827","volume":"69","author":"D Gale","year":"1962","unstructured":"Gale, D., Shapley, L.S.: College admissions and the stability of marriage. Am. Math. Mon. 69(1), 9\u201315 (1962)","journal-title":"Am. Math. Mon."},{"key":"33_CR27","doi-asserted-by":"crossref","unstructured":"Gan, J., Majumdar, R., Radanovic, G., Singla, A.: Bayesian persuasion in sequential decision-making. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol.\u00a036, pp. 5025\u20135033 (2022)","DOI":"10.1609\/aaai.v36i5.20434"},{"issue":"4","key":"33_CR28","doi-asserted-by":"publisher","first-page":"587","DOI":"10.2307\/1914083","volume":"41","author":"A Gibbard","year":"1973","unstructured":"Gibbard, A.: Manipulation of voting schemes: a general result. Econometrica 41(4), 587\u2013601 (1973)","journal-title":"Econometrica"},{"key":"33_CR29","doi-asserted-by":"crossref","unstructured":"Gladden, M.E.: Who will be the members of society 5.0? towards an anthropology of technologically posthumanized future societies. Soc. Sci. 8(5), 148 (2019)","DOI":"10.3390\/socsci8050148"},{"key":"33_CR30","unstructured":"Goodfellow, I.J., Shlens, J., Szegedy, C.: Explaining and harnessing adversarial examples. arXiv preprint arXiv:1412.6572 (2014)"},{"key":"33_CR31","unstructured":"Groves, T., Ledyard, J.: Incentive compatibility since 1972. In: Information, Incentives, and Economic Mechanisms: Essays in Honor of Leonid Hurwicz, pp. 48\u2013111 (1987)"},{"key":"33_CR32","doi-asserted-by":"crossref","unstructured":"Guesnerie, R.: Hidden actions, moral hazard and contract theory. In: Allocation, information and markets, pp. 120\u2013131. Springer (1989)","DOI":"10.1007\/978-1-349-20215-7_13"},{"key":"33_CR33","unstructured":"Heidari, H., Ferrari, C., Gummadi, K., Krause, A.: Fairness behind a veil of ignorance: a welfare analysis for automated decision making. In: Advances in Neural Information Processing Systems, vol. 31 (2018)"},{"key":"33_CR34","unstructured":"Hossain, S., Wang, T., Lin, T., Chen, Y., Parkes, D.C., Xu, H.: Multi-sender persuasion: a computational perspective. arXiv preprint arXiv:2402.04971 (2024)"},{"issue":"48","key":"33_CR35","doi-asserted-by":"publisher","first-page":"23989","DOI":"10.1073\/pnas.1910125116","volume":"116","author":"K Huang","year":"2019","unstructured":"Huang, K., Greene, J.D., Bazerman, M.: Veil-of-ignorance reasoning favors the greater good. Proc. Natl. Acad. Sci. 116(48), 23989\u201323995 (2019)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"33_CR36","unstructured":"Hurwicz, L.: On informationally decentralized systems. Decis. Organ. volume in Honor of J. Marschak (1972)"},{"key":"33_CR37","unstructured":"Ibarz, B., Leike, J., Pohlen, T., Irving, G., Legg, S., Amodei, D.: Reward learning from human preferences and demonstrations in atari. In: Advances in Neural Information Processing Systems, vol. 31 (2018)"},{"key":"33_CR38","unstructured":"Irving, G., Christiano, P., Amodei, D.: Ai safety via debate. arXiv preprint arXiv:1805.00899 (2018)"},{"key":"33_CR39","unstructured":"Ivanov, D., D\u00fctting, P., Talgam-Cohen, I., Wang, T., Parkes, D.C.: Principal-agent reinforcement learning: orchestrating AI agents with contracts. arXiv preprint arXiv:2407.18074 (2024)"},{"key":"33_CR40","unstructured":"Ji, J., et\u00a0al.: Ai alignment: a comprehensive survey. arXiv preprint arXiv:2310.19852 (2023)"},{"key":"33_CR41","doi-asserted-by":"publisher","first-page":"249","DOI":"10.1146\/annurev-economics-080218-025739","volume":"11","author":"E Kamenica","year":"2019","unstructured":"Kamenica, E.: Bayesian persuasion and information design. Ann. Rev. Econ. 11, 249\u2013272 (2019)","journal-title":"Ann. Rev. Econ."},{"issue":"6","key":"33_CR42","doi-asserted-by":"publisher","first-page":"2590","DOI":"10.1257\/aer.101.6.2590","volume":"101","author":"E Kamenica","year":"2011","unstructured":"Kamenica, E., Gentzkow, M.: Bayesian persuasion. Am. Econ. Rev. 101(6), 2590\u20132615 (2011)","journal-title":"Am. Econ. Rev."