A human-centric approach to artificial intelligence: ethical, social and economic challenges
DOI:
https://doi.org/10.61007/QdC.2025.1.295Keywords:
human-centric, bias, governance, sustainability, ethicsAbstract
The article explores a human-centric approach to artificial intelligence (AI), examining its ethical, pedagogical, and social implications through the perceptions of TFA students. The objective is to define guidelines for a sustainable and responsible use of AI that integrates fundamental values, promotes educational and social well- being, and critically addresses the challenges posed by automation.
References
Angwin, J., Larson, J., Mattu, S., & Kirchner, L. (2016). Machine bias: There’s software used across the country to predict future criminals. And it’s biased against blacks. ProPublica.
Bostrom, N. (2018). Superintelligenza: Tendenze, pericoli, strategie (S. Frediani, Trad.). Bollati Boringhieri. (Opera originale pubblicata nel 2014).
Brynjolfsson, E., & McAfee, A. (2014). The Second Machine Age: Work, Progress, and Prosperity in a Time of Brilliant Technologies. W.W. Norton & Company. Coeckelbergh, M. (2020). AI Ethics. MIT Press.
Eubanks, V. (2018). Automating Inequality: How High-Tech Tools Profile, Police, and Punish the Poor. St. Martin’s Press.
European Commission. (2023). White Paper on Artificial Intelligence: A European Approach to Excellence and Trust.
Fjeld, J., Achten, N., Hilligoss, H., Nagy, A. C., & Srikumar, M. (2020). Principled Artificial Intelligence: Mapping Consensus in Ethical and Rights-based Approaches to Principles for AI. Berkman Klein Center Research Publication, (2020-1).
Floridi, L., (2020). The Ethics of Artificial Intelligence: Principles and Practices. Oxford University Press.
Floridi, L., (2022). Etica dell’intelligenza artificiale. Raffaello Cortina.
Hagendorff, T. (2020). The Ethics of AI Ethics: An Evaluation of Guidelines. Minds and Machines, 30(1), 99-120.
Jobin, A., Ienca, M., & Vayena, E. (2020). The Global Landscape of AI Ethics Guidelines. Nature Machine Intelligence, 2(6), 389-399.
Johnson, M., & Verdicchio, M. (2022). AI Literacy and Ethical Challenges in the 21st Century. Cambridge Scholars Publishing.
McKinsey Global Institute. (2022). The Future of Work in the Age of AI.
Mittelstadt, B. D. (2021). Principles Alone Cannot Guarantee Ethical AI. Nature Machine Intelligence, 3(2), 104-110.
OCSE (2021). OECD Employment Outlook 2021: AI and the Future of Work. OECD Publishing. https://doi.org/10.1787/5a700c4b-en
OECD (2023). AI and Digital Transformation: Governance and Responsible AI.
O’Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. New York: Crown.
Russell, S. (2022). Human Compatible: Artificial Intelligence and the Problem of Control. Penguin Books.
Smith, A. (2023). Regulatory Frameworks for a Human-Centric AI. Routledge.
TECH4FUTURE. (2022). Impronta di carbonio e intelligenza artificiale. https://tech4future.info/impronta-di-carbonio-intelligenza-artificiale/ (consultato il 9 novembre 2024).
UNESCO. (2022). Artificial Intelligence in Education: Challenges and Opportunities.
Whittlestone, J., Nyrup, R., Alexandrova, A., & Dihal, K. (2021). The Role and Limits of Principles in AI Ethics: Towards a Focus on Tensions. AI & Society, 36(1), 1-12.
Zeng, Y., Lu, E., & Huangfu, C. (2021). Linking Artificial Intelligence Principles: The Study of Ethics Guidelines, Policy, and Practices. Journal of Business Ethics, 167(4), 645-662.
Zuboff, S. (2019). Il capitalismo della sorveglianza: Il futuro dell’umanità nell’era dei nuovi poteri (P. Bassotti, Trad.). Roma: Luiss University Press.
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Community Notebook. People, Education and Welfare in the Society 5.0

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.