Taiwo et al. 2023

Full Title: A Review of the Ethics of Artificial Intelligence and its Applications in the United States

Citation: Taiwo, E., Akinsola, A., Tella, E., Makinde, K., & Akinwande, M. (2023). A Review of the Ethics of Artificial Intelligence and its Applications in the United States. arXiv preprint arXiv:2310.05751.

Core Framing

A comprehensive review that synthesizes AI ethics principles and their application across US sectors (business, government, academia, civil society). The paper draws on a 2019 meta-review identifying 11 fundamental ethical principles and consolidates them into seven operational themes aligned with Deloitte’s Trustworthy AI™ framework.

Key Contribution

Maps the landscape of AI ethics principles and attempts to bridge the gap between high-level values and engineering practice. Positions the discussion explicitly in a US context, acknowledging sector-specific dependencies on AI.

Eleven Principles Identified

  1. Transparency
  2. Justice
  3. Fairness
  4. Equity
  5. Non-Maleficence
  6. Responsibility
  7. Accountability
  8. Privacy
  9. Beneficence
  10. Freedom/Autonomy
  11. Trust/Dignity/Sustainability/Solidarity

Seven Operational Themes

Consolidated into actionable engineering-adjacent concerns:

  1. Human agency and oversight
  2. Safety
  3. Privacy
  4. Transparency
  5. Fairness
  6. Accountability
  7. Technical robustness

Extracted Content

Notes

The framing reveals more than the findings. The fact that a review paper is needed to consolidate 11+ overlapping principles into 7 themes suggests the field is still in definitional flux. The reliance on bioethics foundations (beneficence, non-maleficence, autonomy, justice from the Belmont Report) is both strength and limitation, these concepts were developed for human research contexts, not autonomous systems.