Algorithmic accountability refers to the allocation of responsibility for the consequences of real-world actions influenced by algorithms used in decision-making processes.

May 24, 2023 · Algorithmic accountability focuses on the question of who takes the obligation to justify the design, use, and outcome of machine learning systems and who assumes responsibility for the …

Dec 9, 2025 · About this toolkit This toolkit is designed for anyone looking to investigate and challenge the use of algorithmic systems in the public sector. It aims to synthesize the learnings of Amnesty …

Although AI algorithmic decision-making is an especially challenging case, the account of accountability presented here applies broadly to AI and non-AI algorithmic decision-making.

The following discussion surveys some of the accountability deficits exposed by the spreading adoption of algorithms. It considers four areas in which significant concerns are raised by the lack of …

What is Algorithmic Accountability? Algorithmic accountability ultimately refers to the assignment of responsibility for how an algorithm is created and its impact on society; if harm occurs, accountable …

Feb 23, 2023 · What is Algorithmic Accountability? Algorithmic accountability is the idea that those designing, procuring, and using flawed algorithms should be held responsible for their actions and …

May 24, 2023 · This alignment demonstrates the relevance of cluster C, making accountability in the context of AI particularly relevant in this sense (i.e., societal, moral, and consequences).

Apr 11, 2023 · Despite unresolved concerns, an audit-centered algorithmic accountability approach is being rapidly mainstreamed into voluntary frameworks and regulations, and industry has taken a …

May 27, 2025 · Algorithmic accountability refers to the ability to understand, explain, and justify the decisions made by AI systems. In this comprehensive guide, we will explore the key concepts, …