Ethics and Social Responsibility in the Implementation of Artificial Intelligence Systems in the Administration

Authors

DOI:

https://doi.org/10.5281/zenodo.13308314

Keywords:

Ethics, social responsibility, artificial intelligence, business administration

Abstract

This systematic review aimed to analyse the ethical dilemmas and social responsibility implications of adopting artificial intelligence (AI) in business administration. A comprehensive search was conducted in the Scopus, Web of Science and EBSCOhost databases, identifying studies published between 2018 and 2024 that met the inclusion criteria. The narrative synthesis of the findings revealed key concerns around fairness in automated decision-making, the need for transparency and explainability of algorithms, defining responsibility for AI actions, the impact on workers’ employment and skills, and the protection of privacy and data. The review concludes that the ethical integration of AI in administration requires the adoption of clear ethical guidelines, robust governance frameworks and a proactive approach by companies to mitigate ethical risks and promote a fair, transparent and sustainable work environment.

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References

Ali, K., Alzaidi, M., Al-Fraihat, D., & Elamir, A. M. (2023). Artificial intelligence: benefits, application, ethical issues, and organizational responses. En Intelligent Sustainable Systems: selected Papers of WorldS4 2022, volume 1 (pp. 685-702). Springer Nature Singapore. https://link.springer.com/chapter/10.1007/978-981-19-7660-5_62

Benefo, E. O., Tingler, A., White, M., Cover, J., Torres, L., Broussard, C., ... & Patra, D. (2022). Ethical, legal, social, and economic (ELSE) implications of artificial intelligence at a global level: a scientometrics approach. AI and Ethics, 2(4), 667-682. https://link.springer.com/article/10.1007/s43681-021-00124-6

Tursunbayeva, A. (2019). Human resource technology disruptions and their implications for human resources management in healthcare organizations. BMC health services research, 19(1), 268. https://link.springer.com/article/10.1186/s12913-019-4068-3

Brendel, A. B., Mirbabaie, M., Lembcke, T. B., & Hofeditz, L. (2021). Ethical management of artificial intelligence. Sustainability, 13(4), 1974. https://www.mdpi.com/2071-1050/13/4/1974

Brynjolfsson, E., & McAfee, A. (2014). The second machine age: Work, progress, and prosperity in a time of brilliant technologies. W. W. Norton & Company. https://books.google.es/books?hl=es&lr=&id=WiKwAgAAQBAJ&oi=fnd&pg=PA1&dq=Brynjolfsson,+E.,+%26+McAfee,+A.+(2014).+The+second+machine+age:+Work,+progress,+and+prosperity+in+a+time+of+brilliant+technologies.+W.+W.+Norton+%26+Company.&ots=4-VoWh-tgi&sig=gQOxZmtQ_K7o8bfRF92Ou3tolSQ

Carrillo, M. R. (2020). Artificial intelligence: From ethics to law. Telecommunications Policy, 44(6), 101937. https://www.sciencedirect.com/science/article/pii/S030859612030029X

Carter, D. (2020). Regulation and ethics in artificial intelligence and machine learning technologies: Where are we now? Who is responsible? Can the information professional play a role? Business Information Review, 37(2), 60-68. https://journals.sagepub.com/doi/abs/10.1177/0266382120923962

Davenport, T. H., & Kirby, J. (2016). Only humans need apply: Winners and losers in the age of smart machines. Harper Business. https://leadersexcellence.com/wp-content/uploads/dlm_uploads/2016/08/Davenport-Leaders-Excellence-presentation.pdf

Djeffal, C. (2020). Artificial intelligence and public governance: normative guidelines for artificial intelligence in government and public administration. Regulating Artificial Intelligence, 277-293. https://link.springer.com/chapter/10.1007/978-3-030-32361-5_12

Elliott, K., Price, R., Shaw, P., Spiliotopoulos, T., Ng, M., Coopamootoo, K., & Van Moorsel, A. (2021). Towards an equitable digital society: artificial intelligence (AI) and corporate digital responsibility (CDR). Society, 58(3), 179-188. https://link.springer.com/article/10.1007/s12115-021-00594-8

Floridi, L. (2019). The ethics of information. En F. van der Hoek (Ed.), The Oxford Handbook of Philosophy of Information (pp. 443-462). Oxford University Press. https://books.google.es/books?hl=es&lr=&id=_XHcAAAAQBAJ&oi=fnd&pg=PP1&dq=Floridi,+L.+(2019).+The+ethics+of+information.+En+F.+van+der+Hoek+(Ed.),+The+Oxford+Handbook+of+Philosophy+of+Information+(pp.+443-462).+Oxford+University+Press.&ots=f_hD5_RvWX&sig=VGVY9MjV_G54RXJLEfqxQA3N8ZI

Fountaine, T., McCarthy, B., & Saleh, T. (2021). Building the AI-powered organization. Harvard Business Review, 99(4), 62-73. https://wuyuansheng.com/doc/Databricks-AI-Powered-Org__Article-Licensing-July21-1.pdf

Greenhalgh, T., & Peacock, R. (2005). Effectiveness and efficiency of search methods in systematic reviews of complex evidence: Audit of primary sources. BMJ, 331(7524), 1065–1069. https://www.bmj.com/content/331/7524/1064.short

