Utilizing SBOM for Transparent AI Risk Communication

Value chains for AI systems are becoming increasingly complex and can consists of multiple actors that contribute services, tools, data, models and code. An efficient risk management along this value chain requires all actors to communicate potential risk sources and recommendations for mitigation. The Software Bill of Materials (SBOM) is a method from cybersecurity, that enables organizations to communicate information like licences, security vulnerabilities and dependencies of software components. SBOM raises increasing interest in the AI community to share information about AI components, like data and models. In this paper we discuss the suitability of SBOM for AI risk management along a value chain and show the potential but also gaps in current approaches.

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Publication Details

Journal
Proceedings of the AAAI Symposium Series
Published
2025-11-23
DOI
https://doi.org/10.1609/aaaiss.v7i1.36885
Primary Topic
Ethics and Social Impacts of AI
Type
article
Field-Weighted Citation Impact
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article

Utilizing SBOM for Transparent AI Risk Communication

Proceedings of the AAAI Symposium Series
Ethics and Social Impacts of AI
article

Utilizing SBOM for Transparent AI Risk Communication

article en

Abstract

Value chains for AI systems are becoming increasingly complex and can consists of multiple actors that contribute services, tools, data, models and code. An efficient risk management along this value chain requires all actors to communicate potential risk sources and recommendations for mitigation. The Software Bill of Materials (SBOM) is a method from cybersecurity, that enables organizations to communicate information like licences, security vulnerabilities and dependencies of software components. SBOM raises increasing interest in the AI community to share information about AI components, like data and models. In this paper we discuss the suitability of SBOM for AI risk management along a value chain and show the potential but also gaps in current approaches.

Proceedings of the AAAI Symposium SeriesVol. 7(1)
Machine Intelligence Research Institute (US), Fraunhofer Institute for Intelligent Analysis and Information Systems (DE)
Peace, Justice and strong institutions
Openalex Percentile: Top 38%
Ethics and Social Impacts of AI
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