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Algorithmic accountability

Algorithmic accountability requires organisations to justify, monitor and control automated decisions, addressing bias, transparency, data protection and remedies.

Algorithmic accountability concerns the legal and governance duties around AI and automated decision systems. It requires clarity about purpose, data sources, model performance, human oversight, discrimination risks, explainability, security and avenues to contest harmful outcomes. In Switzerland, data protection, employment, consumer, financial, health and public-law rules may apply depending on use. Comparative developments, especially in Europe, influence expectations for risk assessments and documentation. Organisations should keep records of design choices, testing, monitoring, incident handling and responsibilities across vendors and deployers.

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