As algorithmic decision-making expands into high-stakes domains, the ability to examine and challenge biased outcomes becomes essential. EthosBIAS is designed to support accountability by bringing structure, clarity, and evidence to how automated systems influence real-world determinations.
EthosBIAS™ is a conceptual litigation-support initiative designed to examine and challenge bias embedded in algorithmic decision-making.
While EthosGuard focuses on preventing misuse, EthosBIAS turns the lens inward to help surface, document, and contextualize patterns of algorithmic behavior that may lead to harmful or inequitable outcomes. Designed to support legal accountability, EthosBIAS brings structure and clarity to how automated systems influence real-world determinations.