Guyatt, G. H., Oxman, A. D., Vist, G. E., Kunz, R., Falck-Ytter, Y., Alonso-Coello, P., ... & Schünemann, H. J. (2008). GRADE: an emerging consensus on rating quality of evidence and strength of recommendations. BMJ, 336(7650), 924–926. https://www.bmj.com/content/336/7650/924.short

Harlow, H. (2018, Septiembre). Ethical concerns of artificial intelligence, big data and data analytics. En European Conference on Knowledge Management (pp. 316-323). Academic Conferences International Limited. https://search.proquest.com/openview/56146799514cd6f3c4e92e82079fb128/1?pq-origsite=gscholar&cbl=1796412

Holstein, K., Wortman Vaughan, J., Daumé III, H., Dudik, M., & Wallach, H. (2019). Improving fairness in machine learning systems: What do industry practitioners need? En Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (pp. 1-16). https://dl.acm.org/doi/abs/10.1145/3290605.3300830

Kerr, A., Barry, M., & Kelleher, J. D. (2020). Expectations of artificial intelligence and the performativity of ethics: Implications for communication governance. Big Data & Society, 7(1), 2053951720915939. https://journals.sagepub.com/doi/abs/10.1177/2053951720915939

Kieslich, K., Keller, B., & Starke, C. (2022). Artificial intelligence ethics by design. Evaluating public perception on the importance of ethical design principles of artificial intelligence. Big Data & Society, 9(1), 20539517221092956. https://journals.sagepub.com/doi/abs/10.1177/20539517221092956

Mittelstadt, B. D., Allo, P., Taddeo, M., Wachter, S., & Floridi, L. (2019). The ethics of algorithms: Mapping the debate. Big Data & Society, 6(1), 2053951719839315. https://journals.sagepub.com/doi/abs/10.1177/2053951716679679

Moher, D., Liberati, A., Tetzlaff, J., Altman, D. G., & The PRISMA Group (2009). Preferred reporting items for systematic reviews and meta-analyses: The PRISMA statement. PLoS Medicine, 6(7), e1000097. https://www.acpjournals.org/doi/abs/10.7326/0003-4819-151-4-200908180-00135

?ikadimovs, O., & V?vere, V. (2024, junio). THE USE OF GENERATIVE ARTIFICIAL INTELLIGENCE IN HIGHER EDUCATION: UNIVERSITY SOCIAL RESPONSIBILITY AND STAKEHOLDERS’PERCEPTIONS. En ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference (Vol. 2, pp. 226-231). https://journals.ru.lv/index.php/ETR/article/view/8015

Obermeyer, Z., Powers, B., Vogeli, C., & Mullainathan, S. (2019). Dissecting racial bias in an algorithm used to manage the health of populations. Science, 366(6464), 447-453. https://www.science.org/doi/abs/10.1126/science.aax2342

Petticrew, M., & Roberts, H. (2006). Systematic reviews in the social sciences: A practical guide. Blackwell Publishing. https://books.google.es/books?hl=es&lr=&id=ZwZ1_xU3E80C&oi=fnd&pg=PR5&dq=Petticrew,+M.,+%26+Roberts,+H.+(2006).+Systematic+reviews+in+the+social+sciences:+A+practical+guide.+Blackwell+Publishing.&ots=w_Q_xQIULt&sig=wzaboMWCLsVs4M4w3suRp70mdpM

Popay, J., Roberts, H., Sowden, A., Petticrew, M., Arai, L., Rodgers, M., ... & Duffy, S. (2006). Guidance on the conduct of narrative synthesis in systematic reviews. A product from the ESRC methods programme. https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=ed8b23836338f6fdea0cc55e161b0fc5805f9e27

Rosemann, A., & Zhang, X. (2022). Exploring the social, ethical, legal, and responsibility dimensions of artificial intelligence for health-a new column in Intelligent Medicine. Intelligent Medicine, 2(02), 103-109. https://mednexus.org/doi/abs/10.1016/j.imed.2021.12.002

Santoni de Sio, F., & Mecacci, G. (2021). Four responsibility gaps with artificial intelligence: Why they matter and how to address them. Philosophy & Technology, 34(4), 1057-1084. https://link.springer.com/article/10.1007/s13347-021-00450-x

Tambe, P., Cappelli, P., & Yakubovich, V. (2019). Artificial intelligence in human resources management: Challenges and a path forward. California Management Review, 61(4), 15-42. https://journals.sagepub.com/doi/abs/10.1177/0008125619867910

Weber-Lewerenz, B. (2021). Corporate digital responsibility (CDR) in construction engineering—ethical guidelines for the application of digital transformation and artificial intelligence (AI) in user practice. SN Applied Sciences, 3, 1-25. https://link.springer.com/article/10.1007/s42452-021-04776-1

Zaman, B. U. (2024). The weighty responsibility of creating ai navigating control and ethics. https://www.preprints.org/manuscript/202404.1900

Published

2024-02-29

How to Cite

Acevedo Torres, S. I. . (2024). Ethics and Social Responsibility in the Implementation of Artificial Intelligence Systems in the Administration. Business Innova Sciences, 5(1), 35-57. https://doi.org/10.5281/zenodo.13308314