Last week, the top U.S. House of Representatives subcommittee on IT weighed in on AI with a new report – Rise of the Machines: Artificial Intelligence and its Growing Impact on U.S. Policy. It’s a 15-page, fast read, focused on policy not technology or specific legislation; that said, where there’s a government report, sometimes funding and programs follow.
The report is the result of hearings and research begun last February in the Subcommittee on Information Technology Committee on Oversight and Government Reform. Subcommittee chairman Will Hurd (R-TX) and ranking member Robin Kelly (D-IL) are the listed authors. They emphasize the report’s conclusions relate to “narrow AI – such as playing strategic games, language translation, self-driving vehicles” and not to “general AI, [which] can accomplish more than one task and can move between these tasks based on reasoning.”
Still, Rise of the Machines has an urgent tone: “Chief among the Subcommittee’s recommendations is for the federal government to increase federal spending on research and development to maintain American leadership with respect to AI. In response to concerns about AI’s potential economic impact, federal, state, and local agencies are encouraged to engage more with stakeholders on the development of effective strategies for improving the education, training, and reskilling of American workers to be more competitive in an AI-driven economy.”
It’s probably wrong to call the report alarmist but it certainly is full of worry. To a considerable degree the concerns expressed are familiar – workforce dislocation, cybersecurity, global rivals, privacy, biases, malicious use of AI. Consider these two bulleted excerpts on potential workforce impact taken from the report:
- A December 2017 report from the McKinsey Global Institute reported that as a result of AI-driven automation, “up to 1/3 of [the] workforce in the United States and Germany may need to find work in new occupations.”
- Another study released by Oxford University in 2013 found the impact on U.S. workers by AI technologies may even be higher. According to the Oxford study, “about 47 percent of total U.S. employment is at risk.”These studies indicate the negative impact AI may have on jobs, which has the potential to increase wealth inequality in the United States.
The report also points out that other studies indicate AI has the potential to improve and increase jobs. Part of the challenge is the uncertainty surrounding AI impact on the workforce.
Interestingly, AI progress and global leadership were linked broadly to national R&D spending by the report, which said the R&D spending trend in the U.S. is worrisome:
“Notably, China’s commitment to funding R&D has been growing sharply, up 200 percent from 2000 to 2015.19 On February 7, 2018, the National Science Board’s (Board) and the National Science Foundation’s (NSF) Director, who jointly head NSF, said in a statement that if current trends continue, the Board expects “China to pass the United States in R&D investments” by the end of 2018.”
“China’s rapidly growing investment in AI. Particularly concerning is the prospect of an authoritarian country, such as Russia or China, overtaking the United States in AI. As the Subcommittee’s hearings showed, AI is likely to have a significant impact in cybersecurity, and American competitiveness in AI will be critical to ensuring the United States does not lose any decisive cybersecurity advantage to other nation-states.”
A big question, of course, is how to effectively mobilize. For example, the report labelled as promising Defense Advanced Research Projects Agency’s (DARPA) Artificial Intelligence Exploration program which “plans to invest more than $2 billion into this program and other existing programs. The program focuses research on ‘third wave’ AI theory and application that will make it possible for machines to contextually adapt to changing situations.”
The subcommittee presented a few ideas. Here are two:
Innovative research. “There should be a Grand Challenge, similar to DARPA’s Grand Challenges, using data to solve a problem. The benefit of DARPA’s Grand Challenges is their ability to foster innovative, collaborative research among teams seeking to overcome seemingly unattainable goals. Take, for example, DARPA’s Self-Driving Car Challenge, which offered $1 million to the first team to autonomously navigate a desert course from California to Nevada. In the first year of the Challenge, no team completed the course. In fact, the farthest any vehicle went was 7.5 miles. Yet eighteen months later, 5 out of the 195 competing teams completed the 132-mile course, with the winner having crossed the finish line in a little under seven hours. DARPA’s Grand Challenges provide strong incentives for innovation, and, as seen with its Self-Driving Cars Challenge, can effectuate quick technological advancement. Such competitions have spurred creativity, research, and collaboration, leading to some of the most groundbreaking inventions in recent history.”
Product oversight. “At minimum, a widely agreed upon standard for measuring the safety and security of AI products and applications should precede any new regulations. A common taxonomy also would help facilitate clarity and enable accurate accounting of skills and uses of AI. The National Institute of Standards and Technology (NIST) is situated to be a key player in developing standards. Similar private sector efforts exist from the Institute of Electrical and Electronics Engineers’ Global Initiative on Ethics of Autonomous and Intelligent Systems. The AI Index, which is a part of Stanford’s “One Hundred Year Study on AI,” collects data about AI in order to track and measure its progress, which will be critical in the standards development process to provide historical context. The federal government should look to support public, academic, and private sector efforts in the development of standards for measuring the safety and security of AI products and applications.”
The report frankly noted that narrow AI is already here: “AI is now used in connection with mapping applications or “apps” on mobile phones, tax preparation, song writing, and digital advertising. It is also being used in video games and movies to create special effects. More recently, the Food and Drug Administration approved an AI algorithm that aids radiologists in detecting wrist fractures. The State of Ohio uses robotics in the Bureau of Criminal Investigation laboratories to help reduce the turnaround time on untested rape kits. The application of AI facilitated the state testing 14,000 previously untested rape kits and identifying 300 serial rapists linked to 1,100 crimes.”
“The Government Services Administration has a robotic processing automation (RPA) pilot that automates portions of the Multiple Award Schedules new offer review process. Presently, contract officers must go through a tedious administrative process, reading through dozens of pages of documentation across multiple IT systems to ensure a vendor’s new offer is consistent with information already in government databases. RPA software offers the capability to perform these tasks, so the contract officers can spend more time engaging with customers.”
It’s reasonable to wonder what comes next. Rise of the Machines certainly seems to be setting the stage for broader governmental oversight and involvement in AI development and use: “AI has the potential to disrupt every sector of society in both anticipated and unanticipated ways. In light of that potential for disruption, it’s critical that the federal government address the different challenges posed by AI, including its current and future applications.”