Journal Article

Trust by Design: An Ethical Framework for Collaborative Intelligence Systems in Industry 5.0

Merchán-Cruz, Emmanuel A., Aragón-Camarasa, Gerardo, Gabelaia, Ioseb, Soe, Shwe, Hansen, Mark F., Savrasovs, Mihails, Rodriguez-Cañizo, Ricardo G.

2025

Overview

Industry 5.0 highlights human-centricity, sustainability, and resilience. This article presents a novel Trust by Design framework applicable to collaborative intelligence systems within Industry 5.0, addressing the need for collaborative systems to be reliable by design, incorporating ethical principles such as transparency, accountability, fairness, and privacy throughout the entire system lifecycle. The framework is grounded in select ethical philosophies applied to practical design requirements for human-AI collaboration, identifying key ethical challenges that threaten to damage trust and restrict the adoption of collaborative systems. The authors employ a qualitative, literature-driven method, conceptual modeling, and scenario-based case study analysis, synthesizing best practices and ethical policies from the EU AI Act, GDPR, and more. Trust by Design suggests a structured set of principles and implementation measures to embed ethics into every phase of the system’s lifecycle. The applicability and suitability of the framework are demonstrated through representative real-world application scenarios across industries. The results indicate that trust in collaborative intelligence systems is not static but dynamic, context-dependent, and controlled by transparency, fairness, and user experience. The framework includes instruments and methods to measure ethical performance, including trust metrics, override rates, fairness indicators, and incident tracking.

• Publisher: MDPI AG
• Subject: Artificial intelligence / Automation / Best practice / Case studies / Collaboration / Ethics / Industry 5.0 / Intelligence / Philosophy / Privacy / Productivity / Qualitative analysis / Sustainability / User experience