{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T17:56:33Z","timestamp":1776102993698,"version":"3.50.1"},"publisher-location":"Cham","reference-count":37,"publisher":"Springer Nature Switzerland","isbn-type":[{"value":"9783031746260","type":"print"},{"value":"9783031746277","type":"electronic"}],"license":[{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,1,1]],"date-time":"2025-01-01T00:00:00Z","timestamp":1735689600000},"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":[[2025]]},"DOI":"10.1007\/978-3-031-74627-7_20","type":"book-chapter","created":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T14:00:14Z","timestamp":1735653614000},"page":"268-275","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Towards Synergistic Human-AI Collaboration in\u00a0Hybrid Decision-Making Systems"],"prefix":"10.1007","author":[{"given":"Clara","family":"Punzi","sequence":"first","affiliation":[]},{"given":"Mattia","family":"Setzu","sequence":"additional","affiliation":[]},{"given":"Roberto","family":"Pellungrini","sequence":"additional","affiliation":[]},{"given":"Fosca","family":"Giannotti","sequence":"additional","affiliation":[]},{"given":"Dino","family":"Pedreschi","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,1,1]]},"reference":[{"issue":"8","key":"20_CR1","doi-asserted-by":"publisher","first-page":"18","DOI":"10.1109\/MC.2020.2996587","volume":"53","author":"Z Akata","year":"2020","unstructured":"Akata, Z., et al.: A research agenda for hybrid intelligence: augmenting human intellect with collaborative, adaptive, responsible, and explainable artificial intelligence. Computer 53(8), 18\u201328 (2020). https:\/\/doi.org\/10.1109\/MC.2020.2996587","journal-title":"Computer"},{"key":"20_CR2","unstructured":"Alkan, O., Wei, D., Mattetti, M., Nair, R., Daly, E., Saha, D.: FROTE: feedback rule-driven oversampling for editing models. In: Marculescu, D., Chi, Y., Wu, C. (eds.) Proceedings of Machine Learning and Systems 2022, MLSys 2022, Santa Clara, CA, USA, August 29 - September 1 2022 (2022)"},{"key":"20_CR3","doi-asserted-by":"publisher","unstructured":"Bansal, G., Nushi, B., Kamar, E., Lasecki, W.S., Weld, D.S., Horvitz, E.: Beyond accuracy: the role of mental models in human-AI team performance. In: Proceedings of the AAAI Conference on Human Computation and Crowdsourcing, vol. 7, pp. 2\u201311, October 2019. https:\/\/doi.org\/10.1609\/hcomp.v7i1.5285","DOI":"10.1609\/hcomp.v7i1.5285"},{"key":"20_CR4","doi-asserted-by":"publisher","unstructured":"Binns, R., Veale, M.: Is that your final decision? Multi-stage profiling, selective effects, and Article 22 of the GDPR. Int. Data Priv. Law 11(4), 319\u2013332 (2021). https:\/\/doi.org\/10.1093\/idpl\/ipab020","DOI":"10.1093\/idpl\/ipab020"},{"key":"20_CR5","doi-asserted-by":"publisher","unstructured":"Cabitza, F., et al.: Rams, hounds and white boxes: investigating human-AI collaboration protocols in medical diagnosis. Artif. Intell. Med. 138, 102506 (2023). https:\/\/doi.org\/10.1016\/j.artmed.2023.102506","DOI":"10.1016\/j.artmed.2023.102506"},{"key":"20_CR6","doi-asserted-by":"publisher","unstructured":"Cabitza, F., Natali, C.: Open, multiple, adjunct. decision support at the time of relational AI. In: HHAI2022: Augmenting Human Intellect. IOS Press, September 2022. https:\/\/doi.org\/10.3233\/faia220204","DOI":"10.3233\/faia220204"},{"key":"20_CR7","doi-asserted-by":"publisher","unstructured":"Cortes, C., DeSalvo, G., Mohri, M.: Learning with rejection. In: Ortner, R., Simon, H., Zilles, S. (eds.) ALT 2016. LNCS, vol. 9925, pp. 67\u201382. Springer, Cham (2016). https:\/\/doi.org\/10.1007\/978-3-319-46379-7_5. https:\/\/cs.nyu.edu\/~mohri\/pub\/rej.pdf","DOI":"10.1007\/978-3-319-46379-7_5"},{"key":"20_CR8","doi-asserted-by":"publisher","unstructured":"Elgohary, A., Meek, C., Richardson, M., Fourney, A., Ramos, G., Awadallah, A.H.: NL-EDIT: correcting semantic parse errors through natural language