In a highly orchestrated policy announcement made at the 2020 CES show, the Trump Administration released a draft framework and set of principles for governance of AI technology and applications in the U.S.
Specifically, the OMB released a memorandum to all federal agencies and executive offices, the “Guidance for Regulation of Artificial Intelligence Applications” (AI Guidelines), a detailed policy document articulating the Administration’s regulatory and non-regulatory approach to the many forms of emerging artificial intelligence (AI) technology and applications in society today. The Administration is inviting public comment on the AI Guidelines for a period of sixty days which will conclude on March 13.
According to the Administration’s AI policy lead, Chief Technology Officer Michael Kratsios, the AI Guidelines are intended to achieve three overarching policy goals:
The guidelines reflect a National AI strategy based on a philosophy of regulatory restraint, as mandated by President Trump’s Executive Order 13859. Indeed, the AI Guidelines call for federal agencies to consider a regulatory approach that fosters “innovation, growth, and engenders trust, while protecting core American values” through both regulatory and non-regulatory actions and “reducing unnecessary barriers to the development and deployment of AI.” To that end, the AI Guidelines directs federal agencies to “avoid regulatory and non-regulatory actions that needlessly hamper AI innovation and growth.”
We purposely wanted to avoid top-down, one-size-fits-all, blanket regulations...
Lynne Parker, U.S. Deputy Chief Technology Officer,
White House Office of Science and Technology Policy
Notably, the AI guidelines do not articulate a policy preference or approach for regulating any specific AI technology or application, such as facial recognition, deep fakes or algorithmic decision-making systems. Nor do the guidelines articulate high-level governance or ethical principles that would cover all AI technologies.
Instead, the Administration is using the comment process to design potential regulation of AI technologies consistent with “the U.S. approach to free-market capitalism, federalism, and good regulatory practices.”
In conjunction with the AI guidelines, the Department of Transportation also released their latest guidance on the development of autonomous vehicles, largely reflecting the regulatory restraint articulated in the AI Guidelines. Ironically, at the same time that the Administration was touting its philosophy of regulatory restraint, the Commerce Department’s Bureau of Industry and Security issued an interim final rule restricting the sale and export of Geospatial AI software, which leverages AI to analyze satellite imagery.
The Administration’s AI Guidelines direct agencies to first consider actions that encourage innovation, growth and engender trust while also “protecting core American values,” which, according to OMB, include “protecting American technology, economic and national security, privacy, civil liberties, and other American values, including the principles of freedom, human rights, the rule of law, and respect for intellectual property.”
Specifically, the agencies must consider approaches that reduce barriers to the development and deployment of AI, and avoid actions that hamper AI innovation and growth. Further, agencies must undertake AI-specific cost-benefit analyses before taking any action.
These principles reflect traditional conservative principles of limited regulation in the area of emerging technologies that is necessary to ensure that new regulations do not stifle innovation – what one agency head has called “regulatory humility.” Notably, this approach differs from some proposals in Congress, which seek to regulate or limit algorithms or certain AI applications, and marks a clear move away from the type of top-down regulatory oversight that many believe the EU may adopt in the months ahead.
Notably, the OMB guidance encourages federal agencies to consider preempting state laws in certain situations, including (if necessary) addressing inconsistent, duplicative or burdensome state laws “that prevent the emergence of a national market.” The AI Guidelines specifically direct federal agencies to consider the effect of potential federal regulation on existing or potential state actions.
This approach mirrors many of the same issues raised in the current debate over the need for a national privacy framework, and the potential preemption of certain state laws.
The 10 principles identified in the AI Guidelines are as follows:
Indeed, the discussion of fairness, discrimination, disclosures and transparency in principles 7 & 8 could be read as a tacit acknowledgement that some regulations may be necessary in some circumstances. A number of high-profile issues, such as bias and discrimination, are called out in this framework.
For example, principle #7 (Fairness and Nondiscrimination) asserts that AI applications have the potential to reduce present-day discrimination caused by human subjectivity, while also acknowledging the risk that certain applications can introduce bias that produces discriminatory outcomes or decisions that undermine public trust and confidence in AI.
Similarly, principle #8 (Disclosure and Transparency) recognizes that transparency can increase public trust and confidence in AI, and that at times certain disclosures may be necessary or appropriate. For example, this principle acknowledges that disclosing when AI is being used may be appropriate when the application is used to interface with human beings. At the same time, this principle also recognizes that certain existing legal or policy regimes may be sufficient to address such concerns, so careful evaluation is necessary.
Recognizing that data quality is key to enabling trustworthy and robust AI, principle #3 (Data Quality) directs agencies to hold information that is likely to have a clear and substantial influence on important public policy or privacy sector decisions “to a high standard of quality, transparency and compliance.” Specific best practices cited in the OMB Guidance include: transparently articulating strengths, weaknesses, intended optimizations or outcomes, bias mitigation, and appropriate uses of AI application results.
Although the AI Guidelines indicate a strong preference for agencies to adopt a light-touch approach, there is no express prohibition on the adoption of new regulations. However, the AI Guidelines do offer examples of several “non-regulatory” actions that agencies may take to address potential risks posed by AI, including:
The promotion of safe harbors, pilot programs, best practices and other frameworks is encouraging, and could be a useful tool in many circumstances for advocating for alternative approaches if regulators appear to be intent on moving towards adopting new regulations.
Following the public comment period that ends March 13, and upon issuance of the finalized guidelines, agencies with regulatory authority relevant to AI will have 180 days to submit plans to the OMB to “demonstrate consistency” with the AI Guidelines. Such agencies must identify statutory authorities specifically authorizing agency regulation of AI applications or technology, as well as any collection of AI-related information from regulated entities.
Covered agencies are also expected to list and describe any planned or considered regulatory actions on AI.
Several agencies are already in the middle of developing new regulatory policies centered on AI and algorithmic decision-making, including FDA, PTO, Commerce Department, and HUD. DWT’s AI Team will be closely following those proceedings and any new proposals to ensure conformance with these guidelines. Please contact the authors to learn more about these and other AI regulatory and policy developments.