Crossing the principle-practice gap in AI ethics with ethical problem-solving

The "principle-practice gap" is a real problem in AI ethics: The paper identifies a significant disconnect between ethical principles that AI developers discuss and the actual technical implementations in AI systems, suggesting that good intentions alone are insufficient without concrete methodologies to translate them into practice.

Ethical Problem-Solving (EPS) offers a practical bridge: The framework proposes using impact assessment surveys and differential recommendation methods to convert abstract ethical principles into actionable steps during AI development, making ethics a tangible part of the technical process rather than an afterthought.

Ethics should be integrated as a service, not an add-on: The paper proposes an "Ethics as a Service Platform" concept, suggesting that ethical considerations need to be embedded throughout AI development workflows rather than treated as separate compliance checkpoints, similar to how other technical services are integrated into development pipelines.

Human-centric values must guide AI development decisions: The framework emphasizes that responsible AI development should be "human-centric and value-oriented," implying that technical choices should be explicitly evaluated against their impact on human welfare and societal values, not just performance metrics.

Open-source implementation encourages broader adoption: By releasing all framework components openly with permissive licensing, the authors are attempting to democratize responsible AI practices, suggesting that solutions to ethical challenges are more likely to scale when shared openly with the broader AI community.