},{"key":"33_CR43","first-page":"25655","volume":"35","author":"Y Kang","year":"2022","unstructured":"Kang, Y., Wang, T., Yang, Q., Wu, X., Zhang, C.: Non-linear coordination graphs. Adv. Neural. Inf. Process. Syst. 35, 25655\u201325666 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"key":"33_CR44","unstructured":"Krueger, D., et al.: Out-of-distribution generalization via risk extrapolation (rex). In: International Conference on Machine Learning, pp. 5815\u20135826. PMLR (2021)"},{"key":"33_CR45","doi-asserted-by":"crossref","unstructured":"Lazar, S., Nelson, A.: Ai safety on whose terms? (2023)","DOI":"10.1126\/science.adi8982"},{"issue":"10","key":"33_CR46","doi-asserted-by":"publisher","first-page":"9575","DOI":"10.1109\/JIOT.2020.2985694","volume":"7","author":"W Lim","year":"2020","unstructured":"Lim, W., et al.: Hierarchical incentive mechanism design for federated machine learning in mobile networks. IEEE Internet Things J. 7(10), 9575\u20139588 (2020)","journal-title":"IEEE Internet Things J."},{"key":"33_CR47","unstructured":"Lubana, E.S., Bigelow, E.J., Dick, R.P., Krueger, D., Tanaka, H.: Mechanistic mode connectivity. In: International Conference on Machine Learning, pp. 22965\u201323004. PMLR (2023)"},{"key":"33_CR48","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.futures.2017.03.006","volume":"90","author":"S Makridakis","year":"2017","unstructured":"Makridakis, S.: The forthcoming artificial intelligence (ai) revolution: its impact on society and firms. Futures 90, 46\u201360 (2017)","journal-title":"Futures"},{"issue":"10","key":"33_CR49","doi-asserted-by":"publisher","first-page":"1787","DOI":"10.1038\/s41562-023-01686-7","volume":"7","author":"KR McKee","year":"2023","unstructured":"McKee, K.R., et al.: Scaffolding cooperation in human groups with deep reinforcement learning. Nat. Hum. Behav. 7(10), 1787\u20131796 (2023)","journal-title":"Nat. Hum. Behav."},{"key":"33_CR50","doi-asserted-by":"crossref","unstructured":"Michaelis, J.E., Mutlu, B.: Reading socially: transforming the in-home reading experience with a learning-companion robot. Science Robotics 3(21), eaat5999 (2018)","DOI":"10.1126\/scirobotics.aat5999"},{"key":"33_CR51","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1287\/moor.6.1.58","volume":"6","author":"RB Myerson","year":"1981","unstructured":"Myerson, R.B.: Optimal auction design. Math. Oper. Res. 6, 58\u201373 (1981)","journal-title":"Math. Oper. Res."},{"key":"33_CR52","unstructured":"Ngo, R., Chan, L., Mindermann, S.: The alignment problem from a deep learning perspective. arXiv preprint arXiv:2209.00626 (2022)"},{"key":"33_CR53","doi-asserted-by":"publisher","first-page":"105212","DOI":"10.1016\/j.jet.2021.105212","volume":"193","author":"A Nguyen","year":"2021","unstructured":"Nguyen, A., Tan, T.Y.: Bayesian persuasion with costly messages. J. Econ. Theor. 193, 105212 (2021)","journal-title":"J. Econ. Theor."},{"key":"33_CR54","doi-asserted-by":"crossref","unstructured":"Nisan, N., Ronen, A.: Algorithmic mechanism design. In: Proceedings of the Thirty-First Annual ACM Symposium on Theory of Computing, pp. 129\u2013140 (1999)","DOI":"10.1145\/301250.301287"},{"key":"33_CR55","unstructured":"Orzan, N.: Cooperation under uncertain incentive alignment: a multi-agent reinforcement learning perspective (2025)"},{"key":"33_CR56","first-page":"27730","volume":"35","author":"L Ouyang","year":"2022","unstructured":"Ouyang, L., et al.: Training language models to follow instructions with human feedback. Adv. Neural. Inf. Process. Syst. 35, 27730\u201327744 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"1","key":"33_CR57","doi-asserted-by":"publisher","first-page":"305","DOI":"10.1287\/msom.2020.0945","volume":"24","author":"V Pavlov","year":"2022","unstructured":"Pavlov, V., Katok, E., Zhang, W.: Optimal contract under asymmetric information about fairness. Manuf. Serv. Oper. Manag. 24(1), 305\u2013314 (2022)","journal-title":"Manuf. Serv. Oper. Manag."},{"key":"33_CR58","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/s00146-020-01005-y","volume":"36","author":"MM Peeters","year":"2021","unstructured":"Peeters, M.M., et al.: Hybrid collective intelligence in a human-ai society. AI Soc. 36, 217\u2013238 (2021)","journal-title":"AI Soc."