Rise of the Machines – Clarion Call on AI by U.S. House Subcommittee

By John Russell

October 2, 2018

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.”

Stay tuned.

Link to report: https://oversight.house.gov/wp-content/uploads/2018/09/AI-White-Paper-.pdf

Subscribe to HPCwire's Weekly Update!

Be the most informed person in the room! Stay ahead of the tech trends with industry updates delivered to you every week!

Weekly Wire Roundup: July 8-July 12, 2024

July 12, 2024

HPC news can get pretty sleepy in June and July, but this week saw a bump in activity midweek as Americans realized they still had work to do after the previous holiday weekend. The world outside the United States also s Read more…

Nvidia, Intel not Welcomed in New Apple AI and HPC Development Tools

July 12, 2024

New Mac developer tools will leverage Apple's homegrown chips, limiting HPC users' ability to use parallel programming frameworks from Intel or Nvidia. Apple's latest programming framework, Xcode 16, was introduced at Read more…

Virga: Australia’s New HPC and AI Powerhouse

July 11, 2024

Australia has officially added another supercomputer to the TOP500 list with the implementation of Virga. Officially coming online in June 2024, Virga is the newest HPC system to come out of the Australian Commonwealth S Read more…

NSF Issues Next Solicitation and More Detail on National Quantum Virtual Laboratory

July 10, 2024

After percolating for roughly a year, NSF has issued the next solicitation for the National Quantum Virtual Lab program — this one focused on design and implementation phases of the Quantum Quantum Science and Technolo Read more…

NCSA’s SEAS Team Keeps APACE of AlphaFold2

July 9, 2024

High-performance computing (HPC) can often be challenging for researchers to use because it requires expertise in working with large datasets, scaling the software, and selecting the best user interface. The National Read more…

Anders Jensen on Europe’s Plan for AI-optimized Supercomputers, Welcoming the UK, and More

July 8, 2024

The recent ISC24 conference in Hamburg showcased LUMI and other leadership-class supercomputers co-funded by the EuroHPC Joint Undertaking (JU), including three of the 10 highest-ranking Top500 systems, but some other ne Read more…

Shutterstock 2203611339

NSF Issues Next Solicitation and More Detail on National Quantum Virtual Laboratory

July 10, 2024

After percolating for roughly a year, NSF has issued the next solicitation for the National Quantum Virtual Lab program — this one focused on design and imple Read more…

NCSA’s SEAS Team Keeps APACE of AlphaFold2

July 9, 2024

High-performance computing (HPC) can often be challenging for researchers to use because it requires expertise in working with large datasets, scaling the softw Read more…

Anders Jensen on Europe’s Plan for AI-optimized Supercomputers, Welcoming the UK, and More

July 8, 2024

The recent ISC24 conference in Hamburg showcased LUMI and other leadership-class supercomputers co-funded by the EuroHPC Joint Undertaking (JU), including three Read more…

Generative AI to Account for 1.5% of World’s Power Consumption by 2029

July 8, 2024

Generative AI will take on a larger chunk of the world's power consumption to keep up with the hefty hardware requirements to run applications. "AI chips repres Read more…

US Senators Propose $32 Billion in Annual AI Spending, but Critics Remain Unconvinced

July 5, 2024

Senate leader, Chuck Schumer, and three colleagues want the US government to spend at least $32 billion annually by 2026 for non-defense related AI systems.  T Read more…

Point and Click HPC: High-Performance Desktops

July 3, 2024

Recently, an interesting paper appeared on Arvix called Use Cases for High-Performance Research Desktops. To be clear, the term desktop in this context does not Read more…

IonQ Plots Path to Commercial (Quantum) Advantage

July 2, 2024

IonQ, the trapped ion quantum computing specialist, delivered a progress report last week firming up 2024/25 product goals and reviewing its technology roadmap. Read more…

Shutterstock_1687123447

Nvidia Economics: Make $5-$7 for Every $1 Spent on GPUs

June 30, 2024

Nvidia is saying that companies could make $5 to $7 for every $1 invested in GPUs over a four-year period. Customers are investing billions in new Nvidia hardwa Read more…

Atos Outlines Plans to Get Acquired, and a Path Forward

May 21, 2024

Atos – via its subsidiary Eviden – is the second major supercomputer maker outside of HPE, while others have largely dropped out. The lack of integrators and Atos' financial turmoil have the HPC market worried. If Atos goes under, HPE will be the only major option for building large-scale systems. Read more…

Everyone Except Nvidia Forms Ultra Accelerator Link (UALink) Consortium

May 30, 2024

Consider the GPU. An island of SIMD greatness that makes light work of matrix math. Originally designed to rapidly paint dots on a computer monitor, it was then Read more…

Comparing NVIDIA A100 and NVIDIA L40S: Which GPU is Ideal for AI and Graphics-Intensive Workloads?

