The Current Policy Landscape in California
In California, the policy landscape for Artificial Intelligence (AI) is evolving rapidly, with a myriad of bills introduced this legislative cycle. In health care, AI holds the potential to transform diagnosis and treatment recommendations, improve patient engagement and adherence to care plans, and reduce the administrative burden on clinical teams to have more quality time to engage with patients.
Connecting for Better Health (C4BH) is tracking the progress of AI bills in 2024 as they make their way through the legislature. Many of the proposed bills have been amended and are currently in the Appropriations committees. These bills have until the end of August to make it to Governor Newsom’s desk for signature.
There is a concerted effort to make AI more inclusive, encompassing diverse entities such as government agencies, academic institutions, and private sector partners. Current legislation generally focuses on the governance of AI within the health care sector, aiming to establish safety and security protocols, risk assessment measures, and unbiased evaluation processes for health plans utilizing AI technology. The expansion of data sharing relies on a close tracking of how bias may alter or corrode data analytics. To prevent the likelihood of bias, proactive approaches must be deployed to develop anti-biased data sharing practices. Already, we have seen EHR algorithms double and triple book appointments for individuals with a high no-show probability (Health Affairs). In the same vein, AI tools have been shown to use expense as a way to define high-utilizers, which shifts resources to individuals that are more likely to have insurance and attainable access to care (Payer Issues). A regulatory framework is vital for promoting trust, accountability, and the responsible use of AI in an increasingly data-driven world.
Principles for Trustworthy AI
Across the current AI landscape, principles to foster trust and reliability in AI have emerged from organizations such as the Coalition for Health AI (CHAI) and the National Institute of Standards and Technology:
- Usefulness, Usability, and Efficacy: AI should provide tangible benefits, be user-friendly, and deliver effective results.
- Fairness, Equity, and Bias Management: AI systems must be fair, equitable, and actively managed to prevent bias.
- Safety and Reliability: AI technologies should be safe to use and consistently reliable.
- Transparency, Intelligibility, and Accountability: AI processes and decisions should be transparent, understandable, and accountable by all parties, including patients.
- Security and Privacy: Ensuring the security and privacy of data is crucial in maintaining trust in AI systems.
Future Considerations
As AI continues to be integrated into health care, several considerations must be addressed to ensure its proper use and effectiveness. Compliance with regulations, targeting diverse populations and addressing social determinants of health (SDOH), algorithmic bias, and HIPAA/consent considerations are paramount. Ensuring that AI technologies adhere to these standards will help mitigate risks and promote trust in AI-driven health care solutions.
Connecting for Better Health’s Role
C4BH is committed to engaging with AI-related legislation both in California and nationally. As our coalition advocates for more inclusive and seamless data sharing, the goal should be leveraging AI technologies to improve health care outcomes equitably, ensuring they reduce disparities in care rather than exacerbate them.
