{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,4,22]],"date-time":"2025-04-22T07:57:18Z","timestamp":1745308638521,"version":"3.40.3"},"publisher-location":"Cham","reference-count":59,"publisher":"Springer Nature Switzerland","isbn-type":[{"type":"print","value":"9783031601248"},{"type":"electronic","value":"9783031601255"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"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":[[2024]]},"DOI":"10.1007\/978-3-031-60125-5_20","type":"book-chapter","created":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T01:02:20Z","timestamp":1717203740000},"page":"296-308","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Operational Collective Intelligence of\u00a0Humans and\u00a0Machines"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3479-2037","authenticated-orcid":false,"given":"Nikolos","family":"Gurney","sequence":"first","affiliation":[]},{"given":"Fred","family":"Morstatter","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2452-4733","authenticated-orcid":false,"given":"David V.","family":"Pynadath","sequence":"additional","affiliation":[]},{"given":"Adam","family":"Russell","sequence":"additional","affiliation":[]},{"given":"Gleb","family":"Satyukov","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2024,6,1]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Atanasov, P., et al.: Distilling the wisdom of crowds: prediction markets vs. prediction polls. Manag. Sci. 63(3), 691\u2013706 (2017)","key":"20_CR1","DOI":"10.1287\/mnsc.2015.2374"},{"unstructured":"Benjamin, D.M., et\u00a0al.: Hybrid forecasting of geopolitical events. AI Mag. (2023)","key":"20_CR2"},{"unstructured":"Bollier, D., Firestone, C.M., et al.: The promise and peril of big data. Aspen Institute, Communications and Society Program Washington, DC (2010)","key":"20_CR3"},{"issue":"6370","key":"20_CR4","doi-asserted-by":"publisher","first-page":"1530","DOI":"10.1126\/science.aap8062","volume":"358","author":"E Brynjolfsson","year":"2017","unstructured":"Brynjolfsson, E., Mitchell, T.: What can machine learning do? Workforce implications. Science 358(6370), 1530\u20131534 (2017)","journal-title":"Science"},{"unstructured":"Budach, L., et al.: The effects of data quality on machine learning performance. arXiv preprint arXiv:2207.14529 (2022)","key":"20_CR5"},{"issue":"2","key":"20_CR6","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1287\/mnsc.2014.1909","volume":"61","author":"DV Budescu","year":"2015","unstructured":"Budescu, D.V., Chen, E.: Identifying expertise to extract the wisdom of crowds. Manage. Sci. 61(2), 267\u2013280 (2015)","journal-title":"Manage. Sci."},{"doi-asserted-by":"crossref","unstructured":"Budescu, D.V., Fiedler, K., et\u00a0al.: Confidence in aggregation of opinions from multiple sources. In: Information Sampling and Adaptive Cognition, pp. 327\u2013352 (2006)","key":"20_CR7","DOI":"10.1017\/CBO9780511614576.014"},{"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":"20_CR8"},{"issue":"5","key":"20_CR9","doi-asserted-by":"publisher","first-page":"1847","DOI":"10.1287\/mnsc.2019.3294","volume":"66","author":"Z Da","year":"2020","unstructured":"Da, Z., Huang, X.: Harnessing the wisdom of crowds. Manage. Sci. 66(5), 1847\u20131867 (2020)","journal-title":"Manage. Sci."},{"issue":"4899","key":"20_CR10","doi-asserted-by":"publisher","first-page":"1668","DOI":"10.1126\/science.2648573","volume":"243","author":"RM Dawes","year":"1989","unstructured":"Dawes, R.M., Faust, D., Meehl, P.E.: Clinical versus actuarial judgment. Science 243(4899), 1668\u20131674 (1989)","journal-title":"Science"},{"key":"20_CR11","doi-asserted-by":"publisher","first-page":"637","DOI":"10.1007\/s12599-019-00595-2","volume":"61","author":"D Dellermann","year":"2019","unstructured":"Dellermann, D., Ebel, P., S\u00f6llner, M., Leimeister, J.M.: Hybrid intelligence. Bus. Inf. Syst. Eng. 61, 637\u2013643 (2019)","journal-title":"Bus. Inf. Syst. Eng."