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arXiv · 2508.20040

Model Science: getting serious about verification, explanation and control of AI systems

Przemyslaw Biecek·Wojciech Samek
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Abstract

The growing adoption of foundation models calls for a paradigm shift from Data Science to Model Science. Unlike data-centric approaches, Model Science places the trained model at the core of analysis, aiming to interact, verify, explain, and control its behavior across diverse operational contexts. This paper introduces a conceptual framework for a new discipline called Model Science, along with the proposal for its four key pillars: Verification, which requires strict, context-aware evaluation protocols; Explanation, which is understood as various approaches to explore of internal model operations; Control, which integrates alignment techniques to steer model behavior; and Interface, which develops interactive and visual explanation tools to improve human calibration and decision-making. The proposed framework aims to guide the development of credible, safe, and human-aligned AI systems.

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Przemyslaw Biecek, Wojciech Samek. 2025-08-27. Model Science: getting serious about verification, explanation and control of AI systems. https://arxiv.org/abs/2508.20040

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