interaction. In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pp. 5599\u20135610. Association for Computational Linguistics, Online, June 2021. https:\/\/doi.org\/10.18653\/v1\/2021.naacl-main.444","DOI":"10.18653\/v1\/2021.naacl-main.444"},{"issue":"2","key":"20_CR9","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1177\/0146167205282152","volume":"32","author":"B Englich","year":"2006","unstructured":"Englich, B., Mussweiler, T., Strack, F.: Playing dice with criminal sentences: the influence of irrelevant anchors on experts\u2019 judicial decision making. Pers. Soc. Psychol. Bull. 32(2), 188\u2013200 (2006). https:\/\/doi.org\/10.1177\/0146167205282152","journal-title":"Pers. Soc. Psychol. Bull."},{"key":"20_CR10","unstructured":"European Commission: Proposal for a regulation of the European parliament and of the council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act) and amending certain union legislative acts (2021), COM(2021) 206 final. https:\/\/eur-lex.europa.eu\/legal-content\/EN\/TXT\/?uri=celex%3A52021PC0206. Accessed 15 June 2023"},{"key":"20_CR11","unstructured":"European Commission and Directorate-General for Communications Networks, Content and Technology: Ethics guidelines for trustworthy AI (2019). https:\/\/digital-strategy.ec.europa.eu\/en\/library\/ethics-guidelines-trustworthy-ai"},{"key":"20_CR12","unstructured":"Geifman, Y., El-Yaniv, R.: Selective classification for deep neural networks. In: Guyon, I., Luxburg, U.V., Bengio, S., Wallach, H., Fergus, R., Vishwanathan, S., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol.\u00a030. Curran Associates, Inc. (2017)"},{"key":"20_CR13","doi-asserted-by":"publisher","unstructured":"Giannotti, F., Naretto, F., Bodria, F.: Explainable for trustworthy AI. In: Chetouani, M., Dignum, V., Lukowicz, P., Sierra, C. (eds.) ACAI 2021. LNCS, vol. 13500, pp. 175\u2013195. Springer, Cham (2023). https:\/\/doi.org\/10.1007\/978-3-031-24349-3_10","DOI":"10.1007\/978-3-031-24349-3_10"},{"key":"20_CR14","doi-asserted-by":"publisher","unstructured":"Grgi\u0107-Hlac\u0306a, N., Lima, G., Weller, A., Redmiles, E.M.: Dimensions of diversity in human perceptions of algorithmic fairness. In: Equity and Access in Algorithms, Mechanisms, and Optimization, EAAMO 2022, Arlington, VA, USA, 6\u20139 October 2022, pp. 21:1\u201321:12. ACM (2022). https:\/\/doi.org\/10.1145\/3551624.3555306","DOI":"10.1145\/3551624.3555306"},{"key":"20_CR15","doi-asserted-by":"publisher","unstructured":"Guo, L., Daly, E.M., Alkan, O., Mattetti, M., Cornec, O., Knijnenburg, B.: Building trust in interactive machine learning via user contributed interpretable rules. In: 27th International Conference on Intelligent User Interfaces. ACM, March 2022. https:\/\/doi.org\/10.1145\/3490099.3511111","DOI":"10.1145\/3490099.3511111"},{"key":"20_CR16","series-title":"Lecture Notes in Computer Science (Lecture Notes in Artificial Intelligence)","doi-asserted-by":"publisher","first-page":"77","DOI":"10.1007\/978-3-030-30391-4_5","volume-title":"Explainable, Transparent Autonomous Agents and Multi-Agent Systems","author":"SF Jentzsch","year":"2019","unstructured":"Jentzsch, S.F., H\u00f6hn, S., Hochgeschwender, N.: Conversational interfaces for explainable AI: a human-centred approach. In: Calvaresi, D., Najjar, A., Schumacher, M., Fr\u00e4mling, K. (eds.) EXTRAAMAS 2019. LNCS (LNAI), vol. 11763, pp. 77\u201392. Springer, Cham (2019). https:\/\/doi.org\/10.1007\/978-3-030-30391-4_5"},{"key":"20_CR17","volume-title":"Thinking, Fast and Slow","author":"D Kahneman","year":"2013","unstructured":"Kahneman, D.: Thinking, Fast and Slow. Farrar Straus & Giroux, New York (2013)"},{"issue":"6","key":"20_CR18","doi-asserted-by":"publisher","first-page":"720","DOI":"10.1177\/1023263X20978649","volume":"27","author":"R Koulu","year":"2020","unstructured":"Koulu, R.: Proceduralizing control and discretion: human oversight in artificial intelligence policy. Maastricht J. Eur. Comp. Law 27(6), 720\u2013735 (2020). https:\/\/doi.org\/10.1177\/1023263X20978649","journal-title":"Maastricht J. Eur. Comp. Law"},{"key":"20_CR19","doi-asserted-by":"publisher","unstructured":"Lai, V., Tan, C.: On human predictions with explanations and predictions of machine learning models: a case study on deception detection. In: Proceedings of the Conference on Fairness, Accountability, and Transparency, pp. 29\u201338 (2019). https:\/\/doi.org\/10.1145\/3287560.3287590","DOI":"10.1145\/3287560.3287590"},{"key":"20_CR20","doi-asserted-by":"publisher","unstructured":"Le, T., Miller, T., Singh, R., Sonenberg, L.: Explaining model confidence using counterfactuals. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 37, no. 10, pp. 11856\u201311864 (2023). https:\/\/doi.org\/10.1609\/aaai.v37i10.26399","DOI":"10.1609\/aaai.v37i10.26399"},{"issue":"1","key":"20_CR21","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1518\/hfes.46.1.50_30392","volume":"46","author":"JD Lee","year":"2004","unstructured":"Lee, J.D., See, K.A.: Trust in automation: designing for appropriate reliance. Hum. Factors J. Hum. Factors Ergon. Soc. 46(1), 50\u201380 (2004). https:\/\/doi.org\/10.1518\/hfes.46.1.50_30392","journal-title":"Hum. Factors J. Hum. Factors Ergon. Soc."},{"issue":"1","key":"20_CR22","doi-asserted-by":"publisher","first-page":"205395171875668","DOI":"10.1177\/2053951718756684","volume":"5","author":"MK Lee","year":"2018","unstructured":"Lee, M.K.: Understanding perception of algorithmic decisions: fairness, trust, and emotion in response to algorithmic management. Big Data Soc. 5(1), 2053951718756684 (2018). https:\/\/doi.org\/10.1177\/2053951718756684","journal-title":"Big Data Soc."},{"key":"20_CR23","doi-asserted-by":"publisher","unstructured":"Leit\u00e3o, D., Saleiro, P., Figueiredo, M.A.T., Bizarro, P.: Human-AI collaboration in decision-making: beyond learning to defer (2022). https:\/\/doi.org\/10.48550\/ARXIV.2206.13202","DOI":"10.48550\/ARXIV.2206.13202"},{"key":"20_CR24","unstructured":"Madras, D., Pitassi, T., Zemel, R.: Predict responsibly: improving fairness and accuracy by learning to defer. In: Bengio, S., Wallach, H., Larochelle, H., Grauman, K., Cesa-Bianchi, N., Garnett, R. (eds.) Advances in Neural Information Processing Systems, vol.\u00a031. Curran Associates, Inc. (2018)"},{"key":"20_CR25","unstructured":"Madumal, P., Miller, T., Vetere, F., Sonenberg, L.: Towards a grounded dialog model for explainable artificial intelligence. arXiv preprint arXiv:1806.08055 (2018)"},{"key":"20_CR26","doi-asserted-by":"publisher","unstructured":"Miller, T.: Explainable AI is dead, long live explainable AI! Hypothesis-driven decision support (2023). https:\/\/doi.org\/10.48550\/ARXIV.2302.12389","DOI":"10.48550\/ARXIV.2302.12389"},{"key":"20_CR27","unstructured":"Mozannar, H., Lang, H., Wei, D., Sattigeri, P., Das, S., Sontag, D.: Who should predict? exact algorithms for learning to defer to humans. In: Ruiz, F., Dy, J., van\u00a0de Meent, J.W. (eds.) Proceedings of The 26th International Conference on Artificial Intelligence and Statistics. Proceedings of Machine Learning Research, vol.\u00a0206, pp. 10520\u201310545. PMLR, 25\u201327 April 2023"},{"key":"20_CR28","doi-asserted-by":"publisher","unstructured":"Panigutti, C., et al.: Co-design of human-centered, explainable AI for clinical decision support. ACM Trans. Interact. Intell. Syst. (2023). https:\/\/doi.org\/10.1145\/3587271","DOI":"10.1145\/3587271"},{"key":"20_CR29","unstructured":"Rabinowitz, N., Perbet, F., Song, F., Zhang, C., Eslami, S.M.A., Botvinick, M.: Machine theory of mind. In: Dy, J., Krause, A. (eds.) Proceedings of the 35th International Conference on Machine Learning. Proceedings of Machine Learning Research, vol.\u00a080, pp. 4218\u20134227. PMLR, 10\u201315 July 2018"},{"issue":"5","key":"20_CR30","doi-asserted-by":"publisher","first-page":"206","DOI":"10.1038\/s42256-019-0048-x","volume":"1","author":"C Rudin","year":"2019","unstructured":"Rudin, C.: Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nat. Mach. Intell. 