October 30, 2023

With long lead times for the NVIDIA H100 and A100 GPUs, many organizations are looking at the new NVIDIA L40S GPU, which it’s a new GPU optimized for AI and g Read more…

Nvidia’s New Blackwell GPU Can Train AI Models with Trillions of Parameters

March 18, 2024

Nvidia's latest and fastest GPU, codenamed Blackwell, is here and will underpin the company's AI plans this year. The chip offers performance improvements from Read more…

Shutterstock_1687123447

Nvidia Economics: Make $5-$7 for Every $1 Spent on GPUs

June 30, 2024

Nvidia is saying that companies could make $5 to $7 for every $1 invested in GPUs over a four-year period. Customers are investing billions in new Nvidia hardwa Read more…

Nvidia Shipped 3.76 Million Data-center GPUs in 2023, According to Study

June 10, 2024

Nvidia had an explosive 2023 in data-center GPU shipments, which totaled roughly 3.76 million units, according to a study conducted by semiconductor analyst fir Read more…

Some Reasons Why Aurora Didn’t Take First Place in the Top500 List

May 15, 2024

The makers of the Aurora supercomputer, which is housed at the Argonne National Laboratory, gave some reasons why the system didn't make the top spot on the Top Read more…

Nvidia H100: Are 550,000 GPUs Enough for This Year?

August 17, 2023

The GPU Squeeze continues to place a premium on Nvidia H100 GPUs. In a recent Financial Times article, Nvidia reports that it expects to ship 550,000 of its lat Read more…

Leading Solution Providers

Contributors

AMD Clears Up Messy GPU Roadmap, Upgrades Chips Annually

June 3, 2024

In the world of AI, there's a desperate search for an alternative to Nvidia's GPUs, and AMD is stepping up to the plate. AMD detailed its updated GPU roadmap, w Read more…

Intel’s Next-gen Falcon Shores Coming Out in Late 2025 

April 30, 2024

It's a long wait for customers hanging on for Intel's next-generation GPU, Falcon Shores, which will be released in late 2025.  "Then we have a rich, a very Read more…

Google Announces Sixth-generation AI Chip, a TPU Called Trillium

May 17, 2024

On Tuesday May 14th, Google announced its sixth-generation TPU (tensor processing unit) called Trillium.  The chip, essentially a TPU v6, is the company's l Read more…

Choosing the Right GPU for LLM Inference and Training

December 11, 2023

Accelerating the training and inference processes of deep learning models is crucial for unleashing their true potential and NVIDIA GPUs have emerged as a game- Read more…

IonQ Plots Path to Commercial (Quantum) Advantage

July 2, 2024

IonQ, the trapped ion quantum computing specialist, delivered a progress report last week firming up 2024/25 product goals and reviewing its technology roadmap. Read more…

The NASA Black Hole Plunge

May 7, 2024

We have all thought about it. No one has done it, but now, thanks to HPC, we see what it looks like. Hold on to your feet because NASA has released videos of wh Read more…

Q&A with Nvidia’s Chief of DGX Systems on the DGX-GB200 Rack-scale System

March 27, 2024

Pictures of Nvidia's new flagship mega-server, the DGX GB200, on the GTC show floor got favorable reactions on social media for the sheer amount of computing po Read more…

MLPerf Inference 4.0 Results Showcase GenAI; Nvidia Still Dominates

March 28, 2024

There were no startling surprises in the latest MLPerf Inference benchmark (4.0) results released yesterday. Two new workloads — Llama 2 and Stable Diffusion Read more…

  • arrow
  • Click Here for More Headlines
  • arrow
HPCwire