The landscape of artificial intelligence (AI) regulation in the United States is undergoing a significant shift, with states taking a more prominent role in the absence of comprehensive federal action. Virginia is at the forefront of this movement, poised to become the second state to regulate "high-risk" uses of AI, a move that signals a future defined by a complex mosaic of state laws.

Virginia's legislature passed the High-Risk Artificial Intelligence Developer and Deployer Act, which is awaiting action by Gov. Greg Youngkin. This bill aims to curb algorithmic discrimination, requiring companies that develop and utilize "high-risk" AI systems to implement safeguard parameters. These systems span across various sectors such as employment, lending, healthcare, housing, and insurance.

This legislative effort in Virginia follows Colorado's lead in establishing a framework to address algorithmic discrimination within "high-risk" AI technologies. While sharing a similar goal, the Virginia bill presents crucial distinctions compared to Colorado's AI law. These variations include a more condensed definition of what constitutes a high-risk system, more specific transparency obligations for companies, and a less rigid standard for determining which automated decision-making activities fall under covered high-risk uses.

A key distinction between the Colorado and Virginia AI laws lies in their scope of protection. Unlike Colorado's AI Law, which has a broader scope encompassing protections for individuals in commercial or employment contexts, the Virginia AI Act is designed to protect Virginia residents primarily in individual or household contexts. This means it focuses on safeguarding individuals in their roles as consumers. For instance, this difference is illustrated in the laws' treatment of individuals in commercial or employment contexts: while both states' laws address AI-driven hiring tools, Virginia's legislation would not extend to the use of high-risk AI systems for ongoing employee monitoring, a common practice in remote work environments.

Beyond addressing algorithmic discrimination, states are also considering legislation to regulate other aspects of AI.

This surge in state-level AI regulation is occurring against a backdrop of federal ambivalence. The federal government's perceived withdrawal from the AI regulatory space, following President Trump’s executive order to ease limitations on AI development and innovations, is emboldening states to take action. However, this state-led approach is expected to result in a complex and potentially conflicting mosaic of laws across different states. This amalgam will create significant compliance challenges for businesses operating across state lines, as they will face varying regulatory requirements.

The future of AI regulation will likely involve navigating this intricate web of state laws, with companies needing to stay abreast of and adapt to diverse requirements. While states are taking proactive steps to address the risks and ethical considerations surrounding AI, the lack of a unified federal approach presents ongoing challenges for both regulators and the industry.

Example: Impact of the Virginia AI Bill

To illustrate the potential impact of the Virginia AI Bill, consider a company using AI in its hiring process.

• Current Scenario: A company uses an AI-powered tool to screen job applicants. The AI analyzes resumes and applications, scoring candidates based on certain criteria. There are no specific state regulations in place governing the use of this AI. The AI system might inadvertently discriminate against certain demographic groups, but the company may not be aware of it or have any obligation to prevent it.
  
• Impact of Virginia AI Bill: If the Virginia AI Bill is enacted, the company would likely be considered a "deployer" of a "high-risk" AI system. The company would be required to implement safeguards against algorithmic discrimination. This could involve several key measures, with algorithmic impact assessments being a crucial component:
  

  • Algorithmic Impact Assessments in Detail:
    
    Algorithmic impact assessments are in-depth evaluations designed to identify, assess, and mitigate potential risks of algorithmic discrimination and other adverse impacts arising from the use of AI systems. These assessments involve a multi-faceted approach:
    
  • Additional Compliance Measures:
    
    In addition to algorithmic impact assessments, companies would likely need to implement a risk management program to monitor and mitigate risks, provide clear disclosures to job applicants about the use of AI in the hiring process, and offer applicants explanation, correction, and appeal rights if they are adversely affected by the AI's decision.

This example demonstrates how the Virginia AI Bill aims to increase transparency and accountability in the use of AI systems, particularly in high-risk areas like employment. It also highlights the potential compliance burden on companies, which would need to take proactive steps to ensure their AI systems are fair and non-discriminatory.

Virginia's AI bill represents a significant step towards regulating AI at the state level, highlighting a trend that is likely to continue. As states take varying approaches, a complex blend of regulations is forming, posing challenges for businesses in the AI industry. Algorithmic impact assessments and proactive compliance measures will be crucial for navigating this evolving landscape and ensuring responsible AI implementation.

To effectively navigate the complexities of AI regulation and ensure compliance, businesses should seek expert guidance. Consult your legal representation today to discuss how they can help your business navigate the complexities of AI legislation, assess potential risks, and develop effective strategies to protect your interests.

This article is intended for informational purposes only and does not constitute legal advice. Please consult with an attorney to discuss your specific legal situation.