The discussion of Artificial Intelligence (“AI”) in the workplace typically focuses on whether the AI tool and model has a discriminatory impact. This means examining whether the AI output creates an unlawful disparate impact against individuals belonging to a protected category.
However, that discussion rarely centers on the types of training data used, and whether the training data itself could have a harmful effect on the workers tasked with training the AI model.
It has been four years since Congress enacted the Eliminating Kickbacks in Recovery Act (“EKRA”), codified at 18 U.S.C. § 220. EKRA initially targeted patient brokering and kickback schemes within the addiction treatment and recovery spaces. However, since EKRA was expansively drafted to also apply to clinical laboratories (it applies to improper referrals for any “service”, regardless of the payor), public as well as private insurance plans and even self-pay patients fall within the reach of the statute.
Recent Updates
- ABA and FWA: Compliance Best Practices
- Regulatory Scrutiny in ABA: What Providers Need to Know About Compliance Oversight
- When Clear Drafting is Not Enough: Fifth Circuit Rejects a “Sole Discretion” Arbitration Clause
- ABA and FWA: Legitimate Providers Operate in a High-Risk Environment
- Powerful Tool, but Not an Attorney: Massachusetts Court Rejects Work Product Protection for AI-Generated Documents