},{"issue":"1","key":"20_CR12","doi-asserted-by":"publisher","first-page":"114","DOI":"10.1037\/xge0000033","volume":"144","author":"BJ Dietvorst","year":"2015","unstructured":"Dietvorst, B.J., Simmons, J.P., Massey, C.: Algorithm aversion: people erroneously avoid algorithms after seeing them err. J. Exp. Psychol. Gen. 144(1), 114 (2015)","journal-title":"J. Exp. Psychol. Gen."},{"key":"20_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.elerap.2022.101216","volume":"56","author":"L Dong","year":"2022","unstructured":"Dong, L., Zheng, H., Li, L., Hao, L.: Human-machine hybrid prediction market: a promising sales forecasting solution for e-commerce enterprises. Electron. Commer. Res. Appl. 56, 101216 (2022)","journal-title":"Electron. Commer. Res. Appl."},{"issue":"9","key":"20_CR14","doi-asserted-by":"publisher","first-page":"1397","DOI":"10.3390\/math10091397","volume":"10","author":"JJ Gal\u00e1n","year":"2022","unstructured":"Gal\u00e1n, J.J., Carrasco, R.A., LaTorre, A.: Military applications of machine learning: a bibliometric perspective. Mathematics 10(9), 1397 (2022)","journal-title":"Mathematics"},{"issue":"1949","key":"20_CR15","doi-asserted-by":"publisher","first-page":"450","DOI":"10.1038\/075450a0","volume":"75","author":"F Galton","year":"1907","unstructured":"Galton, F.: Vox populi. Nature 75(1949), 450\u2013451 (1907)","journal-title":"Nature"},{"unstructured":"Garcez, A.D., et al.: Neural-symbolic learning and reasoning: a survey and interpretation. In: Neuro-Symbolic Artificial Intelligence: The State of the Art, vol. 342, no. 1, p. 327 (2022)","key":"20_CR16"},{"unstructured":"Goldstein, S.: December 2015. https:\/\/www.iarpa.gov\/research-programs\/hfc","key":"20_CR17"},{"doi-asserted-by":"publisher","unstructured":"Gurney, N., Pynadath, D.V., Wang, N.: Measuring and predicting human trust in recommendations from an AI teammate. In: Degen, H., Ntoa, S. (eds.) HCII 2022. LNCS, vol. 13336, pp. 22\u201334. Springer, Cham (2022). https:\/\/doi.org\/10.1007\/978-3-031-05643-7_2","key":"20_CR18","DOI":"10.1007\/978-3-031-05643-7_2"},{"doi-asserted-by":"publisher","unstructured":"Gurney, N., Pynadath, D.V., Wang, N.: Comparing psychometric and behavioral predictors of compliance during human-AI interactions. In: Meschtscherjakov, A., Midden, C., Ham, J. (eds) PERSUASIVE 2023, vol. 13832, pp. 175\u2013197. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-30933-5_12","key":"20_CR19","DOI":"10.1007\/978-3-031-30933-5_12"},{"key":"20_CR20","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.eswa.2016.12.035","volume":"73","author":"G Haixiang","year":"2017","unstructured":"Haixiang, G., Yijing, L., Shang, J., Mingyun, G., Yuanyue, H., Bing, G.: Learning from class-imbalanced data: review of methods and applications. Expert Syst. Appl. 73, 220\u2013239 (2017)","journal-title":"Expert Syst. Appl."},{"key":"20_CR21","doi-asserted-by":"publisher","first-page":"5","DOI":"10.1007\/s40745-015-0029-9","volume":"2","author":"H Hassani","year":"2015","unstructured":"Hassani, H., Silva, E.S.: Forecasting with big data: a review. Ann. Data Sci. 2, 5\u201319 (2015)","journal-title":"Ann. Data Sci."},{"issue":"2","key":"20_CR22","first-page":"1","volume":"9","author":"B Heinrich","year":"2018","unstructured":"Heinrich, B., Hristova, D., Klier, M., Schiller, A., Szubartowicz, M.: Requirements for data quality metrics. J. Data Inf. Qual. (JDIQ) 9(2), 1\u201332 (2018)","journal-title":"J. Data Inf. Qual. (JDIQ)"},{"doi-asserted-by":"crossref","unstructured":"Huber, D.J., et al.: MATRICS: a system for human-machine hybrid forecasting of geopolitical events. In: 2019 IEEE International Conference on Big Data (Big Data), pp. 2028\u20132032. IEEE (2019)","key":"20_CR23","DOI":"10.1109\/BigData47090.2019.9006134"},{"issue":"1","key":"20_CR24","doi-asserted-by":"publisher","first-page":"69","DOI":"10.4018\/jdsst.2009010105","volume":"1","author":"L