Glossary
Algorithmic Accountability
The expectation that organizations can explain, justify and remedy the effects of algorithmic systems they use.
Last reviewed 2026-08-22
In plain language
Accountability in this context includes identifying who is responsible, what records exist, how affected people can contest outcomes, and which public bodies can investigate. It is used in civil-society advocacy, public-administration reform and some legislative proposals. Accountability is not achieved by transparency alone; it requires authority, incentives and redress.
Why it matters for AI governance
AI systems can diffuse responsibility across vendors, data providers and public agencies. Accountability language is a way to reconnect automated decisions to institutions that can be held to answer.