SCOR: A Framework for Responsible AI Innovation in Digital Ecosystems
This addresses the problem of fragmented ethical oversight for stakeholders like technology firms and regulators in digital ecosystems, presenting a replicable but incremental approach.
The paper tackles the lack of cohesive ethical governance in AI-driven digital ecosystems by proposing the SCOR framework, which embeds accountability, fairness, and inclusivity through four pillars, offering practical guidance and mixed-method KPIs for implementation.
AI-driven digital ecosystems span diverse stakeholders including technology firms, regulators, accelerators and civil society, yet often lack cohesive ethical governance. This paper proposes a four-pillar framework (SCOR) to embed accountability, fairness, and inclusivity across such multi-actor networks. Leveraging a design science approach, we develop a Shared Ethical Charter(S), structured Co-Design and Stakeholder Engagement protocols(C), a system of Continuous Oversight and Learning(O), and Adaptive Regulatory Alignment strategies(R). Each component includes practical guidance, from lite modules for resource-constrained start-ups to in-depth auditing systems for larger consortia. Through illustrative vignettes in healthcare, finance, and smart city contexts, we demonstrate how the framework can harmonize organizational culture, leadership incentives, and cross-jurisdictional compliance. Our mixed-method KPI design further ensures that quantitative targets are complemented by qualitative assessments of user trust and cultural change. By uniting ethical principles with scalable operational structures, this paper offers a replicable pathway toward responsible AI innovation in complex digital ecosystems.