SCOR: A Framework for Responsible AI Innovation in Digital Ecosystems
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Abstract (arXiv)
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.
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References · 5
- 2019Understanding artificial intelligence ethics and safetycited by 68
- 2023Diversity and Inclusion in Artificial Intelligencecited by 14
- 2023Stronger Together: on the Articulation of Ethical Charters, Legal Tools, and Technical Documentation in MLcited by 9
- 2022Putting AI Ethics into Practice: The Hourglass Model of Organizational AI Governancecited by 7
- 2025Emerging Practices in Participatory AI Design in Public Sector Innovationcited by 1
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