# Responsible Artificial Intelligence -- from Principles to Practice

arXiv: https://arxiv.org/abs/2205.10785 · HTML: https://mlsanity.com/paper/2205.10785/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 10 references that are in the map.
- First posted on arXiv 22 May 2022.

## Builds on (most cited first, 2 of 2)

- [The Next Decade in AI: Four Steps Towards Robust Artificial Intelligence](https://mlsanity.com/paper/2002.06177/) (2020)
- [Artificial Intelligence: the global landscape of ethics guidelines](https://mlsanity.com/paper/1906.11668/) (2019)

## Built on by (most cited first, 6 of 6)

- [Secret Use of Large Language Model (LLM)](https://mlsanity.com/paper/2409.19450/) (2024)
- [Trustworthy and Responsible AI for Human-Centric Autonomous Decision-Making Systems](https://mlsanity.com/paper/2408.15550/) (2024)
- [Trustworthy, responsible, ethical AI in manufacturing and supply chains: synthesis and emerging research questions](https://mlsanity.com/paper/2305.11581/) (2023)
- [Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences (October 2025 -- Version 2)](https://mlsanity.com/paper/2505.16619/) (2025)
- [Responsible AI: Portraits with Intelligent Bibliometrics](https://mlsanity.com/paper/2405.02846/) (2024)
- [FAIRTOPIA: Envisioning Multi-Agent Guardianship for Disrupting Unfair AI Pipelines](https://mlsanity.com/paper/2506.09107/) (2025)

## Abstract (arXiv)

The impact of Artificial Intelligence does not depend only on fundamental research and technological developments, but for a large part on how these systems are introduced into society and used in everyday situations. AI is changing the way we work, live and solve challenges but concerns about fairness, transparency or privacy are also growing. Ensuring responsible, ethical AI is more than designing systems whose result can be trusted. It is about the way we design them, why we design them, and who is involved in designing them. In order to develop and use AI responsibly, we need to work towards technical, societal, institutional and legal methods and tools which provide concrete support to AI practitioners, as well as awareness and training to enable participation of all, to ensure the alignment of AI systems with our societies' principles and values.