# Blockchain As a Platform For Artificial Intelligence (AI) Transparency

arXiv: https://arxiv.org/abs/2503.08699 · HTML: https://mlsanity.com/paper/2503.08699/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 36 references that are in the map.
- First posted on arXiv 7 Mar 2025.

## Builds on (most cited first, 7 of 7)

- [Concrete Problems in AI Safety](https://mlsanity.com/paper/1606.06565/) (2016)
- [Towards A Rigorous Science of Interpretable Machine Learning](https://mlsanity.com/paper/1702.08608/) (2017)
- [European Union regulations on algorithmic decision-making and a "right to explanation"](https://mlsanity.com/paper/1606.08813/) (2016)
- [Blockchain for Internet of Things: A Survey](https://mlsanity.com/paper/1906.00245/) (2019)
- [A Review on the Use of Blockchain for the Internet of Things](https://mlsanity.com/paper/2402.00687/) (2024)
- [Blockchain and Artificial Intelligence](https://mlsanity.com/paper/1802.04451/) (2018)
- [Enhancing Data Integrity and Traceability in Industry Cyber Physical Systems (ICPS) through Blockchain Technology: A Comprehensive Approach](https://mlsanity.com/paper/2405.04837/) (2024)

## Abstract (arXiv)

As artificial intelligence (AI) systems become increasingly complex and autonomous, concerns over transparency and accountability have intensified. The "black box" problem in AI decision-making limits stakeholders' ability to understand, trust, and verify outcomes, particularly in high-stakes sectors such as healthcare, finance, and autonomous systems. Blockchain technology, with its decentralized, immutable, and transparent characteristics, presents a potential solution to enhance AI transparency and auditability. This paper explores the integration of blockchain with AI to improve decision traceability, data provenance, and model accountability. By leveraging blockchain as an immutable record-keeping system, AI decision-making can become more interpretable, fostering trust among users and regulatory compliance. However, challenges such as scalability, integration complexity, and computational overhead must be addressed to fully realize this synergy. This study discusses existing research, proposes a framework for blockchain-enhanced AI transparency, and highlights practical applications, benefits, and limitations. The findings suggest that blockchain could be a foundational technology for ensuring AI systems remain accountable, ethical, and aligned with regulatory standards.