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Regulation of AI in Healthcare Utilization Management and Prior Authorization
Colorado: On May 17, 2024, Colorado adopted the Consumer Protections in Interactions with Artificial Intelligence Systems Act of 2023. The act applies to developers of “high risk AI systems,” which includes AI systems that are used by healthcare providers to make decisions that have a “material legal or similarly significant effect on the …
The Colorado Artificial Intelligence Act
The Colorado artificial Intelligence Act
FPF U.S. Legislation Policy Brief July 2024
Authored By: Rice, Deputy Director, U.S. Legislation … Duty of Care to Mitigate Algorithmic discrimination: Developers and deployers are … reproductive health, sex, or veteran status.(Sec. 6-1-1701(1)). Self-testing for bias, activities that …
health companies building with artificial intelligence, CAIA sets the first extensive national benchmark for minimum rights and protection…ne-based system that generates outputs — such as decisions, predictions, or recommendations — that can influence real-world environments.
“Consequential Decision” means a decision that materially affects a consumer’s access to or cost of health care, insurance, or other essential services.
“High-Risk AI system” means any AI tool that makes or substantially influences a consequential decision.
“Substantial Factor” means a factor that assists in making a consequential decision or is capable of altering the outcome of a consequential decision and is generated by an AI system.
“Developers” means creators of AI systems.
“deployers” means users of high-risk AI systems.
How Can Health Care Providers Ensure Compliance?
Even though the Act sets out broad obligations, specific regulations are still forthcoming. The Colorado Attorney General has been tasked with developing rules to clarify compliance requirements. These regulations may address:
- Risk management and compliance frameworks for AI systems.
- Disclosure requirements for AI usage in consumer-facing applications.
- guidance on evaluating and mitigating algorithmic discrimination.
Health care providers should monitor developments as the regulatory framework evolves to ensure their AI-
It truly seems like you’re outlining guidelines for mitigating algorithmic discrimination in AI systems,with responsibilities for both developers and deployers. Here’s a more structured and complete version of your points:
Obligations of Developers
- Data Transparency
- Developers must document the composition and potential biases in the training data used for AI systems.
- Known Biases
- Developers must identify and document any known biases in the AI system.
- Intended Use Cases
– Developers must specify the intended use cases of the AI system.
- Risk Mitigation
– Developers must document efforts to minimize algorithmic discrimination.
- Impact Assessments
– Developers must evaluate whether the AI system poses risks of discrimination before deploying it.
Obligations of Deployers (e.g., Health Care Providers)
- Duty to Avoid Algorithmic Discrimination
– Deployers of high-risk AI systems must use reasonable care to protect consumers from known or foreseeable risks of algorithmic discrimination.
- Risk Management Policy & Program
– Deployers must implement a risk management policy and program that identifies, documents, and mitigates risks of algorithmic discrimination.
- The program must be iterative, regularly updated, and aligned with recognized AI risk management frameworks.- Requirements vary based on the deployer’s size, complexity, AI system scope, and data sensitivity.
- Impact Assessments (Regular & Event-Triggered Reviews)
– Timing Requirements:
– Before deploying any high-risk AI system.
– At least annually for each deployed high-risk AI system.
– Within 90 days after any intentional and substantial modification to the AI system.
– Required Content:
– Each impact assessment must include:
– The AI system’s purpose, intended use, and benefits.
- An analysis of risks of algorithmic discrimination and mitigation measures.
– A description of data processed (inputs, outputs, and any customization data).
– Performance metrics and system limitations.
– Transparency measures (including consumer disclosures).
– Details on post-deployment monitoring and safeguards.
- Special Requirements for Modifications
– If an impact assessment is conducted due to modifications, the assessment must include:
– An analysis of how the modifications affect the risks of algorithmic discrimination.
– Updated mitigation measures to address any new risks introduced by the modifications.
Summary
These guidelines aim to ensure that both developers and deployers of AI systems are proactive in identifying,documenting,and mitigating risks of algorithmic discrimination. By following these obligations, stakeholders can definitely help create more fair and equitable AI systems.
Summary of the Colorado AI regulation Act and its implications for Health Care Providers
The Colorado AI Regulation Act introduces significant regulations aimed at managing the risks associated with AI systems,particularly in the context of health care. Here’s a breakdown of key points and their implications for health care providers:
Key Provisions of the Act
- AI Risk Management Frameworks:
– Deployers must use recognized AI risk management frameworks to identify and mitigate discrimination risks.
- Notices to Patients/Employees:
– Before an AI system makes a consequential decision, individuals must be notified of its use.
- Post-Decision Clarification:
– If AI contributes to an adverse decision,deployers must explain its role and allow the individual to appeal or correct inaccurate data.
- Attorney General Notifications:
- If AI is found to have caused algorithmic discrimination, deployers must notify the Attorney General within 90 days.
- Exemptions for Small Deployers:
- Small deployers (those with fewer then 50 employees) who do not train AI models with their own data are exempt from manny compliance obligations.
Enforcement of the Act
- Enforcement Authority:
– Only the Colorado Attorney General has enforcement authority.
- Presumption of Compliance:
– A rebuttable presumption of compliance exists if deployers follow recognized AI risk management frameworks.
- no Private Right of Action:
– Consumers cannot sue directly under the Act.
Actions for Health Care Providers
- assess AI Usage:
– Health care providers should take early action to assess their AI usage and implement compliance measures.
- Thorough Legal Analysis:
– Conduct a thorough legal analysis to determine whether the Act applies to specific use cases.
- Review Service Agreements:
– Carefully review and negotiate service agreements with AI developers to ensure sufficient information and cooperation for compliance.
- Implement Risk Management Frameworks:
– Implement recognized AI risk management frameworks to mitigate discrimination risks.
- Establish Compliance Protocols:
– Establish protocols for ongoing compliance and work closely with legal counsel to navigate the complexities of the Act.
Final Thoughts
- Significant Shift in AI Regulation:
– The Act represents a significant shift in AI regulation, particularly for health care providers who increasingly rely on AI-driven tools for patient care.
- Broader Trend Toward AI Regulation:
– The Act reflects a broader trend toward AI regulation that is highly likely to extend beyond state borders. Health care organizations that invest in AI governance now will mitigate legal risks and maintain patient trust.
- ethical and Equitable AI Practices:
– Proactive legal assessment and compliance will be crucial to ensuring that health care providers not only meet regulatory requirements but also uphold ethical and equitable AI practices that align with broader industry standards.
Conclusion
The Colorado AI Regulation Act introduces stringent requirements for health care providers using AI systems. Compliance is not a one-size-fits-all process and requires careful evaluation and ongoing management.Health care providers must proactively assess their AI tools, implement risk management frameworks, and work closely with legal counsel to ensure compliance and maintain patient trust in an increasingly AI-driven industry.
