# Macro Ethics Principles for Responsible AI Systems: Taxonomy and Future Directions

arXiv: https://arxiv.org/abs/2208.12616 · HTML: https://mlsanity.com/paper/2208.12616/

## Key facts

- Cited by 7 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Aug 2022.

## Built on by (most cited first, 7 of 7)

- [A Framework for Responsible AI Systems: Building Societal Trust through Domain Definition, Trustworthy AI Design, Auditability, Accountability, and Governance](https://mlsanity.com/paper/2503.04739/) (2025)
- [Artificial Intelligence for Collective Intelligence: A National-Scale Research Strategy](https://mlsanity.com/paper/2411.06211/) (2024)
- [Value-Based Rationales Improve Social Experience: A Multiagent Simulation Study](https://mlsanity.com/paper/2408.02117/) (2024)
- [Operationalising Rawlsian Ethics for Fairness in Norm-Learning Agents](https://mlsanity.com/paper/2412.15163/) (2024)
- [Towards the Formalization of a Trustworthy AI for Mining Interpretable Models explOiting Sophisticated Algorithms](https://mlsanity.com/paper/2510.20621/) (2025)
- [Ethic-BERT: An Enhanced Deep Learning Model for Ethical and Non-Ethical Content Classification](https://mlsanity.com/paper/2510.12850/) (2025)
- [What We Know about Responsible AI Practices in Industry: A Half Decade of Empirical Research](https://mlsanity.com/paper/2608.10431/) (2026)

## Abstract (arXiv)

Responsible AI must be able to make or support decisions that consider human values and can be justified by human morals. Accommodating values and morals in responsible decision making is supported by adopting a perspective of macro ethics, which views ethics through a holistic lens incorporating social context. Normative ethical principles inferred from philosophy can be used to methodically reason about ethics and make ethical judgements in specific contexts. Operationalising normative ethical principles thus promotes responsible reasoning under the perspective of macro ethics. We survey AI and computer science literature and develop a taxonomy of 21 normative ethical principles which can be operationalised in AI. We describe how each principle has previously been operationalised, highlighting key themes that AI practitioners seeking to implement ethical principles should be aware of. We envision that this taxonomy will facilitate the development of methodologies to incorporate normative ethical principles in reasoning capacities of responsible AI systems.