AI Hiring Glossary

Algorithmic Accountability

Algorithmic Accountability

The principle that organizations deploying AI systems must be responsible and answerable for their algorithms' outcomes, including discriminatory impacts. Encompasses transparency, auditability, bias testing, human oversight, and remediation of algorithmic harms.

Why This Matters for Employers

Emerging AI hiring laws establish algorithmic accountability frameworks requiring employers to audit, monitor, and remediate biased AI systems. Accountability means employers can't outsource liability to vendors - deployers remain responsible for discrimination caused by AI they use.

Related Laws & Regulations

NYC Local Law 144
New York City
Colorado AI Act
Colorado
Illinois HRAB
Illinois
Proposed federal AI legislation

Examples in Practice

Conducting annual bias audits of AI hiring tools
Maintaining documentation of AI system testing and validation
Establishing AI governance committees with oversight authority
Creating processes to investigate and remediate AI-caused discrimination

How EmployArmor Helps

Understanding Algorithmic Accountability is just the first step. EmployArmor helps you implement compliance for all AI hiring regulations.

Compliance Assessment

Find out which laws apply to your AI hiring tools and what you need to do to comply.

Documentation Templates

Get ready-to-use templates for impact assessments, notifications, and audit preparation.