In this episode, Anya and Ben unravel the intricacies of the applicant's project proposal, "The AI Labor Impact Index (ALII)". They discuss how ALII aims to be a dynamic, participatory tool to measure AI's labor impact through equity-centered metrics. Anya and Ben explore the framework's key features: the Automation Risk Score (ARS), Augmentation Potential Score (APS), and Resilience Index (RI), and how these metrics move beyond static models to incorporate real-time technical modeling and worker-centered design. The hosts will highlight ALII's methodology, which bridges technical rigor with participatory depth, including co-creation workshops and ethical guardrails. They will emphasize ALII's potential impact for policymakers, workers, and academia, and its focus on sustainability and data-driven decisions, core tenets of the AISS program.