{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,30]],"date-time":"2026-04-30T08:12:13Z","timestamp":1777536733385,"version":"3.51.4"},"reference-count":45,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T00:00:00Z","timestamp":1635811200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"},{"start":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T00:00:00Z","timestamp":1635811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0"}],"funder":[{"name":"IHP GmbH \u2013 Leibniz-Institut f\u00fcr innovative Mikroelektronik"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["AI Ethics"],"published-print":{"date-parts":[[2022,2]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Sustainability constitutes a focal challenge and objective of our time and requires collaborative efforts. As artificial intelligence brings forth substantial opportunities for innovations across industry and social contexts, so it provides innovation potential for pursuing sustainability. We argue that (chemical) research and development driven by artificial intelligence can substantially contribute to sustainability if it is leveraged in an ethical way. Therefore, we propose that the ethical principle <jats:italic>explicability<\/jats:italic> combined with (open) research data management systems should accompany artificial intelligence in research and development to foster sustainability in an equitable and collaborative way.<\/jats:p>","DOI":"10.1007\/s43681-021-00114-8","type":"journal-article","created":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T12:07:18Z","timestamp":1635854838000},"page":"29-33","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":17,"title":["Artificial intelligence in research and development for sustainability: the centrality of explicability and research data management"],"prefix":"10.1007","volume":"2","author":[{"given":"Erik","family":"Hermann","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gunter","family":"Hermann","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,11,2]]},"reference":[{"issue":"14","key":"114_CR1","doi-asserted-by":"publisher","first-page":"5915","DOI":"10.1016\/j.eswa.2015.03.023","volume":"42","author":"JM Ali","year":"2015","unstructured":"Ali, J.M., Hussain, M.A., Tade, M.O., Zhang, J.: Artificial Intelligence techniques applied as estimator in chemical process systems \u2013 A literature survey. Expert Syst. Appl. 42(14), 5915\u20135931 (2015). https:\/\/doi.org\/10.1016\/j.eswa.2015.03.023","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"114_CR2","doi-asserted-by":"publisher","first-page":"973","DOI":"10.1177\/1461444816676645","volume":"20","author":"M Ananny","year":"2018","unstructured":"Ananny, M., Crawford, K.: Seeing without knowing: Limitations of the transparency ideal and its application to algorithmic accountability. New Med. Soc. 20(3), 973\u2013989 (2018). https:\/\/doi.org\/10.1177\/1461444816676645","journal-title":"New Med. Soc."},{"key":"114_CR3","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.inffus.2019.12.012","volume":"58","author":"A Barredo Arrieta","year":"2020","unstructured":"Barredo Arrieta, A., D\u00edaz-Rodr\u00edguez, N., Del Ser, J., Benneto, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., Chatila, R., Herrera, F.: Explainable artificial intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fusion 58, 82\u2013115 (2020). https:\/\/doi.org\/10.1016\/j.inffus.2019.12.012","journal-title":"Inf. Fusion"},{"key":"114_CR4","doi-asserted-by":"publisher","first-page":"102225","DOI":"10.1016\/j.ijinfomgt.2020.102225","volume":"57","author":"AFS Borges","year":"2021","unstructured":"Borges, A.F.S., Laurindo, F.J.B., Sp\u00ednola, M.M., Gon\u00e7alves, R.F., Mattos, C.A.: