ENGINEERING BLOG
Technical research and engineering insights from the team building the operating system for responsible AI operations.
121 articles · Published by MARIA OS
Defining the mathematical boundary between helpful personalization and harmful manipulation using causal reasoning and responsibility gates
Retail recommendation systems operate between beneficial personalization and potentially manipulative behavior. This paper introduces a causal-inference framework that defines the personalization-manipulation boundary, enabling retail AI agents to operate within explicit ethical constraints while routing boundary violations to human review.
A formal framework for ensuring AI-driven pricing decisions preserve consumer welfare through responsibility gates and counterfactual fairness constraints
Dynamic pricing algorithms optimize revenue in real time, but unconstrained optimization can increase vulnerability and unfair outcomes. This paper introduces a Pricing Responsibility Gate that evaluates each price change against welfare constraints, fairness criteria, and reversibility conditions, so AI pricing can remain within explicit governance boundaries while preserving business value.
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Complete list of all 121 published articles. EN / JA bilingual index.
121 articles
All articles reviewed and approved by the MARIA OS Editorial Pipeline.
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