The information provided here are SDO committees that are active in the development of AI standards and have active federal participation.
Note: This SDO information originated from Appendix A of this report:
U.S. LEADERSHIP IN AI: A Plan for Federal Engagement in Developing Technical Standards and Related Tools Prepared in response to Executive Order 13859 Submitted on August 9, 2019
List of SDOs/Groups and Calendar of Meetings:
AI-related cross sector and sector specific standards have been and are being developed in several committees and subcommittees.
Starting in 2016, the IEEE P7000™ series of standards projects addresses specific issues at the intersection of technological and ethical considerations for AI.
Several ASTM technical committees are developing standards to support the reliable, robust, and trustworthy systems that use AI.
CTA events: https://www.cta.tech/Events
Investigating possible standardization work for AI in the following focus groups:
OMG events: https://www.omg.org/events/index.htm
If there are events specific to AI-related OMG groups, they are probably listed in the members only area.
Info about OMG work in AI:
SAE events: https://www.sae.org/attend
Standards mentioned in the AI Report:
- SAE J 3016-2018, Taxonomy and Definitions for Terms Related to Driving Automation Systems for On-Road Motor Vehicles
- SAE CRB 1-2016 (SAE CRB1-2016) Managing The Development Of Artificial Intelligence Software (Stabilized: May 2016)
Note that DOT events are not listed in this table.
Examples of both horizontal cross sector and vertical sector-specific standards for AI systems are found in the Department of Transportation report, Preparing for the Future of Transportation: Automated Vehicles 3.0 (AV 3.0). Voluntary consensus standards are mentioned throughout this report as a strategy for supporting Automated Driving Systems and Automated Vehicle development. Appendix C, “Voluntary Technical Standards for Automation,” lists numerous AI-relevant horizontal and vertical standards in the functional areas of: Definitions and Architecture; Data; Design; Maintenance and Inspections; Functional/Performance; Protocols (Communications); Security; and Testing/Test Target.
The W3C Web Ontology Language (OWL) is a Semantic Web language designed to represent rich and complex knowledge about things, groups of things, and relations between things. OWL is a computational logic-based language such that knowledge expressed in OWL can be exploited by computer programs, e.g., to verify the consistency of that knowledge or to make implicit knowledge explicit. OWL documents, known as ontologies, can be published in the World Wide Web and may refer to or be referred from other OWL ontologies. OWL is part of the W3C’s Semantic Web technology stack.
The term “Semantic Web” refers to W3C’s vision of the Web of linked data. Semantic Web technologies enable people to create data stores on the Web, build vocabularies, and write rules for handling data.Standards include: RDF, OWL, SPARQL, RDFa, JSONLD, SKOS, RDFS, GRDDL, POWDER, PROV, RIF, SAWSDL, RDB2RDF.
W3C Events: https://www.w3.org/participate/eventscal.html