The strategic use of artificial intelligence in the digital era: systematic literature review and future research directions. Int. J. Inf. Manage 57, 102225 (2021). https:\/\/doi.org\/10.1016\/j.ijinfomgt.2020.102225","journal-title":"Int. J. Inf. Manage"},{"issue":"6370","key":"114_CR5","doi-asserted-by":"publisher","first-page":"1530","DOI":"10.1126\/science.aap8062","volume":"358","author":"E Brynjolfsson","year":"2017","unstructured":"Brynjolfsson, E., Mitchell, T.M.: What can machine learning do? Workforce implications. Science 358(6370), 1530\u20131534 (2017). https:\/\/doi.org\/10.1126\/science.aap8062","journal-title":"Science"},{"key":"114_CR6","doi-asserted-by":"publisher","first-page":"391","DOI":"10.1016\/j.jbusres.2020.11.003","volume":"131","author":"G Calic","year":"2021","unstructured":"Calic, G., Ghasemaghaei, M.: Big data for social benefits: Innovation as a mediator of the relationship between big data and corporate social performance. J. Bus. Res. 131, 391\u2013401 (2021). https:\/\/doi.org\/10.1016\/j.jbusres.2020.11.003","journal-title":"J. Bus. Res."},{"issue":"4","key":"114_CR7","doi-asserted-by":"publisher","first-page":"2051","DOI":"10.1007\/s11948-019-00146-8","volume":"26","author":"M Coeckelbergh","year":"2020","unstructured":"Coeckelbergh, M.: Artificial intelligence, responsibility attribution, and a relational justification of explainability. Sci. Eng. Ethics 26(4), 2051\u20132068 (2020). https:\/\/doi.org\/10.1007\/s11948-019-00146-8","journal-title":"Sci. Eng. Ethics"},{"issue":"2","key":"114_CR8","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1038\/s42256-021-00296-0","volume":"3","author":"J Cowls","year":"2021","unstructured":"Cowls, J., Tsamados, A., Taddeo, M., Floridi, L.: A definition, benchmark and database of AI for social good initiatives. Nat. Mach. Intell. 3(2), 111\u2013115 (2021). https:\/\/doi.org\/10.1038\/s42256-021-00296-0","journal-title":"Nat. Mach. Intell."},{"issue":"10","key":"114_CR9","doi-asserted-by":"publisher","first-page":"589","DOI":"10.1038\/s41570-019-0124-0","volume":"3","author":"AF de Almeida","year":"2019","unstructured":"de Almeida, A.F., Moreira, R., Rodrigues, T.: Synthetic organic chemistry driven by artificial intelligence. Nat. Rev. Chem. 3(10), 589\u2013604 (2019). https:\/\/doi.org\/10.1038\/s41570-019-0124-0","journal-title":"Nat. Rev. Chem."},{"key":"114_CR10","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.ijinfomgt.2019.01.021","volume":"48","author":"Y Duan","year":"2019","unstructured":"Duan, Y., Edwards, J.S., Dwivedi, Y.K.: Artificial intelligence for decision making in the era of Big Data \u2013 evolution, challenges and research agenda. Int. J. Inf. Manage 48, 63\u201371 (2019). https:\/\/doi.org\/10.1016\/j.ijinfomgt.2019.01.021","journal-title":"Int. J. Inf. Manage"},{"key":"114_CR11","doi-asserted-by":"publisher","first-page":"101994","DOI":"10.1016\/j.ijinfomgt.2019.08.002","volume":"57","author":"YK Dwivedi","year":"2021","unstructured":"Dwivedi, Y.K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P.V., Janssen, M., Jones, P., Kar, A.K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., Williams, M.D.: Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. Int J Inf Manage 57, 101994 (2021). https:\/\/doi.org\/10.1016\/j.ijinfomgt.2019.08.002","journal-title":"Int J Inf Manage"},{"issue":"6476","key":"114_CR12","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1126\/science.aay6636","volume":"367","author":"BI Escher","year":"2020","unstructured":"Escher, B.I., Stapleton, H.M., Schymanski, E.L.: Tracking complex mixtures of chemicals in our changing environment. Science 367(6476), 388\u2013392 (2020). https:\/\/doi.org\/10.1126\/science.aay6636","journal-title":"Science"},{"issue":"3","key":"114_CR13","doi-asserted-by":"publisher","first-page":"1771","DOI":"10.1007\/s11948-020-00213-5","volume":"26","author":"L Floridi","year":"2020","unstructured":"Floridi, L., Cowls, J., King, T.C., Taddeo, M.: How to design AI for social good: seven essential factors. Sci Eng Ethics 26(3), 1771\u20131796 (2020). https:\/\/doi.org\/10.1007\/s11948-020-00213-5","journal-title":"Sci Eng Ethics"},{"issue":"4","key":"114_CR14","doi-asserted-by":"publisher","first-page":"689","DOI":"10.1007\/s11023-018-9482-5","volume":"28","author":"L Floridi","year":"2018","unstructured":"Floridi, L., Cowls, J., Beltrametti, M., Chatila, R., Chazerand, P., Dignum, V., Luetge, C., Madelin, R., Pagallo, U., Rossi, F., Schafer, B., Valcke, P., Vayena, E.: AI4People \u2013 An ethical framework for a good AI society: opportunities, risks, principles, and recommendations. Minds Mach. 28(4), 689\u2013707 (2018). https:\/\/doi.org\/10.1007\/s11023-018-9482-5","journal-title":"Minds Mach."},{"issue":"20","key":"114_CR15","doi-asserted-by":"publisher","first-page":"2233","DOI":"10.1002\/cphc.202000518","volume":"21","author":"J Gasteiger","year":"2020","unstructured":"Gasteiger, J.: Chemistry in times of artificial intelligence. ChemPhysChem 21(20), 2233\u20132242 (2020). https:\/\/doi.org\/10.1002\/cphc.202000518","journal-title":"ChemPhysChem"},{"key":"114_CR16","doi-asserted-by":"publisher","first-page":"147","DOI":"10.1016\/j.jbusres.2019.09.062","volume":"108","author":"M Ghasemaghaei","year":"2020","unstructured":"Ghasemaghaei, M., Calic, G.: Assessing the impact of big data on firm innovation performance: big data is not always better data. J. Bus. Res. 108, 147\u2013162 (2020). https:\/\/doi.org\/10.1016\/j.jbusres.2019.09.062","journal-title":"J. Bus. Res."},{"issue":"1","key":"114_CR17","doi-asserted-by":"publisher","first-page":"99","DOI":"10.1007\/s11023-020-09517-8","volume":"30","author":"T Hagendorff","year":"2020","unstructured":"Hagendorff, T.: The ethics of AI ethics: an evaluation of guidelines. Minds Mach. 30(1), 99\u2013120 (2020). https:\/\/doi.org\/10.1007\/s11023-020-09517-8","journal-title":"Minds Mach."},{"key":"114_CR18","unstructured":"IPCC: Global warming of 1.5 \u00b0C. An IPCC Special Report on the impacts of global warming of 1.5 \u00b0C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. IPCC (Intergovernmental Panel on Climate Change) (2018)."},{"issue":"4","key":"114_CR19","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1080\/10590501.2018.1537118","volume":"36","author":"G Idakwo","year":"2019","unstructured":"Idakwo, G., Luttrell, J., Chen, M., Hong, H., Zhou, Z., Gong, P., Zhang, C.: A review on machine learning methods for in silico toxicity prediction. J. Environ. Sci. Health C Toxicol. Carcinog. 36(4), 169\u2013191 (2019). https:\/\/doi.org\/10.1080\/10590501.2018.1537118","journal-title":"J. Environ. Sci. Health C Toxicol. Carcinog."},{"issue":"10","key":"114_CR20","doi-asserted-by":"publisher","first-page":"573","DOI":"10.1038\/s42256-020-00236-4","volume":"2","author":"J Jim\u00e9nez-Luna","year":"2020","unstructured":"Jim\u00e9nez-Luna, J., Grisoni, F., Schneider, G.: Drug discovery with explainable artificial intelligence. Nat. Mach. Intell. 2(10), 573\u2013584 (2020). https:\/\/doi.org\/10.1038\/s42256-020-00236-4","journal-title":"Nat. Mach. Intell."},{"issue":"9","key":"114_CR21","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1038\/s42256-019-0088-2","volume":"1","author":"A Jobin","year":"2019","unstructured":"Jobin, A., Ienca, M., Vayena, E.: The global landscape of AI ethics guidelines. Nat. Mach. Intell. 1(9), 389\u2013399 (2019). https:\/\/doi.org\/10.1038\/s42256-019-0088-2","journal-title":"Nat. Mach. Intell."