AI Supply Chain Transparency & Collaboration
It Was a Black Box
This case study explores the consequences of adopting AI systems in education without sufficient understanding of how they work—or where the data comes from. The fictionalised but research-informed scenario follows a school system that implemented a predictive analytics tool to support student interventions. Despite widespread use, no one on staff understood how the model made its decisions, what data it used, or whether the data was ethically sourced. When harm emerged, the lack of transparency made it impossible to respond effectively. This case highlights the need for model explainability, data literacy, and procurement due diligence across all educational AI use.
We Signed Before We Asked
Behind Closed Algorithms
This case study explores the risks educational institutions face when AI tools are procured from third-party vendors without sufficient due diligence or safeguards. The fictionalised scenario follows a school district that purchased an AI learning analytics platform with limited understanding of the tool’s functionality, data handling practices, or alignment with educational values. When privacy concerns and algorithmic bias emerged, the lack of contractual protections or accountability clauses left the district exposed. This case highlights the importance of proactive vendor engagement, clear risk management strategies, and education-specific procurement protocols when working with AI providers.
This case study explores the consequences of siloed decision-making in AI adoption and the missed opportunities that arise when educational institutions fail to collaborate openly on AI safety and ethics. In this fictionalised scenario, a university deployed a suite of AI tools across its student services and academic platforms without consulting students, staff, or external experts. When problems emerged, there was no shared understanding—or shared solution. The case highlights the need for cross-sector collaboration, participatory design, and open dialogue to ensure AI systems in education are not only technically effective, but socially responsible.