Towards a Framework for Operationalizing the Specification of Trustworthy AI Requirements

• URL: http://arxiv.org/abs/2507.10228v1
• Date: Mon, 14 Jul 2025 12:49:26 GMT
• Title: Towards a Framework for Operationalizing the Specification of Trustworthy AI Requirements
• Authors: Hugo Villamizar, Daniel Mendez, Marcos Kalinowski,
• Abstract summary: Growing concerns around the trustworthiness of AI-enabled systems highlight the role of requirements engineering (RE)<n>We propose the integration of two complementary approaches: AMDiRE and PerSpecML.
• Score: 1.2184324428571227
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Growing concerns around the trustworthiness of AI-enabled systems highlight the role of requirements engineering (RE) in addressing emergent, context-dependent properties that are difficult to specify without structured approaches. In this short vision paper, we propose the integration of two complementary approaches: AMDiRE, an artefact-based approach for RE, and PerSpecML, a perspective-based method designed to support the elicitation, analysis, and specification of machine learning (ML)-enabled systems. AMDiRE provides a structured, artefact-centric, process-agnostic methodology and templates that promote consistency and traceability in the results; however, it is primarily oriented toward deterministic systems. PerSpecML, in turn, introduces multi-perspective guidance to uncover concerns arising from the data-driven and non-deterministic behavior of ML-enabled systems. We envision a pathway to operationalize trustworthiness-related requirements, bridging stakeholder-driven concerns and structured artefact models. We conclude by outlining key research directions and open challenges to be discussed with the RE community.

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