},{"key":"33_CR59","doi-asserted-by":"crossref","unstructured":"Poursaeed, O., Jiang, T., Yang, H., Belongie, S., Lim, S.N.: Robustness and generalization via generative adversarial training. In: Proceedings of the IEEE\/CVF International Conference on Computer Vision, pp. 15711\u201315720 (2021)","DOI":"10.1109\/ICCV48922.2021.01542"},{"issue":"8","key":"33_CR60","doi-asserted-by":"publisher","first-page":"182101","DOI":"10.1007\/s11432-023-3862-1","volume":"67","author":"R Qin","year":"2024","unstructured":"Qin, R., et al.: Multi-agent policy transfer via task relationship modeling. Sci. China Inf. Sci. 67(8), 182101 (2024)","journal-title":"Sci. China Inf. Sci."},{"key":"33_CR61","doi-asserted-by":"crossref","unstructured":"Rawls, J.: Atheory of Justice. Cambridge (Mass.) (1971)","DOI":"10.4159\/9780674042605"},{"issue":"7","key":"33_CR62","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/1785414.1785439","volume":"53","author":"T Roughgarden","year":"2010","unstructured":"Roughgarden, T.: Algorithmic game theory. Commun. ACM 53(7), 78\u201386 (2010)","journal-title":"Commun. ACM"},{"issue":"2","key":"33_CR63","doi-asserted-by":"publisher","first-page":"187","DOI":"10.1016\/0022-0531(75)90050-2","volume":"10","author":"MA Satterthwaite","year":"1975","unstructured":"Satterthwaite, M.A.: Strategy-proofness and arrow\u2019s conditions: existence and correspondence theorems for voting procedures and social welfare functions. J. Econ. Theor. 10(2), 187\u2013217 (1975)","journal-title":"J. Econ. Theor."},{"key":"33_CR64","doi-asserted-by":"crossref","unstructured":"Selbst, A.D., Boyd, D., Friedler, S.A., Venkatasubramanian, S., Vertesi, J.: Fairness and abstraction in sociotechnical systems. In: Proceedings of the Conference on Fairness, Accountability, and Transparency, pp. 59\u201368 (2019)","DOI":"10.1145\/3287560.3287598"},{"key":"33_CR65","doi-asserted-by":"crossref","unstructured":"Sinha, A., Anastasopoulos, A.: Mechanism design for fair allocation. In: 2015 53rd Annual Allerton Conference on Communication, Control, and Computing (Allerton), pp. 467\u2013473. IEEE (2015)","DOI":"10.1109\/ALLERTON.2015.7447041"},{"key":"33_CR66","first-page":"101","volume":"16","author":"H Steinhaus","year":"1948","unstructured":"Steinhaus, H.: The problem of fair division. Econometrica 16, 101\u2013104 (1948)","journal-title":"Econometrica"},{"key":"33_CR67","doi-asserted-by":"crossref","unstructured":"Tessler, M.H., et\u00a0al.: Ai can help humans find common ground in democratic deliberation. Science 386(6719), eadq2852 (2024)","DOI":"10.1126\/science.adq2852"},{"key":"33_CR68","unstructured":"Vapnik, V.: Principles of risk minimization for learning theory. In: Advances in Neural Information Processing Systems, vol. 4 (1991)"},{"issue":"1","key":"33_CR69","doi-asserted-by":"publisher","first-page":"8","DOI":"10.1111\/j.1540-6261.1961.tb02789.x","volume":"16","author":"W Vickrey","year":"1961","unstructured":"Vickrey, W.: Counterspeculation, auctions, and competitive sealed tenders. J. Financ. 16(1), 8\u201337 (1961)","journal-title":"J. Financ."},{"key":"33_CR70","doi-asserted-by":"publisher","first-page":"120482","DOI":"10.1016\/j.techfore.2020.120482","volume":"164","author":"SF Wamba","year":"2021","unstructured":"Wamba, S.F., Bawack, R.E., Guthrie, C., Queiroz, M.M., Carillo, K.: Are we preparing for a good ai society? a bibliometric review and research agenda. Technol. Forecast. Soc. Chang. 164, 120482 (2021)","journal-title":"Technol. Forecast. Soc. Chang."},{"key":"33_CR71","doi-asserted-by":"crossref","unstructured":"Wang, T., Jiang, Y., Parkes, D.C.: Gemnet: menu-based, strategy-proof multi-bidder auctions through deep learning. arXiv preprint arXiv:2406.07428 (2024)","DOI":"10.1145\/3670865.3673454"},{"key":"33_CR72","unstructured":"Wang, X., et al.: Self-consistency improves chain of thought reasoning in language models. arXiv preprint arXiv:2203.11171 (2022)"},{"key":"33_CR73","first-page":"24824","volume":"35","author":"J Wei","year":"2022","unstructured":"Wei, J., et al.: Chain-of-thought prompting elicits reasoning in large language models. Adv. Neural. Inf. Process. Syst. 35, 24824\u201324837 (2022)","journal-title":"Adv. Neural. Inf. Process. Syst."