The project aims to develop a decentralized infrastructure to observe, audit, and document the systemic effects of large-scale algorithmic deployments, with a focus on transparency, institutional resilience, and socio-economic impact.

It brings together applied research, data governance, and strategic system design to build infrastructures that align technology with human values.

Phase 1: The first phase of the project focuses on developing experimental machine learning models to detect and analyze preliminary systemic effects and biases within existing datasets. This early-stage exploration will provide actionable insights and serve as a foundation for the broader decentralized auditing infrastructure.