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U.S. Special Operations Command Employs AI and Machine Learning to Improve Operations

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Screenshot from the webinar

December 11, 2020 — In today’s digital environment, winning wars requires more than “boots on the ground.” It also requires computer algorithms and artificial intelligence.

The United States’ Special Operations Command is currently playing a critical role advancing the employment of AI and machine learning in the fight against the country’s current and future advisories, through Project Maven.

To discuss the initiatives taking place as part of the project, General Richard Clarke, who currently serves as the Commander of USSOCOM, and Richard Shultz, who has served as a security consultant to various U.S. government agencies since the mid-1980s, joined the Hudson Institute for a virtual discussion on Monday.

Among other objectives, Project Maven aims to develop and integrate computer-vision algorithms needed to help military and civilian analysts encumbered by the sheer volume of full-motion video data that the Department of Defense collects every day in support of counterinsurgency and counter terrorism operation, according to Clarke.

When troops carry out militarized site exploration, or military raids, they bring back copious amounts of computers, papers, and hard drives, filled with potential evidence. In order to manage enormous quantities of information in real time to achieve strategic objectives, the Algorithmic Warfare Cross-Function task force, launched in April 2017, began utilizing AI to help.

“We had to find a way to put all of this data into a common database,” said Clarke. “Over the last few years, humans were tasked with sorting through this content — watching every video, and reading every detainee report. A human cannot sort and shift through this data quickly and deeply enough,” he said.

AI and machine learning have demonstrated that algorithmic warfare can aid military operations.

Project Maven initiatives helped “increase the frequency of raid operations from 20 raids a month to 300 raids a month,” said Schultz. “AI technology increases both the number of decisions that can be made, and the scale. Faster more effective decisions on your part, are going to give enemies more issues.”

Project Maven initiatives have increased the accuracy of bomb targeting. “Instead of hundreds of people working on these initiatives, today it is tens of people,” said Clarke.

AI has also been used to rival adversary propaganda. “I now spend over 70 percent of my time in the information environment. If we don’t influence a population first, ISIS will get information out more quickly,” said Clarke.

AI and machine learning tools, enable USSOCOM to understand “what an enemy is sending and receiving, what are false narratives, what are bots, and more,” the detection of which allows decision makers to make faster, and more accurate, calls.

Military use of machine learning for precision raids and bomb strikes naturally raises concerns. In 2018, more than 3,000 Google employees signed a petition in protest against the company’s involvement with Project Maven.

In an open letter addressed to CEO Sundar Pichai, Google employees expressed concern that the U.S. military could weaponize AI and apply the technology towards refining drone strikes and other kinds of lethal attacks. “We believe that Google should not be in the business of war,” the letter read.

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Artificial Intelligence

AI Should Compliment and Not Replace Humans, Says Stanford Expert

AI that strictly imitates human behavior can make workers superfluous and concentrate power in the hands of employers.

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Photo of Erik Brynjolfsson, director of the Stanford Digital Economy Lab, in January 2017 by Sandra Blaser used with permission

WASHINGTON, November 4, 2022 – Artificial intelligence should be developed primarily to augment the performance of, not replace, humans, said Erik Brynjolfsson, director of the Stanford Digital Economy Lab, at a Wednesday web event hosted by the Brookings Institution.

AI that complements human efforts can increase wages by driving up worker productivity, Brynjolfsson argued. AI that strictly imitates human behavior, he said, can make workers superfluous – thereby lowering the demand for workers and concentrating economic and political power in the hands of employers – in this case the owners of the AI.

“Complementarity (AI) implies that people remain indispensable for value creation and retain bargaining power in labor markets and in political decision-making,” he wrote in an essay earlier this year.

What’s more, designing AI to mimic existing human behaviors limits innovation, Brynjolfsson argued Wednesday.

“If you are simply taking what’s already being done and using a machine to replace what the human’s doing, that puts an upper bound on how good you can get,” he said. “The bigger value comes from creating an entirely new thing that never existed before.”

