【英文】2021年美国新一届政府创新技术议程（47页）

英文研究报告 2020年12月09日 06:40 管理员

critical factor in the United States’ economic and military success has been the achievement of global leadership in advanced technology; however, the next administration will inherit the country’s most tenuous global position in this area since the Second World War. In today’s Fourth Industrial Revolution, technological change over the next 30 years will make the last 30 years look insignificant. The next administration will also deal with a dramatically shifting global landscape influenced by the long-term effects of the coronavirus pandemic and a Chinese government that is trying to rapidly erode U.S. technological advantages through legal and illegal means. Winning this generation-defining struggle for global leadership in advanced technology will not just affect the U.S. economy but will also shape the rest of the century for the entire world. The next administration must have a comprehensive technology agenda to spur innovation in the United States, leverage innovative technologies within government to better serve citizens, mitigate the challenges posed by technological disruption, and work with allies to ensure our democratic values drive development of these new tools.

Though artificial intelligence (AI) is just one of many critical emerging technologies, the blueprint for achieving global leadership in AI can be a useful guide for how the next administration could foster innovation across a number of technologies. The explosion of data and computational capability has made advances in AI possible; but these resources are concurrently chokepoints preventing the maturity of the industry. Continued AI innovation will require large amounts of data and if the federal government provided more high-quality data sets to the public, entrepreneurs and researchers could compete more closely on the quality of their ideas, rather than their access to proprietary data sets. Open data does not just advance innovation, it can also promote equity by reducing one source of bias in AI—inferior training data. While vetted government data sets will not eliminate bias, this coupled with investment in digital infrastructure can go a long way in addressing digital equity. Whether it is increasing access to supercomputing resources for academic researchers to advance basic knowledge or providing broadband access so underserved communities can participate in the digital economy, the United States will not reach its full AI potential if bright minds are left behind.