In response to President Biden’s Executive Order relating to the safe use of AI, the U.S. Department of Labor just released new guidance titled “Artificial Intelligence and Worker Well-being: Principles and Best Practices for Developers and Employers.” While non-binding, this guidance creates a framework that may inform future employment-related enforcement actions and regulatory development in the AI space.
Key Areas Requiring Review by In-House Counsel
- Discrimination and Civil Rights Compliance
- Labor Relations and Organizing Rights
- Data Privacy and Security
- AI Governance and Human Oversight
- Worker Transparency Requirements
Of primary concern are discrimination and civil rights considerations. The guidance makes clear that employers must audit AI systems for disparate impacts across protected classes before deployment, and notably, indicates these audit results should be made public. Systems must maintain compliance with existing anti-discrimination laws, with special attention paid to accessibility and reasonable accommodations for workers with disabilities. This public disclosure requirement, while not legally mandated, could create exposure risks that need careful management.
Labor relations emerge as another crucial focus area. The guidance cautions that AI systems cannot interfere with or monitor protected organizing activities, and systems that could have a “chilling effect” on labor organizing are prohibited. Employers should provide advance notice to workers and unions about new AI implementation, and meet all collective bargaining obligations regarding AI deployment. This may require revising existing technology implementation procedures and union communication protocols.
Data privacy and security requirements form a third major component of the new guidance. The DOL emphasizes that worker data collection must be limited to legitimate business purposes, with prompt notification required for any data breaches. Consent requirements apply to sharing worker data with third parties, and special protections are needed for medical and genetic information. These requirements align with, and expand upon, existing data privacy obligations.
Suggested Action Items for Legal Departments
- Review existing AI implementations against new guidelines
- Develop comprehensive AI governance framework
- Update privacy policies and data handling procedures
- Establish audit and documentation protocols
- Review collective bargaining agreements for AI provisions
The guidance establishes expectations for governance and oversight. AI cannot be the sole decision-maker for significant employment decisions, and documented appeal procedures are strongly advised for adverse AI-driven decisions. Organizations should consider implementing training for managers overseeing AI systems and establish clear governance structures accountable to leadership. This suggests the need for a formal AI internal governance framework using these technologies.
Transparency obligations represent another significant area of focus. Companies should strongly consider providing advance notice to workers about AI implementation, clearly disclosing data collection and monitoring practices, and ensuring workers have access to review and correct their data. Plain language explanations are optimal for AI-driven employment decisions, creating new operational requirements for HR and management teams.
This guidance likely signals future enforcement priorities and may inform the development of more formal regulations. Organizations should consider piloting AI systems before full deployment and implement regular independent audits of AI systems. Establishing clear channels for worker feedback and developing protocols for AI-related workforce transitions will be crucial for compliance and risk management.
Risk Mitigation Priorities
- Establish independent audit procedures
- Create worker feedback channels
- Develop AI-related workforce transition protocols
- Review insurance coverage for AI-related risks
General counsel should work closely with HR, IT, and operations to ensure AI implementations align with these principles while meeting business objectives. This may require updating existing policies and procedures, developing new training programs and establishing documentation protocols. Organizations that proactively align with these guidelines may be better positioned for future compliance requirements and face reduced legal risk.