Iandoli","year":"2009","unstructured":"Iandoli, L., Klein, M., Zollo, G.: Enabling on-line deliberation and collective decision-making through large-scale argumentation: a new approach to the design of an internet-based mass collaboration platform. Int. J. Decis. Support Syst. Technol. (IJDSST) 1(1), 69\u201392 (2009)","journal-title":"Int. J. Decis. Support Syst. Technol. (IJDSST)"},{"issue":"6245","key":"20_CR25","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1126\/science.aaa8415","volume":"349","author":"MI Jordan","year":"2015","unstructured":"Jordan, M.I., Mitchell, T.M.: Machine learning: trends, perspectives, and prospects. Science 349(6245), 255\u2013260 (2015)","journal-title":"Science"},{"unstructured":"Kamar, E., Hacker, S., Horvitz, E.: Combining human and machine intelligence in large-scale crowdsourcing. In: AAMAS, vol.\u00a012, pp. 467\u2013474 (2012)","key":"20_CR26"},{"issue":"6","key":"20_CR27","doi-asserted-by":"publisher","first-page":"345","DOI":"10.1038\/s44159-022-00054-y","volume":"1","author":"T Kameda","year":"2022","unstructured":"Kameda, T., Toyokawa, W., Tindale, R.S.: Information aggregation and collective intelligence beyond the wisdom of crowds. Nat. Rev. Psychol. 1(6), 345\u2013357 (2022)","journal-title":"Nat. Rev. Psychol."},{"unstructured":"Kott, A., Ownby, M.: Toward a research agenda in adversarial reasoning: computational approaches to anticipating the opponent\u2019s intent and actions. arXiv preprint arXiv:1512.07943 (2015)","key":"20_CR28"},{"issue":"34","key":"20_CR29","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.2221473120","volume":"120","author":"RH Kurvers","year":"2023","unstructured":"Kurvers, R.H., Nuzzolese, A.G., Russo, A., Barabucci, G., Herzog, S.M., Trianni, V.: Automating hybrid collective intelligence in open-ended medical diagnostics. Proc. Natl. Acad. Sci. 120(34), e2221473120 (2023)","journal-title":"Proc. Natl. Acad. Sci."},{"doi-asserted-by":"crossref","unstructured":"Landemore, H.: Collective wisdom: old and new. In: Collective Wisdom: Principles and Mechanisms, vol. 1, pp. 1\u201320 (2012)","key":"20_CR30","DOI":"10.1017\/CBO9780511846427.001"},{"issue":"258","key":"20_CR31","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1111\/j.1475-4932.2006.00343.x","volume":"82","author":"A Leigh","year":"2006","unstructured":"Leigh, A., Wolfers, J.: Competing approaches to forecasting elections: economic models, opinion polling and prediction markets. Econ. Rec. 82(258), 325\u2013340 (2006)","journal-title":"Econ. Rec."},{"key":"20_CR32","volume-title":"Collective Intelligence: Mankind\u2019s Emerging World in Cyberspace","author":"P Levy","year":"1997","unstructured":"Levy, P., Bononno, R.: Collective Intelligence: Mankind\u2019s Emerging World in Cyberspace. Perseus Books, USA (1997)"},{"doi-asserted-by":"crossref","unstructured":"Li, H., Liu, Q.: Cheaper and better: selecting good workers for crowdsourcing. In: Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, vol.\u00a03, pp. 20\u201321 (2015)","key":"20_CR33","DOI":"10.1609\/hcomp.v3i1.13248"},{"doi-asserted-by":"crossref","unstructured":"Li, H., Zhao, B., Fuxman, A.: The wisdom of minority: discovering and targeting the right group of workers for crowdsourcing. In: Proceedings of the 23rd International Conference on World Wide Web, pp. 165\u2013176 (2014)","key":"20_CR34","DOI":"10.1145\/2566486.2568033"},{"unstructured":"Liu, J., et al.: Towards out-of-distribution generalization: a survey. arXiv preprint arXiv:2108.13624 (2021)","key":"20_CR35"},{"key":"20_CR36","doi-asserted-by":"publisher","first-page":"90","DOI":"10.1016\/j.obhdp.2018.12.005","volume":"151","author":"JM Logg","year":"2019","unstructured":"Logg, J.M., Minson, J.A., Moore, D.A.: Algorithm appreciation: people prefer algorithmic to human judgment. Organ. Behav. Hum. Decis. Process. 151, 90\u2013103 (2019)","journal-title":"Organ. Behav. Hum. Decis. Process."