# Privacy in Responsible AI: Approaches to Facial Recognition from Cloud Providers

arXiv: https://arxiv.org/abs/2503.04866 · HTML: https://mlsanity.com/paper/2503.04866/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 47 references that are in the map.
- First posted on arXiv 6 Mar 2025.

## Builds on (most cited first, 3 of 3)

- [Connecting the Dots in Trustworthy Artificial Intelligence: From AI Principles, Ethics, and Key Requirements to Responsible AI Systems and Regulation](https://mlsanity.com/paper/2305.02231/) (2023)
- [Socially Responsible AI Algorithms: Issues, Purposes, and Challenges](https://mlsanity.com/paper/2101.02032/) (2021)
- [Responsible AI Pattern Catalogue: A Collection of Best Practices for AI Governance and Engineering](https://mlsanity.com/paper/2209.04963/) (2022)

## Abstract (arXiv)

As the use of facial recognition technology is expanding in different domains, ensuring its responsible use is gaining more importance. This paper conducts a comprehensive literature review of existing studies on facial recognition technology from the perspective of privacy, which is one of the key Responsible AI principles. Cloud providers, such as Microsoft, AWS, and Google, are at the forefront of delivering facial-related technology services, but their approaches to responsible use of these technologies vary significantly. This paper compares how these cloud giants implement the privacy principle into their facial recognition and detection services. By analysing their approaches, it identifies both common practices and notable differences. The results of this research will be valuable for developers and businesses by providing them insights into best practices of three major companies for integration responsible AI, particularly privacy, into their cloud-based facial recognition technologies.