Trustworthy AI for Good (AI4GOOD) Workshop
Abstract
As agentic AI systems move from benchmarks into public-facing workflows, trustworthy AI must go beyond model-level security and isolated safety checks. The central challenge is whether advanced AI systems can produce measurable public benefit across populations while mitigating systemic risks such as power concentration, unequal access, accountability gaps, and dependence on a small number of AI providers and institutions. This workshop brings together the science of trustworthy AI, AI safety, AI for social good, and AI policy/governance communities to connect technical progress in evaluation, robustness, alignment, monitoring, interpretability, and human oversight with responsible deployment in public-interest settings. We focus on applications aligned with the United Nations Sustainable Development Goals, including health, education, climate action, humanitarian response, accessibility, reduced inequalities, and inclusive public services. Through invited talks, contributed presentations, posters, and a cross-sector panel, the workshop aims to build a shared research agenda for AI systems that are safer, more accountable, and more beneficial at societal scale.