},{"issue":"22","key":"20_CR37","doi-asserted-by":"publisher","first-page":"9020","DOI":"10.1073\/pnas.1008636108","volume":"108","author":"J Lorenz","year":"2011","unstructured":"Lorenz, J., Rauhut, H., Schweitzer, F., Helbing, D.: How social influence can undermine the wisdom of crowd effect. Proc. Natl. Acad. Sci. 108(22), 9020\u20139025 (2011)","journal-title":"Proc. Natl. Acad. Sci."},{"doi-asserted-by":"crossref","unstructured":"Malone, T.W., Laubacher, R., Dellarocas, C.: The collective intelligence genome. MIT Sloan Manag. Rev. (2010)","key":"20_CR38","DOI":"10.1109\/EMR.2010.5559142"},{"issue":"2","key":"20_CR39","doi-asserted-by":"publisher","first-page":"276","DOI":"10.1037\/a0036677","volume":"107","author":"AE Mannes","year":"2014","unstructured":"Mannes, A.E., Soll, J.B., Larrick, R.P.: The wisdom of select crowds. J. Pers. Soc. Psychol. 107(2), 276 (2014)","journal-title":"J. Pers. Soc. Psychol."},{"issue":"5","key":"20_CR40","doi-asserted-by":"publisher","first-page":"1106","DOI":"10.1177\/0956797614524255","volume":"25","author":"B Mellers","year":"2014","unstructured":"Mellers, B., et al.: Psychological strategies for winning a geopolitical forecasting tournament. Psychol. Sci. 25(5), 1106\u20131115 (2014)","journal-title":"Psychol. Sci."},{"doi-asserted-by":"crossref","unstructured":"Mnih, V., et\u00a0al.: Human-level control through deep reinforcement learning. Nature 518(7540), 529\u2013533 (2015)","key":"20_CR41","DOI":"10.1038\/nature14236"},{"doi-asserted-by":"crossref","unstructured":"Morstatter, F., et\u00a0al.: SAGE: a hybrid geopolitical event forecasting system. In: IJCAI, vol.\u00a01, pp. 6557\u20136559 (2019)","key":"20_CR42","DOI":"10.24963\/ijcai.2019\/955"},{"issue":"2","key":"20_CR43","doi-asserted-by":"publisher","first-page":"230","DOI":"10.1518\/001872097778543886","volume":"39","author":"R Parasuraman","year":"1997","unstructured":"Parasuraman, R., Riley, V.: Humans and automation: use, misuse, disuse, abuse. Hum. Fact. 39(2), 230\u2013253 (1997)","journal-title":"Hum. Fact."},{"doi-asserted-by":"crossref","unstructured":"Peled, A.: The politics of big data: a three-level analysis. In: European Consortium of Political Research (ECPR) General Conference, Bordeaux, France (2013)","key":"20_CR44","DOI":"10.2139\/ssrn.2315891"},{"issue":"1","key":"20_CR45","first-page":"24","volume":"35","author":"I Pencheva","year":"2020","unstructured":"Pencheva, I., Esteve, M., Mikhaylov, S.J.: Big data and AI-a transformational shift for government: so, what next for research? Public Policy Adm. 35(1), 24\u201344 (2020)","journal-title":"Public Policy Adm."},{"doi-asserted-by":"crossref","unstructured":"Pynadath, D.V., Gurney, N., Wang, N.: Explainable reinforcement learning in human-robot teams: the impact of decision-tree explanations on transparency. In: 2022 31st IEEE International Conference on Robot and Human Interactive Communication (RO-MAN), pp. 749\u2013756. IEEE (2022)","key":"20_CR46","DOI":"10.1109\/RO-MAN53752.2022.9900608"},{"unstructured":"Rafner, J., et\u00a0al.: Revisiting citizen science through the lens of hybrid intelligence. arXiv preprint arXiv:2104.14961 (2021)","key":"20_CR47"},{"unstructured":"Ratner, B.: Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data. CRC Press (2017)","key":"20_CR48"},{"doi-asserted-by":"crossref","unstructured":"Russakovsky, O., Li, L.J., Fei-Fei, L.: Best of both worlds: human-machine collaboration for object annotation. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 2121\u20132131 (2015)","key":"20_CR49","DOI":"10.1109\/CVPR.2015.7298824"},{"doi-asserted-by":"crossref","unstructured":"Shoeibi, A., et\u00a0al.: Automated detection and forecasting of covid-19 using deep learning techniques: a review. Neurocomputing, 127317 (2024)","key":"20_CR50","DOI":"10.1016\/j.neucom.2024.127317"},{"doi-asserted-by":"crossref","unstructured":"Sommer, R., Paxson, V.: Outside the closed world: on using machine learning for network intrusion detection. In: 2010 IEEE Symposium on Security and Privacy, pp. 305\u2013316. IEEE (2010)","key":"20_CR51","DOI":"10.1109\/SP.2010.25"},{"issue":"1","key":"20_CR52","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1145\/3368986","volume":"53","author":"S Suran","year":"2020","unstructured":"Suran, S., Pattanaik, V., Draheim, D.: Frameworks for collective intelligence: a systematic literature review. ACM Comput. Surv. (CSUR) 53(1), 1\u201336 (2020)","journal-title":"ACM Comput. Surv. (CSUR)"},{"unstructured":"Surowiecki, J.: The Wisdom of Crowds. Anchor (2005)","key":"20_CR53"},{"unstructured":"Svenmarck, P., Luotsinen, L., Nilsson, M., Schubert, J.: Possibilities and challenges for artificial intelligence in military applications. In: Proceedings of the NATO Big Data and Artificial Intelligence for Military Decision Making Specialists\u2019 Meeting, pp. 1\u201316 (2018)","key":"20_CR54"},{"doi-asserted-by":"crossref","unstructured":"Wang, N., Pynadath, D.V., Hill, S.G.: Trust calibration within a human-robot team: comparing automatically generated explanations. In: 2016 11th ACM\/IEEE International Conference on Human-Robot Interaction (HRI), pp. 109\u2013116. IEEE (2016)","key":"20_CR55","DOI":"10.1109\/HRI.2016.7451741"},{"issue":"4","key":"20_CR56","doi-asserted-by":"publisher","first-page":"1518","DOI":"10.1016\/j.ijforecast.2022.11.005","volume":"39","author":"X Wang","year":"2023","unstructured":"Wang, X., Hyndman, R.J., Li, F., Kang, Y.: Forecast combinations: an over 50-year review. Int. J. Forecast. 39(4), 1518\u20131547 (2023)","journal-title":"Int. J. Forecast."},{"unstructured":"Welinder, P., Branson, S., Perona, P., Belongie, S.: The multidimensional wisdom of crowds. In: Advances in Neural Information Processing Systems, vol. 23 (2010)","key":"20_CR57"},{"key":"20_CR58","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2023.101906","volume":"55","author":"Y Wu","year":"2023","unstructured":"Wu, Y., Ma, L., Yuan, X., Li, Q.: Human-machine hybrid intelligence for the generation of car frontal forms. Adv. Eng. Inform. 55, 101906 (2023)","journal-title":"Adv. Eng. Inform."},{"doi-asserted-by":"crossref","unstructured":"Zhang, Y., Liao, Q.V., Bellamy, R.K.: Effect of confidence and explanation on accuracy and trust calibration in AI-assisted decision making. In: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, pp. 295\u2013305 (2020)","key":"20_CR59","DOI":"10.1145\/3351095.3372852"}],"container-title":["Lecture Notes in Computer Science","Human Interface and the Management of Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-60125-5_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,6,1]],"date-time":"2024-06-01T01:23:37Z","timestamp":1717205017000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-60125-5_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9783031601248","9783031601255"],"references-count":59,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-60125-5_20","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"1 June 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"The authors have no competing interests to declare that are relevant to the content of this article.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Disclosure of Interests"}},{"value":"HCII","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Human-Computer Interaction","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Washington DC","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"USA","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2024","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"29 June 2024","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"4 July 2024","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"26","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"hcii2024","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2024.hci.international\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}