},{"issue":"6476","key":"114_CR22","doi-asserted-by":"publisher","first-page":"384","DOI":"10.1126\/science.aay6637","volume":"367","author":"AC Johnson","year":"2020","unstructured":"Johnson, A.C., Jin, X., Nakada, N., Sumpter, J.P.: Learning from the past and considering the future of chemicals in the environment. Science 367(6476), 384\u2013387 (2020). https:\/\/doi.org\/10.1126\/science.aay6637","journal-title":"Science"},{"issue":"6245","key":"114_CR23","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). https:\/\/doi.org\/10.1126\/science.aaa8415","journal-title":"Science"},{"issue":"1","key":"114_CR24","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/j.bushor.2019.09.003","volume":"63","author":"A Kaplan","year":"2020","unstructured":"Kaplan, A., Haenlein, M.: Rulers of the world, unite! The challenges and opportunities of artificial intelligence. Bus. Horiz. 63(1), 37\u201350 (2020). https:\/\/doi.org\/10.1016\/j.bushor.2019.09.003","journal-title":"Bus. Horiz."},{"key":"114_CR25","doi-asserted-by":"publisher","first-page":"102371","DOI":"10.1016\/j.ijinfomgt.2021.102371","volume":"60","author":"S Kwon","year":"2021","unstructured":"Kwon, S., Motohashi, K.: Incentive or disincentive for research data disclosure? A large-scale empirical analysis and implications for open science policy. Int. J. Inf. Manage 60, 102371 (2021). https:\/\/doi.org\/10.1016\/j.ijinfomgt.2021.102371","journal-title":"Int. J. Inf. Manage"},{"issue":"4","key":"114_CR26","doi-asserted-by":"publisher","first-page":"611","DOI":"10.1007\/s13347-017-0279-x","volume":"31","author":"B Lepri","year":"2018","unstructured":"Lepri, B., Oliver, N., Letouz\u00e9, E., Pentland, A., Vinck, P.: Fair, transparent, and accountable algorithmic decision-making processes. The premise, the proposed solutions, and the open challenges. Philos. Technol. 31(4), 611\u2013627 (2018). https:\/\/doi.org\/10.1007\/s13347-017-0279-x","journal-title":"Philos. Technol."},{"issue":"25","key":"114_CR27","doi-asserted-by":"publisher","first-page":"587","DOI":"10.1016\/j.anireprosci.2016.02.027","volume":"41","author":"G Link","year":"2017","unstructured":"Link, G., Lumbard, K., Conboy, K., Feldman, M., Feller, J., George, J., Germonprez, M., Goggins, S., Jeske, D., Kiely, G., Schuster, K., Willis, M.: Contemporary issues of open data in information systems research: considerations and recommendations. Commun. Assoc. Inf. Syst. 41(25), 587\u2013610 (2017). https:\/\/doi.org\/10.1016\/j.anireprosci.2016.02.027","journal-title":"Commun. Assoc. Inf. Syst."},{"issue":"4","key":"114_CR28","doi-asserted-by":"publisher","first-page":"835","DOI":"10.1007\/s10551-018-3921-3","volume":"160","author":"K Martin","year":"2019","unstructured":"Martin, K.: Ethical implications and accountability of algorithms. J. Bus. Ethics 160(4), 835\u2013850 (2019). https:\/\/doi.org\/10.1007\/s10551-018-3921-3","journal-title":"J. Bus. Ethics"},{"issue":"11","key":"114_CR29","doi-asserted-by":"publisher","first-page":"501","DOI":"10.1038\/s42256-019-0114-4","volume":"1","author":"BD Mittelstadt","year":"2019","unstructured":"Mittelstadt, B.D.: Principles alone cannot guarantee ethical AI. Nat. Mach. Intell. 1(11), 501\u2013507 (2019). https:\/\/doi.org\/10.1038\/s42256-019-0114-4","journal-title":"Nat. Mach. Intell."},{"issue":"2","key":"114_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1177\/2053951716679679","volume":"3","author":"BD Mittelstadt","year":"2016","unstructured":"Mittelstadt, B.D., Allo, P., Taddeo, M., Wachter, S., Floridi, L.: The ethics of algorithms: mapping the debate. Big Data Soc. 3(2), 1\u201321 (2016). https:\/\/doi.org\/10.1177\/2053951716679679","journal-title":"Big Data Soc."