Preparing for the Future of Artificial Intelligence - A Report by the National Science and Technology Council Committee on Technology
The United States Government is preparing for the future of AI. In 2016, the National Science and Technology Council Committee on Technology (NSTC) prepared a report on “Preparing for the Future of Artificial Intelligence”. The NSTC’s stated objective is to establish clear goals for federal investment into research and development. The NSTC accomplishes this task by interworking with five federal committees:
- Environment, Natural Resources, and Sustainability;
- Homeland and National Security;
- Science, Technology, Engineering, and Mathematics (STEM) Education;
- Science; and
- Technology.
The NSTC makes twenty-three recommendations in its report. These recommendations recognize the need to continue to improve AI and machine learning technology, while recognizing that now is the time to start preparing for the change this technology will bring. The NSTC’s report reveals the U.S. Government’s deep interest in preparing for the future of AI.
In its report, the NSTC makes the following recommendations:
“Recommendation 1: Private and public institutions are encouraged to examine whether and how they can responsibly leverage AI and machine learning in ways that will benefit society. Social justice and public policy institutions that do not typically engage with advanced technologies and data science in their work should consider partnerships with AI researchers and practitioners that can help apply AI tactics to the broad social problems these institutions already address in other ways.
Recommendation 2: Federal agencies should prioritize open training data and open data standards in AI. The government should emphasize the release of datasets that enable the use of AI to address social challenges. Potential steps may include developing an “Open Data for AI” initiative with the objective of releasing a significant number of government data sets to accelerate AI research and galvanize the use of open data standards and best practices across government, academia, and the private sector.
Recommendation 3: The Federal Government should explore ways to improve the capacity of key agencies to apply AI to their missions. For example, Federal agencies should explore the potential to create DARPA-like organizations to support high-risk, high-reward AI research and its application, much as the Department of Education has done through its proposal to create an “ARPA-ED,” to support R&D to determine whether AI and other technologies could significantly improve student learning outcomes.
Recommendation 4: The NSTC MLAI subcommittee should develop a community of practice for AI practitioners across government. Agencies should work together to develop and share standards and best practices around the use of AI in government operations. Agencies should ensure that Federal employee training programs include relevant AI opportunities.
Recommendation 5: Agencies should draw on appropriate technical expertise at the senior level when setting regulatory policy for AI-enabled products. Effective regulation of AI-enabled products requires collaboration between agency leadership, staff knowledgeable about the existing regulatory framework and regulatory practices generally, and technical experts with knowledge of AI. Agency leadership should take steps to recruit the necessary technical talent, or identify it in existing agency staff, and should ensure that there are sufficient technical “seats at the table” in regulatory policy discussions.
Recommendation 6: Agencies should use the full range of personnel assignment and exchange models (e.g. hiring authorities) to foster a Federal workforce with more diverse perspectives on the current state of technology.
Recommendation 7: The Department of Transportation should work with industry and researchers on ways to increase sharing of data for safety, research, and other purposes. The future roles of AI in surface and air transportation are undeniable. Accordingly, Federal actors should focus in the near-term on developing increasingly rich sets of data, consistent with consumer privacy, that can better inform policy-making as these technologies mature.
Recommendation 8: The U.S. Government should invest in developing and implementing an advanced and automated air traffic management system that is highly scalable, and can fully accommodate autonomous and piloted aircraft alike.
Recommendation 9: The Department of Transportation should continue to develop an evolving framework for regulation to enable the safe integration of fully automated vehicles and UAS, including novel vehicle designs, into the transportation system.
Recommendation 10: The NSTC Subcommittee on Machine Learning and Artificial Intelligence should monitor developments in AI, and report regularly to senior Administration leadership about the status of AI, especially with regard to milestones. The Subcommittee should update the list of milestones as knowledge advances and the consensus of experts changes over time. The Subcommittee should consider reporting to the public on AI developments, when appropriate.
Recommendation 11: The Government should monitor the state of AI in other countries, especially with respect to milestones.
Recommendation 12: Industry should work with government to keep government updated on the general progress of AI in industry, including the likelihood of milestones being reached soon.
Recommendation 13: The Federal government should prioritize basic and long-term AI research. The Nation as a whole would benefit from a steady increase in Federal and private-sector AI R&D, with a particular emphasis on basic research and long-term, high-risk research initiatives. Because basic and long-term research especially are areas where the private sector is not likely to invest, Federal investments will be important for R&D in these areas.
Recommendation 14: The NSTC Subcommittees on MLAI and NITRD, in conjunction with the NSTC Committee on Science, Technology, Engineering, and Education (CoSTEM),, should initiate a study on the AI workforce pipeline in order to develop actions that ensure an appropriate increase in the size, quality, and diversity of the workforce, including AI researchers, specialists, and users.
Recommendation 15: The Executive Office of the President should publish a follow-on report by the end of this year, to further investigate the effects of AI and automation on the U.S. job market, and outline recommended policy responses.
Recommendation 16: Federal agencies that use AI-based systems to make or provide decision support for consequential decisions about individuals should take extra care to ensure the efficacy and fairness of those systems, based on evidence-based verification and validation.
Recommendation 17: Federal agencies that make grants to state and local governments in support of the use of AI-based systems to make consequential decisions about individuals should review the terms of grants to ensure that AI-based products or services purchased with Federal grant funds produce results in a sufficiently transparent fashion and are supported by evidence of efficacy and fairness.
Recommendation 18: Schools and universities should include ethics, and related topics in security, privacy, and safety, as an integral part of curricula on AI, machine learning, computer science, and data science.
Recommendation 19: AI professionals, safety professionals, and their professional societies should work together to continue progress toward a mature field of AI safety engineering.
Recommendation 20: The U.S. Government should develop a government-wide strategy on international engagement related to AI, and develop a list of AI topical areas that need international engagement and monitoring.
Recommendation 21: The U.S. Government should deepen its engagement with key international stakeholders, including foreign governments, international organizations, industry, academia, and others, to exchange information and facilitate collaboration on AI R&D.
Recommendation 22: Agencies’ plans and strategies should account for the influence of AI on cybersecurity, and of cybersecurity on AI. Agencies involved in AI issues should engage their U.S. Government and private-sector cybersecurity colleagues for input on how to ensure that AI systems and ecosystems are secure and resilient to intelligent adversaries. Agencies involved in cybersecurity issues should engage their U.S. Government and private sector AI colleagues for innovative ways to apply AI for effective and efficient cybersecurity.
Recommendation 23: The U.S. Government should complete the development of a single, government-wide policy, consistent with international humanitarian law, on autonomous and semi-autonomous weapons.”