Crossroads between ethical prompts and human judgment in the era of artificial intelligence
DOI:
https://doi.org/10.47230/unesum-ciencias.v8.n2.2024.4-19Keywords:
Artificial Intelligence, Ethics, Ethical Prompts, Moral Judgment, Decision Making, Contextual Reasoning.Abstract
In the current era of rapid technological advancement, artificial intelligence (AI) has penetrated various aspects of decision-making, including those with significant ethical implications. This study examines the complex relationship between ethical prompts implemented in AI systems and human moral judgment, investigating whether these prompts can effectively replace human ethical decision-making. The main objective is to evaluate the capabilities and limitations of ethical prompts in capturing the complexity of human moral reasoning. The research reveals that ethical prompts have demonstrated effectiveness in situations where ethical rules are clear and well defined, such as in certain aspects of medicine and finance, sometimes matching or surpassing human performance. However, significant limitations were also identified, particularly in complex ethical scenarios that require deep contextual understanding and cognitive flexibility. AI systems guided by ethical prompts showed difficulties in handling subtle variations in moral dilemmas and adapting to different cultural contexts. The research concludes that, while ethical prompts represent an important advance in incorporating ethical considerations into AI systems, they cannot completely replace human judgment in complex ethical decision-making. A hybrid approach that combines the strengths of ethical prompts with continuous human supervision and judgment is suggested as the most promising path to address ethical challenges in the AI era.
Downloads
References
AI Now Institute. (2019). AI Now 2019 Report. New York University. https://ainowinstitute.org/AI_Now_2019_Report.pdf
Awad, E., Dsouza, S., Kim, R., Schulz, J., Henrich, J., Shariff, A., Bonnefon, J. F., & Rahwan, I. (2018). The Moral Machine experiment. Nature, 563(7729), 59-64. https://www.nature.com/articles/s41586-018-0637-6
Bender, E. M., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021). On the dangers of stochastic parrots: Can language models be too big? Proceedings of the 2021 ACM Conference on Fairness, Accountability, and Transparency, 610-623.
Bostrom, N., & Yudkowsky, E. (2014). The ethics of artificial intelligence. The Cambridge Handbook of Artificial Intelligence, 316-334.
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. arXiv preprint arXiv:2005.14165. https://arxiv.org/abs/2005.14165
Cath, C., Wachter, S., Mittelstadt, B., Taddeo, M., & Floridi, L. (2018). Artificial Intelligence and the 'Good Society': the US, EU, and UK approach. Science and Engineering Ethics, 24(2), 505-528. https://link.springer.com/article/10.1007/s11948-017-9901-7
Char, D. S., Shah, N. H., & Magnus, D. (2018). Implementing machine learning in health care—addressing ethical challenges. *New England Journal of Medicine*, 378(11), 981-983. https://www.nejm.org/doi/full/10.1056/NEJMp1714229
Council of Europe. (2022). Artificial intelligence and the administration of justice. https://rm.coe.int/artificial-intelligence-and-the-administration-of-justice/1680a6f5a0
Crawford, K. (2021). Atlas of AI: Power, Politics, and the Planetary Costs of Artificial Intelligence. Yale University Press.
Floridi, L. (2013). The Ethics of Information. Oxford University Press, Reino Unido. https://global.oup.com/academic/product/the-ethics-of-information-9780199641321
Floridi, L. (2019 a). The Ethics of Artificial Intelligence. Oxford University Press. https://global.oup.com/academic/product/the-ethics-of-artificial-intelligence-9780198838159
Floridi, L., & Cowls, J. (2019 b). A Unified Framework of Five Principles for AI in Society. Harvard Data Science Review, 1(1). https://hdsr.mitpress.mit.edu/pub/l0jsh9d1/release/7
Greene, J. D., Sommerville, R. B., Nystrom, L. E., Darley, J. M., & Cohen, J. D. (2021). An fMRI investigation of emotional engagement in moral judgment. Science, 293(5537), 2105-2108.
Hagendorff, T. (2020). The ethics of AI ethics: An evaluation of guidelines. Minds and Machines, 30(1), 99-120.
Jiang, J., He, D., & Allan, J. (2021). Comparing bayesian and frequentist measures of uncertainty in neural networks. arXiv preprint arXiv:2101.11582. https://arxiv.org/abs/2101.11582
Jonas, H. (1979). El principio de responsabilidad: ensayo de una ética para la civilización tecnológica. Herder Editorial.
Kleinberg, J., Ludwig, J., Mullainathan, S., & Rambachan, A. (2018). Algorithmic Fairness. AEA Papers and Proceedings, 108, 22-27. https://www.aeaweb.org/articles?id=10.1257/pandp.20181018
Li, X., Xu, B., Goodman, K. E., Schatz, B. R., & Zhang, Y. (2022). Artificial intelligence and machine learning in clinical research: A systematic review. Journal of Medical Internet Research, 24(1), e32344. https://www.jmir.org/2022/1/e32344/
Meta. (2022). Community Standards Enforcement Report. https://transparency.fb.com/data/community-standards-enforcement/
Mittelstadt, B. (2019). Principles alone cannot guarantee ethical AI. Nature Machine Intelligence, 1, 501-507. https://www.nature.com/articles/s42256-019-0114-4
Nissenbaum, H. (2010). Privacy in Context: Technology, Policy, and the Integrity of Social Life. Stanford University Press.
O'Neil, C. (2016). Weapons of Math Destruction: How Big Data Increases Inequality and Threatens Democracy. Crown.
Ord, T. (2020). The Precipice: Existential Risk and the Future of Humanity. Hachette Books. https://www.hachettebookgroup.com/titles/toby-ord/the-precipice/9780316484916/
ProPublica. (2016). Machine Bias. https://www.propublica.org/article/machine-bias-risk-assessments-in-criminal-sentencing
Russell, S. (2019). Human Compatible: Artificial Intelligence and the Problem of Control. Viking, EE.UU. https://www.penguinrandomhouse.com/books/566677/human-compatible-by-stuart-russell/
Singer, P. (2021). Ethics in the Real World: 82 Brief Essays on Things That Matter. Princeton University Press, EE.UU. https://press.princeton.edu/books/paperback/9780691178479/ethics-in-the-real-world
TechTarget. (2023). Transparency in AI. https://www.techtarget.com/
Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44-56. https://www.nature.com/articles/s41591-018-0300-7
UNESCO. (2021). Recommendation on the ethics of artificial intelligence. https://unesdoc.unesco.org/ark:/48223/pf0000380455
Wallach, W., & Allen, C. (2009). Moral Machines: Teaching Robots Right from Wrong. Oxford University Press, EE.UU. https://global.oup.com/academic/product/moral-machines-9780195374049
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Mario González Arencibia
This work is licensed under a Creative Commons Attribution 4.0 International License.