- The framework is designed as an initial classification tool for regulators, not as a guide to specific regulatory actions for AI systems or use cases.
- SCSP and JHUAPL argue that regulators cannot govern every AI use case and should focus attention on uses and outcomes with significant societal consequences.
- The framework recommends a preliminary analysis to determine whether foreseeable harms or benefits justify a fuller assessment of an AI application.
- When fuller review is warranted, the framework calls for parallel harms and benefits assessments across ten corresponding categories, using sector-specific judgment.
- Harms are characterized by severity and likelihood factors, while benefits are characterized by impact and likelihood factors that can be scored through rank order categories or a Likert scale approach.
The report presents the ID HCAI Framework, a classification tool intended to help regulators determine which AI uses and outcomes are highly consequential to society and therefore warrant regulatory attention. Developed by SCSP in collaboration with the Johns Hopkins Applied Physics Laboratory, the framework builds on SCSP’s earlier AI governance principles, especially sector-specific governance, modernization of existing regulators, and focus on high-consequence use cases. The source states that the partnership drew on roundtables with experts and practitioners from national security, regulatory, and emerging technology communities. The framework uses a risk-based but flexible approach rather than a static list of technologies. It begins with a preliminary screen for foreseeable harms or benefits, then calls for parallel assessments of harms and benefits across ten corresponding categories, scoring magnitude through severity, impact, and likelihood factors. It also outlines ways to make high-consequence determinations and recommends periodic reassessment as AI systems and social context change. The report emphasizes that the framework does not prescribe specific regulatory actions; instead, it is a living template that sector regulators can tailor. Its policy relevance lies in helping regulators focus limited resources, document decisions, support transparency, and identify AI applications that may require incentives, mitigation, bans, or further investigation.
An American approach to AI must balance innovation with regulation.
SCSP
- Govern AI use cases and outcomes by sector. The risks and opportunities presented by AI are inextricably tied to the context in which it is used.
- Empower and modernize existing regulators. The United States needs to empower and modernize its key regulators, and energize their engagement for the new AI era.
- Focus governance on high consequence use cases. Regulators should focus their efforts on AI uses and outcomes that will be highly consequential to society, including potential unintended uses.
- Strengthen non-regulatory AI governance. Strong, robust non-regulatory governance mechanisms should be used in addition to regulatory guardrails to properly shape AI development and use.
Published by the Special Competitive Studies Project. Co-publishers and external authors, where they exist, are credited in the byline above.