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Algorithmic Accountability

What is Algorithmic Accountability?

The principle that organisations developing or deploying algorithms are responsible for the outcomes those algorithms produce. Algorithmic accountability requires monitoring for bias, errors, and unintended consequences.

AI & Technology

Each of these is named in at least one of the same controls as algorithmic accountability. The number is how many controls name both.

What the standards actually require on algorithmic accountability

Requirements naming algorithmic accountability across 3 standards, quoted from the control text.

GRI Standards2 controls

GRI governance + 2024-2025 pipeline. GOVERNANCE: GRI (Global Reporting Initiative) - independent international organization founded 1997 + headquartered Amsterdam Netherlands.

GRI-Governance-GSSB-2024-2025-Pipeline · GRI Governance (GSSB + Board), 2024-2025 Pipeline and Interoperability Initiative

Global CBPR Forum 2024-2025 status + pipeline. UK ACCESSION 2024: United Kingdom acceded April 2024 + first non-APEC member; ICO + DSIT signed accession; first wave of UK-certified Accountability Agents accredited;

CBPR-2024-2025-UK-NewJurisdictions-AI-PEP · Global CBPR Forum: 2024-2025 Update Pipeline - UK 2024, AI Integration, PEP, ASEAN MCC

Sections 10-11 of DPDP Act 2023 establish enhanced obligations on entities designated as Significant Data Fiduciaries (SDFs). Section 10 Significant Data Fiduciary: Central Government may notify Data Fiduciary or class of Data Fiduciaries as SDF having regard...

DPDP-SignificantDataFiduciary-SDF-Sec10-DPO-IndependentAuditor-DPIA-Algorithmic · DPDP Act Sections 10-11 + Significant Data Fiduciary (SDF) + Data Protection Officer + Independent Data Auditor + DPIA + Algorithmic Software Audit + Privacy by Design + Records of Processing Activities

Questions people ask about algorithmic accountability

What is Algorithmic Accountability?
The principle that organisations developing or deploying algorithms are responsible for the outcomes those algorithms produce. Algorithmic accountability requires monitoring for bias, errors, and unintended consequences.
Why is Algorithmic Accountability important for compliance?
Algorithmic Accountability is a key concept in AI & Technology. Understanding algorithmic accountability helps organizations meet regulatory requirements, reduce risk, and demonstrate due diligence during audits. Our compliance platform maps 686 frameworks with 311K cross-framework control mappings.
Which compliance frameworks address Algorithmic Accountability?
Algorithmic Accountability appears in the requirement text of GRI Standards, Global Cross-Border Privacy Rules (Global CBPR) Forum, India DPDP Act. Across these standards we have identified 4 controls that name it directly, each linked to the control text on the compliance platform.
Where can I learn more about Algorithmic Accountability?
Explore our compliance framework pages to see how algorithmic accountability applies across different standards and regulations. Our implementation guides provide step-by-step guidance, and the compliance platform offers AI-powered analysis of how this concept maps across 686 frameworks.

See how Algorithmic Accountability applies across compliance frameworks

Our platform maps 686 frameworks with 311K cross-framework control mappings. Explore how this concept is addressed across standards.

Written and maintained by Gerard Blokdyk, The Art of Service.