},{"issue":"18","key":"33_CR74","doi-asserted-by":"publisher","first-page":"e2213709120","DOI":"10.1073\/pnas.2213709120","volume":"120","author":"L Weidinger","year":"2023","unstructured":"Weidinger, L., et al.: Using the veil of ignorance to align ai systems with principles of justice. Proc. Natl. Acad. Sci. 120(18), e2213709120 (2023)","journal-title":"Proc. Natl. Acad. Sci."},{"key":"33_CR75","unstructured":"Weidinger, L., et\u00a0al.: Sociotechnical safety evaluation of generative ai systems. arXiv preprint arXiv:2310.11986 (2023)"},{"issue":"136","key":"33_CR76","first-page":"1","volume":"18","author":"C Wirth","year":"2017","unstructured":"Wirth, C., Akrour, R., Neumann, G., F\u00fcrnkranz, J., et al.: A survey of preference-based reinforcement learning methods. J. Mach. Learn. Res. 18(136), 1\u201346 (2017)","journal-title":"J. Mach. Learn. Res."},{"key":"33_CR77","doi-asserted-by":"crossref","unstructured":"Yan, W., Li, L., Li, X., Gao, A., Zhang, H., Chen, W., Hanz, Z.: A contract-based incentive mechanism in rf-powered backscatter cognitive radio networks. In: 2018 10th International Conference on Wireless Communications and Signal Processing (WCSP), pp.\u00a01\u20136. IEEE (2018)","DOI":"10.1109\/WCSP.2018.8555705"},{"key":"33_CR78","unstructured":"Zhang, T., Zhu, Q.: Forward-looking dynamic persuasion for pipeline stochastic bayesian game: a fixed-point alignment principle. arXiv preprint arXiv:2203.09725 (2022)"},{"key":"33_CR79","unstructured":"Zhang, Z., et al.: Amulet: realignment during test time for personalized preference adaptation of LLMs. In: The Thirteenth International Conference on Learning Representations (2025), https:\/\/openreview.net\/forum?id=f9w89OY2cp"},{"key":"33_CR80","unstructured":"Zhang, Z., et al.: Eurocon: benchmarking parliament deliberation for political consensus finding. arXiv preprint arXiv:2505.19558 (2025)"},{"key":"33_CR81","unstructured":"Zhao, W.X., et\u00a0al.: A survey of large language models. arXiv preprint arXiv:2303.18223 (2023)"},{"key":"33_CR82","unstructured":"Zheng, S., et al.: The ai economist: improving equality and productivity with ai-driven tax policies. arXiv preprint arXiv:2004.13332 (2020)"},{"key":"33_CR83","doi-asserted-by":"crossref","unstructured":"Zheng, S., Trott, A., Srinivasa, S., Parkes, D.C., Socher, R.: The ai economist: taxation policy design via two-level deep multiagent reinforcement learning. Sci. Adv. 8(18), eabk2607 (2022)","DOI":"10.1126\/sciadv.abk2607"}],"container-title":["Lecture Notes in Computer Science","Artificial General Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-032-00800-8_33","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,8]],"date-time":"2025-09-08T20:57:13Z","timestamp":1757365033000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-032-00800-8_33"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,8,7]]},"ISBN":["9783032007995","9783032008008"],"references-count":83,"URL":"https:\/\/doi.org\/10.1007\/978-3-032-00800-8_33","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2025,8,7]]},"assertion":[{"value":"7 August 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"AGI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Artificial General Intelligence","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Reykjavic","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Iceland","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2025","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 August 2025","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"13 August 2025","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"agi2025","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/agi-conf.org\/2025\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}