Topics
The editorial pillars of Equity & AI. Each represents a lens through which we examine artificial intelligence as infrastructure: governance, accountability, access, institutional power, and public trust.
Algorithmic Accountability
How power, bias, and responsibility show up in algorithmic systems. From hiring tools to healthcare models, we examine who is harmed, who benefits, and who can demand an account.
AI Governance
The laws, standards, procurement choices, and institutional practices shaping how AI is developed, deployed, audited, and contested.
Digital Divide
Access, connectivity, infrastructure, affordability, and the right to participate in the systems that increasingly shape economic and civic life.
Public Trust
The conditions under which institutions can earn trust when AI enters public agencies, healthcare, disaster response, and community life.
Education
AI in classrooms, learning equity, student data, and what it means to teach critical judgment about systems that will shape public and private life.
Labor & Workforce
Automation, workplace surveillance, displacement, skills, and bargaining power as AI changes how labor is managed, measured, and valued.
Healthcare Equity
Algorithms in medicine, triage, and insurance. When AI enters healthcare, whose outcomes improve — and whose are overlooked?
Responsible Innovation
The design, safety, governance, and accountability practices that should accompany AI development when systems move from laboratories into institutions.