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Ethics Readiness of Artificial Intelligence: A Practical Evaluation Method

arXiv 2512.09729 ↗First posted 10 Dec 2025cs.CY cs.AIcited by 0

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Abstract (arXiv)

We present Ethics Readiness Levels (ERLs), a four-level, iterative method to track how ethical reflection is implemented in the design of AI systems. ERLs bridge high-level ethical principles and everyday engineering by turning ethical values into concrete prompts, checks, and controls within real use cases. The evaluation is conducted using a dynamic, tree-like questionnaire built from context-specific indicators, ensuring relevance to the technology and application domain. Beyond being a managerial tool, ERLs help facilitate a structured dialogue between ethics experts and technical teams, while our scoring system helps track progress over time. We demonstrate the methodology through two case studies: an AI facial sketch generator for law enforcement and a collaborative industrial robot. The ERL tool effectively catalyzes concrete design changes and promotes a shift from narrow technological solutionism to a more reflective, ethics-by-design mindset.

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References · 4

  1. 2019The Ethics of AI Ethics -- An Evaluation of Guidelinescited by 129
  2. 2023Specific versus General Principles for Constitutional AIcited by 47
  3. 2020Technology Readiness Levels for AI & MLcited by 30
  4. 2025Ethics Readiness of Technology: The case for aligning ethical approaches with technological maturitycited by 1

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