},{"issue":"4","key":"114_CR31","doi-asserted-by":"publisher","first-page":"2141","DOI":"10.1007\/s11948-019-00165-5","volume":"26","author":"J Morley","year":"2020","unstructured":"Morley, J., Floridi, L., Kinsey, L., Elhalal, A.: From what to how: an initial review of publicly available AI ethics tools, methods and research to translate principles into practices. Sci. Eng. Ethics 26(4), 2141\u20132168 (2020). https:\/\/doi.org\/10.1007\/s11948-019-00165-5","journal-title":"Sci. Eng. Ethics"},{"issue":"44","key":"114_CR32","doi-asserted-by":"publisher","first-page":"22071","DOI":"10.1073\/pnas.1900654116","volume":"116","author":"WJ Murdoch","year":"2019","unstructured":"Murdoch, W.J., Singh, C., Kumbier, K., Abbasi-Asl, R., Yu, B.: Definitions, methods, and applications in interpretable machine learning. Proc. Natl. Acad. Sci. 116(44), 22071\u201322080 (2019). https:\/\/doi.org\/10.1073\/pnas.1900654116","journal-title":"Proc. Natl. Acad. Sci."},{"key":"114_CR33","doi-asserted-by":"publisher","first-page":"102104","DOI":"10.1016\/j.ijinfomgt.2020.102104","volume":"53","author":"R Nishant","year":"2020","unstructured":"Nishant, R., Kennedy, M., Corbett, J.: Artificial intelligence for sustainability: challenges, opportunities, and a research agenda. Int. J. Inf. Manage 53, 102104 (2020). https:\/\/doi.org\/10.1016\/j.ijinfomgt.2020.102104","journal-title":"Int. J. Inf. Manage"},{"issue":"4","key":"114_CR34","doi-asserted-by":"publisher","first-page":"174","DOI":"10.1038\/s42256-019-0038-z","volume":"1","author":"AS Rich","year":"2019","unstructured":"Rich, A.S., Gureckis, T.M.: Lessons for artificial intelligence from the study of natural stupidity. Nat. Mach. Intell. 1(4), 174\u2013180 (2019). https:\/\/doi.org\/10.1038\/s42256-019-0038-z","journal-title":"Nat. Mach. Intell."},{"issue":"1","key":"114_CR35","doi-asserted-by":"publisher","first-page":"24","DOI":"10.1890\/120375","volume":"12","author":"J R\u00fcegg","year":"2014","unstructured":"R\u00fcegg, J., Gries, C., Bond-Lamberty, B., Bowen, G.J., Felzer, B.S., McIntyre, N.E., Soranno, P.A., Vanderbilt, K.L., Weathers, K.C.: Completing the data life cycle: using information management in macrosystems ecology research. Front. Ecol. Environ. 12(1), 24\u201330 (2014). https:\/\/doi.org\/10.1890\/120375","journal-title":"Front. Ecol. Environ."},{"issue":"2","key":"114_CR36","doi-asserted-by":"publisher","first-page":"97","DOI":"10.1038\/nrd.2017.232","volume":"17","author":"G Schneider","year":"2018","unstructured":"Schneider, G.: Automating drug discovery. Nat. Rev. Drug Discov. 17(2), 97\u2013113 (2018). https:\/\/doi.org\/10.1038\/nrd.2017.232","journal-title":"Nat. Rev. Drug Discov."},{"issue":"3","key":"114_CR37","doi-asserted-by":"publisher","first-page":"128","DOI":"10.1038\/s42256-019-0030-7","volume":"1","author":"G Schneider","year":"2019","unstructured":"Schneider, G.: Mind and machine in drug design. Nat. Mach. Intell. 1(3), 128\u2013130 (2019). https:\/\/doi.org\/10.1038\/s42256-019-0030-7","journal-title":"Nat. Mach. Intell."},{"issue":"18","key":"114_CR38","doi-asserted-by":"publisher","first-page":"10777","DOI":"10.1021\/acs.est.7b02862","volume":"51","author":"R Song","year":"2017","unstructured":"Song, R., Keller, A.A., Suh, S.: Rapid life-cycle impact screening using artificial neural networks. Environ. Sci. Technol. 51(18), 10777\u201310785 (2017). https:\/\/doi.org\/10.1021\/acs.est.7b02862","journal-title":"Environ. Sci. Technol."