1(5), 206\u2013215 (2019). https:\/\/doi.org\/10.1038\/s42256-019-0048-x","journal-title":"Nat. Mach. Intell."},{"key":"20_CR31","doi-asserted-by":"publisher","unstructured":"Tandon, N., Madaan, A., Clark, P., Yang, Y.: Learning to repair: repairing model output errors after deployment using a dynamic memory of feedback. In: Findings of the Association for Computational Linguistics: NAACL 2022, pp. 339\u2013352. Association for Computational Linguistics, Seattle, United States, July 2022. https:\/\/doi.org\/10.18653\/v1\/2022.findings-naacl.26","DOI":"10.18653\/v1\/2022.findings-naacl.26"},{"key":"20_CR32","doi-asserted-by":"publisher","unstructured":"Teso, S., \u00d6znur Alkan, Stammer, W., Daly, E.: Leveraging explanations in interactive machine learning: an overview. Front. Artif. Intell. 6 (2023). https:\/\/doi.org\/10.3389\/frai.2023.1066049","DOI":"10.3389\/frai.2023.1066049"},{"key":"20_CR33","doi-asserted-by":"publisher","unstructured":"Teso, S., Kersting, K.: Explanatory interactive machine learning. In: Proceedings of the 2019 AAAI\/ACM Conference on AI, Ethics, and Society. ACM, January 2019. https:\/\/doi.org\/10.1145\/3306618.3314293","DOI":"10.1145\/3306618.3314293"},{"key":"20_CR34","doi-asserted-by":"publisher","unstructured":"Wang, D., Yang, Q., Abdul, A., Lim, B.Y.: Designing theory-driven user-centric explainable AI. In: Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, May 2019. https:\/\/doi.org\/10.1145\/3290605.3300831","DOI":"10.1145\/3290605.3300831"},{"key":"20_CR35","doi-asserted-by":"publisher","DOI":"10.1111\/tops.12642","author":"SCH Yang","year":"2023","unstructured":"Yang, S.C.H., Folke, T., Shafto, P.: The inner loop of collective human-machine intelligence. Top. Cogn. Sci. (2023). https:\/\/doi.org\/10.1111\/tops.12642","journal-title":"Top. Cogn. Sci."},{"issue":"2","key":"20_CR36","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1109\/JPROC.2023.3238024","volume":"111","author":"XY Zhang","year":"2023","unstructured":"Zhang, X.Y., Xie, G.S., Li, X., Mei, T., Liu, C.L.: A survey on learning to reject. Proc. IEEE 111(2), 185\u2013215 (2023). https:\/\/doi.org\/10.1109\/JPROC.2023.3238024","journal-title":"Proc. IEEE"},{"key":"20_CR37","doi-asserted-by":"publisher","unstructured":"Zhang, Y., Liao, Q.V., Bellamy, R.K.E.: 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. ACM, January 2020. https:\/\/doi.org\/10.1145\/3351095.3372852","DOI":"10.1145\/3351095.3372852"}],"container-title":["Communications in Computer and Information Science","Machine Learning and Principles and Practice of Knowledge Discovery in Databases"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-031-74627-7_20","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,31]],"date-time":"2024-12-31T14:14:27Z","timestamp":1735654467000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-031-74627-7_20"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025]]},"ISBN":["9783031746260","9783031746277"],"references-count":37,"URL":"https:\/\/doi.org\/10.1007\/978-3-031-74627-7_20","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"value":"1865-0929","type":"print"},{"value":"1865-0937","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025]]},"assertion":[{"value":"1 January 2025","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ECML PKDD","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Joint European Conference on Machine Learning and Knowledge Discovery in Databases","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Turin","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Italy","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18 September 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"22 September 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"ecml2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/2023.ecmlpkdd.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}