US – ILLINOIS
EXPERT VIEW
KEY TAKEAWAYS
The US Federal Approach Shows Signs of Balancing AI Innovation With Oversight:
Artificial intelligence
According to OMB, “high-impact AI” is AI for which the “output serves as a principal basis for decisions or actions that have a legal, material, binding, or significant effect on rights or safety.” OMB describes the types of individual and organisational rights and safety interests that might be implicated by “high-impact AI.” They include: • “civil rights, civil liberties, or privacy”; • “access to education, housing, insurance, credit, employment”; • “access to critical government resources or services”; and • “human health and safety”. OMB goes a step further and identifies examples of Federal agency AI use cases that OMB presumes to be “high-impact.” Examples of “high- impact AI” use cases in healthcare – which is the industry on which my law practice focuses – include: • “Medically relevant functions of medical devices”; • “Patient diagnosis, risk assessment, or treatment”; • “Allocation of care in the context of public insurance”; and • “Control of health-insurances costs and underwriting.” Each of those healthcare-related examples pertains to a matter for which the use of AI in generating an output that informs, influences, decides, or executes a decision or action would generally be viewed by most people (not just Americans) as “high impact.” That is because each listed matter relates to “human health,” either in terms of accessing safe and appropriate health care or accessing affordable health insurance to pay for health care. Applying Minimum Risk Management Practices to “High-Impact AI” Use Cases OMB mandates that Federal agencies apply a minimum set of practices to manage risks arising from the “high- impact AI” use cases the agencies determine and document. Those risks, says OMB, include “risks related to the efficacy, safety, fairness, transparency, accountability, appropriateness or lawfulness of a decision or action” resulting from AI’s use to “inform,
periodic human review of the AI to detect and mitigate adverse impacts in the AI’s performance or security post-deployment. 4. Ensure sufficient training and assessment of the human operators of the AI and the human users of the AI output. 5. Ensure human oversight, intervention and accountability for the “high- impact AI” use case commensurate with the risks the use case presents. impacted by a decision or action resulting from the “high-impact AI” use case to appeal the decision or action with a human review. 7. Seek and account for input from the individuals and organisations affected by the “high-impact AI” use case. These risk management practices have appeal in managing the efficacy, safety, fairness, transparency, accountability, appropriateness, and/or lawfulness risks of “high-impact AI” use cases. That’s because they describe actions to be taken. 6. Enable individuals negatively Those actions may be taken not only by Federal agencies – but by private companies – that have determined and documented their “high-impact AI” use cases. Just because these risk management practices are not law to which private American companies are subject, these risk management practices provide a counterbalance to the unrestricted acceleration of AI use and innovation.
Despite early rhetoric about “global AI dominance”, the Trump-era OMB Memorandum M-25-21 signals a pragmatic shift – requiring US federal agencies to incorporate governance principles that promote safe and effective AI deployment, especially for “high- impact AI” applications.
‘High-Impact AI’ Defined by Risk to Rights, Safety and Public Welfare: Use cases are
Watch what the Federal Government does, not what it says
deemed “high-impact” when AI outputs materially affect individual rights, safety, or access to critical services such as health care, education, or housing. Businesses – especially those in the health or insurance sectors – can look to these definitions when assessing risk and liability. Voluntary Guidelines Offer Practical Guardrails for the Private Sector: While not binding for private companies, the seven OMB- prescribed risk management practices (including pre- deployment testing, human oversight, and user appeal rights) offer a valuable framework for managing legal, ethical and reputational risk in AI deployment.
Kathy Roe is managing attorney and co-founder of Health Law Consultancy, a Chicago-based boutique law firm providing legal services for the business of healthcare. Roe began her legal career working for a publicly traded life and health insurance company and later moved into “Big Law” as an associate and then partner before launching Health Law Consultancy over 15 years ago. Roe’s legal experience encompasses regulatory counseling and contracting for health and pharmacy insurance and benefits, health information processing and protection, and payer/provider/vendor arrangements of all sorts in the healthcare space. Roe’s excellence in health law is recognised by Chambers USA and Best Lawyers. Roe is a Vice Chair and Chair- Elect for the Payers, Plans and Managed Care Practice Group of the American Health Law Association. Roe is a former President and Director of the Illinois Association of Healthcare Attorneys.
influence, decide, or execute” the decision or action. The seven minimum practices, says OMB, for managing those risks for a “high-impact AI” use case are: 1. Conduct pre-deployment testing of the AI. 2. Complete a pre-deployment impact assessment of the AI. 3. Conduct ongoing monitoring and
Kathy Roe Managing Attorney, Health Law Consultancy
+1 312 332 7711 kroe@hlconsultancy.com irglobal.com/advisor/kathy-roe
ABOUT US...
hlconsultancy.com
Health Law Consultancy’s focus is strategic application of health law to the business of healthcare. Health Law Consultancy is a boutique law firm that enables health sector businesses to capitalise on business opportunities, manage industry challenges, and gain competitive advantage. With our singular focus on health law, we practice at a high level of sophistication, knowledge, and skill. Health Law Consultancy’s core proficiencies encompass regulatory counseling and contracting for: • Health data privacy, security, and exchange • Prescription drug benefits, payment and pricing
S ince the Trump Administration’s start, its language has been all about “removing the barriers to American leadership in artificial intelligence.” That so-named Executive Order states that U.S. policy under President Trump is “to sustain and enhance America’s global AI dominance.” Nowhere does the Executive Order convey a balancing of any other objective against the pursuit
of worldwide AI dominance.
all there is some Trump Administration recognition of the need for guardrails in developing and deploying AI. Determining and Documenting “High-Impact AI” Use Cases One AI governance area of particular OMB attention is determining and documenting Federal agency use cases for AI that are “high-impact.”
• Health insurance market and government benefits program entry and operations • Antitrust compliance and fraud and abuse avoidance in healthcare • Joint ventures, affiliations, and alliances in healthcare Health Law Consultancy is ranked by Chambers USA for health law in Illinois and rated Chicago Metropolitan Tier 1 in health law by Best Lawyers “Best Law Firms.”
What a surprise, then, to read the White House Office of Management and Budget (OMB)’s Memorandum M-25-21 to non-security Federal agencies about Federal AI use. Although the memorandum encourages federal agencies to “accelerate the Federal use of AI,” OMB, in doing so, asserts that Federal agencies “must redefine AI governance as an enabler of effective and safe AI innovation.” So, maybe, after
irglobal | 23
22 | irglobal
Made with FlippingBook - professional solution for displaying marketing and sales documents online