},{"issue":"6404","key":"114_CR39","doi-asserted-by":"publisher","first-page":"751","DOI":"10.1126\/science.aat5991","volume":"361","author":"M Taddeo","year":"2018","unstructured":"Taddeo, M., Floridi, L.: How AI can be a force for good. Science 361(6404), 751\u2013752 (2018). https:\/\/doi.org\/10.1126\/science.aat5991","journal-title":"Science"},{"issue":"2","key":"114_CR40","doi-asserted-by":"publisher","first-page":"105","DOI":"10.1007\/s10676-009-9187-9","volume":"11","author":"M Turilli","year":"2009","unstructured":"Turilli, M., Floridi, L.: The ethics of information transparency. Ethics Inf. Technol. 11(2), 105\u2013112 (2009). https:\/\/doi.org\/10.1007\/s10676-009-9187-9","journal-title":"Ethics Inf. Technol."},{"key":"114_CR41","doi-asserted-by":"publisher","DOI":"10.1007\/s43681-021-00043-6","author":"A van Wynsberghe","year":"2021","unstructured":"van Wynsberghe, A.: Sustainable AI: AI for sustainability and the sustainability of AI. AI Ethics (2021). https:\/\/doi.org\/10.1007\/s43681-021-00043-6","journal-title":"AI Ethics"},{"key":"114_CR42","doi-asserted-by":"publisher","first-page":"233","DOI":"10.1038\/s41467-019-14108-y","volume":"11","author":"R Vinuesa","year":"2020","unstructured":"Vinuesa, R., Azizpour, H., Leite, I., Balaam, M., Dignum, V., Domisch, S., Fell\u00e4nder, A., Langhans, S.D., Tegmark, M., Fuso Nerini, F.: The role of artificial intelligence in achieving the sustainable development goals. Nat. Commun. 11, 233 (2020). https:\/\/doi.org\/10.1038\/s41467-019-14108-y","journal-title":"Nat. Commun."},{"issue":"1","key":"114_CR43","doi-asserted-by":"publisher","first-page":"20","DOI":"10.1021\/acs.chemrestox.9b00227","volume":"33","author":"AH Vo","year":"2020","unstructured":"Vo, A.H., Van Vleet, T.R., Gupta, R.R., Liguori, M.J., Rao, M.S.: An overview of machine learning and big data for drug toxicity evaluation. Chem. Res. Toxicol. 33(1), 20\u201337 (2020). https:\/\/doi.org\/10.1021\/acs.chemrestox.9b00227","journal-title":"Chem. Res. Toxicol."},{"key":"114_CR44","doi-asserted-by":"publisher","first-page":"160018","DOI":"10.1038\/sdata.2016.18","volume":"3","author":"MD Wilkinson","year":"2016","unstructured":"Wilkinson, M.D., Dumontier, M., Aalsbersberg, I.J., Appleton, G., Axton, M., Mons, B.: The FAIR guiding principles for scientific data management and stewardship. Sci. Data 3, 160018 (2016). https:\/\/doi.org\/10.1038\/sdata.2016.18","journal-title":"Sci. Data"},{"key":"114_CR45","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1057\/s41599-020-0467-7","volume":"6","author":"F Zagonari","year":"2020","unstructured":"Zagonari, F.: Environmental sustainability is not worth pursuing unless it is achieved for ethical reasons. Palgrave Commun. 6, 108 (2020). https:\/\/doi.org\/10.1057\/s41599-020-0467-7","journal-title":"Palgrave Commun."}],"container-title":["AI and Ethics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43681-021-00114-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s43681-021-00114-8\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s43681-021-00114-8.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,4,19]],"date-time":"2022-04-19T08:14:00Z","timestamp":1650356040000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s43681-021-00114-8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,2]]},"references-count":45,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2022,2]]}},"alternative-id":["114"],"URL":"https:\/\/doi.org\/10.1007\/s43681-021-00114-8","relation":{},"ISSN":["2730-5953","2730-5961"],"issn-type":[{"value":"2730-5953","type":"print"},{"value":"2730-5961","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,2]]},"assertion":[{"value":"13 July 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 October 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 November 2021","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors have no conflicts of interest to declare that are relevant to the content of this article.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}