A technical standard includes all of the following:
|“|| (1) Common and repeated use of rules, conditions, guidelines or characteristics for products or related processes and production methods, and related management systems practices.
(2) The definition of terms; classification of components; delineation of procedures; specification of dimensions, materials, performance, designs, or operations; measurement of quality and quantity in describing materials, processes, products, systems, services, or practices; test methods and sampling procedures; or descriptions of fit and measurements of size or strength.
Developing technical standards Edit
The standards development approaches followed in the United States rely largely on the private sector to develop voluntary consensus standards, with Federal agencies contributing to and using these standards. Typically, the Federal role includes contributing agency requirements to standards projects, providing technical expertise to standards development, incorporating voluntary standards into policies and regulations, and citing standards in agency procurements. This use of voluntary consensus standards that are open to contributions from multiple parties, especially the private sector, is consistent with the U.S. market-driven economy and has been endorsed in Federal statute and policy.
Some governments play a more centrally managed role in standards development-related activities—and they use standards to support domestic industrial and innovation policy, sometimes at the expense of a competitive, open marketplace. This merits special attention to ensure that U.S. standards-related priorities and interests, including those related to advancing reliable, robust, and trustworthy AI systems, are not impeded.
The timing of standards development can greatly influence the state of technologies. Premature efforts can result in standards that do not reflect the state of the affected technology or may not be supported by a critical mass of technological understanding. This can yield standards that are not fit-for-purpose and can impede innovation. Alternatively, development efforts timed too late may deliver standards that cannot gain market acceptance due to the built-up infrastructure and power|market-power exerted by incumbent technologies, which will also hinder innovation. Regular review and updating are key elements to ensure that standards reflect technological innovations and take into account changing economic and societal systems.
Developing IT standards Edit
The development of standards for IT is integral to AI technologies and systems. IT encompasses all technologies for the capture, storage, retrieval, processing, display, representation, security, privacy and interchange of data and information. Worldwide, there are multiple Standards Development Organizations (SDOs) developing IT standards using different models to address varying standardization needs. The rapid innovation in IT has been accompanied by competition among SDOs in areas of market relevance (e.g., cloud computing, cybersecurity, and Internet of Things). This has encouraged SDOs to streamline their consensus-building processes to develop and approve timely, technically sound standards that meet current market needs.
Broadly, IT standards can address cross-sector or sector-specific needs. Horizontal IT standards can be used across many applications and industries. Standards developed for specific applications areas such as healthcare or transportation are vertical standards. Developers of horizontal standards often seek to establish collaborative working relationships (e.g., liaisons) with sector-specific (vertical) standards developers. These liaisons foster cooperation, establish or reinforce boundaries, and help to ensure that horizontal standards are relevant to other IT standardization efforts and vice versa.
Developing AI standards Edit
“Technical standards for AI can encompass a wide variety of issues, including safety, accuracy, usability, interoperability, security, reliability, data, and even ethics.... Flexible, robust, common technical standards for AI will be critical to the successful development and deployment of the technology for two key reasons.
"First, technical standards can provide developers clear guidelines for the design of AI systems to ensure that they can be easily integrated with other technologies, utilize best practices for cybersecurity and safety, and adhere to a variety of different technical specifications that maximize their utility.
"Second, common standards can serve as a mechanism to evaluate and compare AI systems. For example, in some contexts, there may be a legal requirement for transparency for a decision-making process, such as judicial decision-making. However, without clear standards defining what algorithmic transparency actually is and how to measure it, it can be prohibitively difficult to objectively evaluate whether a particular AI system meets these requirements or expectations, or does so better than another similar system, which discourages the adoption of these technologies. For this reason, in many cases technical standards will be a key component of determining whether an AI system is appropriate for use in a particular context."
- Developing technical standards section: U.S. Leadership in AI: A Plan for Federal Engagement in Developing Technical Standards and Related Tools, at 9.
- Developing IT standards section: Id.
- Developing AI standards section: Center for Data Innovation, https://www.nist.gov/system/files/documents/2019/05/10/nist-ai-rfi-ctr-for-data-innovation-001.pdf