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This week, the U.S. Department of Commerce announced that it would form a committee to advise federal agencies on AI research and development. Known as the National Artificial Intelligence Advisory Committee and supported by the National Institute of Standards and Technology and the White House’s National AI Initiative Office, it will focus on a range of AI-related issues, including U.S. The current state of competitiveness and how AI can increase opportunities for different geographical regions.
The formation of the committee comes amid an increase in federal spending on AI technologies during the epidemic. According to Deltin’s Govin, identifiable federal spending on AI rose to about 1 1 billion in 2020, making it one of the fastest growing tech investment sectors. While the figure fell short of estimates સરકારે the Bloomberg government estimated that the US would invest more than 6 6 billion in AI-related R&D projects in 2021 છે a sign of renewed enthusiasm from the government that could reach આર્થિક 1.3 trillion by 2030. .
Former Google CEO Eric Schmidt is one who has urged legislators to increase funding in the AI space while encouraging public-private partnerships to develop AI applications in government agencies. The National Security Commission on Artificial Intelligence estimates that the U.S. needs to spend 32 32 billion over the next few years to win the AI competition with China among other competitors. To achieve this, President Joe Biden has proposed spending 2% of U.S. total economic output – or GPD – on science, about 0.7%. That would be about $ 418 billion at last year’s GDP level, which was about $ 146 billion.
The GovWin report shows that the federal government is not close to Biden’s goal. But it shows that AI spending in agencies is generally increasing by 50% compared to 2018. In addition, US AI spending is rising even without a primary scientific mission on agencies, the report states – such as the Department of Justice, transportation, and the state. And AI capabilities, including robotic process automation, are increasingly being used by the government for research, monitoring, trend analysis, and vaccine development.
Between 2018 and 2020, U.S. government agencies spent a total of 9 1.9 billion on AI-related service obligations, a 70% increase over a three-year period. Although the AI costs of the Department of Transportation, the Department of Homeland Security (DHS), and the National Aeronautics and Space Administration combined decreased by $ 81 million, R&D costs reached 1. 1.2 billion in the same 2018 to 2020 period.
Notable AI spending agencies outside the top ten include the Department of Veterans Affairs ($ 38 million), the Department of Commerce ($ 37 million), the Department of Agriculture ($ 28 million) and the Social Security Administration ($ 26 million). Expenditure on autonomy across all agencies from 2018 to 2020 totaled $ 520 million, followed by Intelligent Systems ($ 122 million), Machine Learning ($ 114 million), Augmented Reality ($ 39 million), Deep Learning ($ 26 million) and Virtual Reality ( $ 24 million).
But U.S. defense spending far outstripped civilian agencies. According to GovWin, the Department of Defense AI has kept 109% more on AI from 2018 to 2020: the top ten contractors have been given જવાબ 550 million AI liabilities. Defense accounted for 37% of total AI spending by the U.S. government, with contractors receiving windfalls. Lehed Kahid Martin earned $ 106 million for cyber radar from the Missile Defense Agency while Accenture earned $ 29 million from DHS, the Transportation Security Administration, the Commerce Department and the Patent and Trademark Office.
Some of these projects were in disputed territory. Microsoft and Amazon, for example, were awarded Pentagon contracts to help the military identify objects from drones and other aerial footage – a project Google announced in 2018 that it would not renew amid widespread protests from employees. And a recent report published by the Government Responsible Office states that about a dozen agencies plan to expand their use of facial recognition, a technology that has been shown to discriminate against marginalized gender and ethnic groups.
In light of this, while the Govin report acknowledges that investing in the U.S. To remain competitive, he warns, agencies should improve trust and security in AI and develop standards for the use of technology. “Law and executive branch policy are key drivers of federal AI and machine learning investments,” he reads. “Limiting the regulatory burden on agencies hoping to take advantage of AI and machine learning will be a key factor shaping future investment.”
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