TY - GEN
T1 - A Blockchain-Based Approach for Model Card Accountability and Regulatory Compliance
AU - Lohachab, Ankur
AU - Urovi, Visara
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - This paper introduces an approach that utilizes smart contracts to facilitate the trustworthy sharing and management of Machine Learning (ML) and Artificial Intelligence (AI) models, as described using model cards. To this end, the proposed approach incorporates Account Abstraction for authentication, enabling role-based access control. This control allows stakeholders to share, track, and validate model cards transparently and securely while tailoring visibility and interaction to preserve privacy in accordance with each role’s privileges. The approach further delineates the conceptualization and lifecycle management of model cards, spanning from creation to deprecation, all within a blockchain-based framework. Additionally, the paper discusses the state parameterization of model cards, formalizing the operational dynamics and constraints associated with each phase of their progression. The proof of concept, implemented to evaluate our approach, suggests that it is capable of effectively capturing and maintaining an immutable record of the various states of model cards, thereby providing a robust and verifiable trail. Overall, our approach is designed to ensure the integrity of model cards and establish accountability, thereby strengthening trust among stakeholders, particularly those relying on AI and ML models as described in model cards.
AB - This paper introduces an approach that utilizes smart contracts to facilitate the trustworthy sharing and management of Machine Learning (ML) and Artificial Intelligence (AI) models, as described using model cards. To this end, the proposed approach incorporates Account Abstraction for authentication, enabling role-based access control. This control allows stakeholders to share, track, and validate model cards transparently and securely while tailoring visibility and interaction to preserve privacy in accordance with each role’s privileges. The approach further delineates the conceptualization and lifecycle management of model cards, spanning from creation to deprecation, all within a blockchain-based framework. Additionally, the paper discusses the state parameterization of model cards, formalizing the operational dynamics and constraints associated with each phase of their progression. The proof of concept, implemented to evaluate our approach, suggests that it is capable of effectively capturing and maintaining an immutable record of the various states of model cards, thereby providing a robust and verifiable trail. Overall, our approach is designed to ensure the integrity of model cards and establish accountability, thereby strengthening trust among stakeholders, particularly those relying on AI and ML models as described in model cards.
KW - Account Abstraction
KW - AI and ML Model Provenance
KW - Blockchain Technology
KW - Decentralized Trust in AI
KW - Model Card
KW - Non-Fungible Tokens (NFTs)
KW - Smart Wallet
U2 - 10.1007/978-3-031-61003-5_4
DO - 10.1007/978-3-031-61003-5_4
M3 - Conference article in proceeding
SN - 9783031610028
VL - 521
T3 - Lecture Notes in Business Information Processing
SP - 37
EP - 48
BT - Advanced Information Systems Engineering Workshops - CAiSE 2024 International Workshops, 2024, Proceedings
A2 - Almeida, João Paulo A.
A2 - Di Ciccio, Claudio
A2 - Kalloniatis, Christos
PB - Springer Verlag
T2 - International workshops associated with the 36th International Conference on Advanced Information Systems Engineering, CAiSE 2024
Y2 - 3 June 2024 through 7 June 2024
ER -