# Linking Artificial Intelligence Principles

arXiv: https://arxiv.org/abs/1812.04814 · HTML: https://mlsanity.com/paper/1812.04814/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Dec 2018.

## Built on by (most cited first, 8 of 8)

- [Worldwide AI Ethics: a review of 200 guidelines and recommendations for AI governance](https://mlsanity.com/paper/2206.11922/) (2022)
- [A Survey of the Evolution of Language Model-Based Dialogue Systems: Data, Task and Models](https://mlsanity.com/paper/2311.16789/) (2023)
- [Evaluating Large Language Models with Psychometrics](https://mlsanity.com/paper/2406.17675/) (2024)
- [How Good Is NLP? A Sober Look at NLP Tasks through the Lens of Social Impact](https://mlsanity.com/paper/2106.02359/) (2021)
- [Bridging Ethical Principles and Algorithmic Methods: An Alternative Approach for Assessing Trustworthiness in AI Systems](https://mlsanity.com/paper/2506.22774/) (2025)
- [Fairness: from the ethical principle to the practice of Machine Learning development as an ongoing agreement with stakeholders](https://mlsanity.com/paper/2304.06031/) (2023)
- [Towards a Feminist Metaethics of AI](https://mlsanity.com/paper/2311.14700/) (2023)
- [A Critical Analysis of Trustworthy AI Tools, Mark Frameworks, and the Implementation Chasms](https://mlsanity.com/paper/2607.15480/) (2026)

## Abstract (arXiv)

Artificial Intelligence principles define social and ethical considerations to develop future AI. They come from research institutes, government organizations and industries. All versions of AI principles are with different considerations covering different perspectives and making different emphasis. None of them can be considered as complete and can cover the rest AI principle proposals. Here we introduce LAIP, an effort and platform for linking and analyzing different Artificial Intelligence Principles. We want to explicitly establish the common topics and links among AI Principles proposed by different organizations and investigate on their uniqueness. Based on these efforts, for the long-term future of AI, instead of directly adopting any of the AI principles, we argue for the necessity of incorporating various AI Principles into a comprehensive framework and focusing on how they can interact and complete each other.