Cited by 524Ethics and Social Impacts of AIEthics in Business and EducationDigitalization, Law, and Regulation

Translating Principles into Practices of Digital Ethics: Five Risks of Being Unethical

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Floridi, Luciano·2019·Philosophy & Technology

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Crossref · 10.1007/s13347-019-00354-x

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  • Ethical challenges include concerns about bias, opacity, and data privacy, particularly in contexts where student data are increasingly used for analytics and monitoring.

    “Ethical challenges include concerns about bias, opacity, and data privacy, particularly in contexts where student data are increasingly used for analytics and monitoring (Ayyoub et al., 2025;Floridi, 2019).”

    From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Floridi, 2019

    Section 5 (Ethics Dumping; page not provided) raises a personal-data protection concern, and Section 6 (Ethics Shirking; page not provided) discusses bias. Section 3 (Ethics Bluewashing; page not provided) calls for transparency about ethical practices, but does not specifically address algorithmic opacity. The copy does not discuss student data, learning analytics, or monitoring, so it does not support that context. (LLM, conf=0.84)

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  • Concerns related to algorithmic bias, data privacy, and transparency are well documented, particularly in relation to vulnerable populations such as children.

    “Concerns related to algorithmic bias, data privacy, and transparency are well documented, particularly in relation to vulnerable populations such as children (Floridi, 2019;Jobin et al., 2019).”

    From Teachers' Experiences with AI in K–12 Education: Opportunities and Challenges (2026) · cites this paper as Floridi, 2019

    Section 5 (Ethics Dumping) describes a risk to personal-data protection when algorithms are trained under weaker safeguards, and Section 3 (Ethics Bluewashing) calls for transparency about AI practices. The paper does not document algorithmic bias or identify children or other vulnerable populations as particularly affected; its mention of bias in Section 6 concerns moral double standards, not algorithms. Page numbers are unavailable in our copy. (LLM, conf=0.86)

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Research works printed but not linked: 6

  1. 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.
  2. Floridi, L. (2015). The ethics of information. Oxford: Oxford University Press.
  3. De Franceschi, R. Schulze, M. Graziadei, O. Pollicino, F. Riente, S. Sica and P. Sirena. SSRN: https://ssrn.com/abstract=3369266.
  4. Nordling, L. (2018). Europe's biggest research fund cracks down on Bethics dumping^. Nature, 559(7712), 17.
  5. Samuel, A. L. (1960). Some moral and technical consequences of automation-a refutation. Science, 132(3429), 741-742.
  6. Wiener, N. (1960). Some moral and technical consequences of automation. Science, 131(3410), 1355-1358.

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Authors
Floridi, L.
Affiliations
University of Oxford (GB)
Corresponding author
Floridi, Luciano
Venue
Philosophy & Technology
Published
2019-05-23
Volume
32
Issue
2
Pages
185-193
ISSN
  • 2210-5433 (ISSN-L)
  • 2210-5441
OpenAlex
W2944988415
Cited by
524
References
0
Citations by year
2026: 93 · 2025: 99 · 2024: 95 · 2023: 85 · 2022: 57 · 2021: 52 · 2020: 39 · 2019: 4
FWCI
66.48
Type
journal article
Language
en
Open access
Locations
  • Philosophy & Technology (publishedVersion)
  • PhilPapers (PhilPapers Foundation) (submittedVersion)
Topics
  • Social Sciences › Safety Research › Ethics and Social Impacts of AI
  • Social Sciences › Decision Sciences › Information Systems and Management › Ethics in Business and Education
  • Social Sciences › Law › Digitalization, Law, and Regulation
Keywords
digital ethics, ethical principles, unethical practices, AI ethics, online services

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