Brynjolfsson argued that AI should be crafted to reflect desired societal outcomes. “The tools we have now are more powerful than any we had before, which almost by definition means we have more power to change the world, to shape the world in different ways,” he said.

The AI Bill of Rights

In October, the White House released a blueprint for an “AI Bill of Rights.” The document condemned algorithmic discrimination on the basis of race, sex, religion, or age and emphasized the importance of user privacy. It also endorsed system transparency with users and suggested the use of human alternatives to AI when feasible.

To fully align with the blueprint’s standards, Russell Wald, policy director for Stanford’s Institute for Human-Centered Artificial Intelligence, argued at a recent Brookings event that the nation must develop a larger AI workforce.

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Artificial Intelligence

Workforce Training Needed to Address Artificial Intelligence Bias, Researchers Suggest

Building on the Blueprint for an AI Bill of Rights by the White House Office of Science and Technology Policy.

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Russell Wald. Credit: Rod Searcey, Stanford Law School

WASHINGTON, October 24, 2022–To align with the newly released White House guide on artificial intelligence, Stanford University’s director of policy said at an October Brookings Institution event last week that there needs to be more social and technical workforce training to address artificial intelligence biases.

Released on October 4, the Blueprint for an AI Bill of Rights framework by the White House’s Office of Science and Technology Policy is a guide for companies to follow five principles to ensure the protection of consumer rights from automated harm.

AI algorithms rely on learning the users behavior and disclosed information to customize services and advertising. Due to the nature of this process, algorithms carry the potential to send targeted information or enforce discriminatory eligibility practices based on race or class status, according to critics.

Risk mitigation, which prevents algorithm-based discrimination in AI technology is listed as an ‘expectation of an automated system’ under the “safe and effective systems” section of the White House framework.

Experts at the Brookings virtual event believe that workforce development is the starting point for professionals to learn how to identify risk and obtain the capacity to fulfill this need.

“We don’t have the talent available to do this type of investigative work,” Russell Wald, policy director for Stanford’s Institute for Human-Centered Artificial Intelligence, said at the event.

“We just don’t have a trained workforce ready and so what we really need to do is. I think we should invest in the next generation now and start giving people tools and access and the ability to learn how to do this type of work.”

Nicol Turner-Lee, senior fellow at the Brookings Institution, agreed with Wald, recommending sociologists, philosophers and technologists get involved in the process of AI programming to align with algorithmic discrimination protections – another core principle of the framework.

Core principles and protections suggested in this framework would require lawmakers to create new policies or include them in current safety requirements or civil rights laws. Each principle includes three sections on principles, automated systems and practice by government entities.

In July, Adam Thierer, senior research fellow at the Mercatus Center of George Mason University stated that he is “a little skeptical that we should create a regulatory AI structure,” and instead proposed educating workers on how to set best practices for risk management, calling it an “educational institution approach.”

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Artificial Intelligence

Deepfakes Pose National Security Threat, Private Sector Tackles Issue

Content manipulation can include misinformation from authoritarian governments.

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Photo of Dana Roa of Adobe, Paul Lekas of Global Policy (left to right)

WASHINGTON, July 20, 2022 – Content manipulation techniques known as deepfakes are concerning policy makers and forcing the public and private sectors to work together to tackle the problem, a Center for Democracy and Technology event heard on Wednesday.

A deepfake is a technical method of generating synthetic media in which a person’s likeness is inserted into a photograph or video in such a way that creates the illusion that they were actually there. Policymakers are concerned that deepfakes could pose a threat to the country’s national security as the technology is being increasingly offered to the general population.

Deepfake concerns that policymakers have identified, said participants at Wednesday’s event, include misinformation from authoritarian governments, faked compromising and abusive images, and illegal profiting from faked celebrity content.

“We should not and cannot have our guard down in the cyberspace,” said Representative John Katko, R-NY, ranking member of House Committee on homeland security.

Adobe pitches technology to identify deepfakes

Software company Adobe released an open-source toolkit to counter deepfake concerns earlier this month, said Dana Rao, executive vice president of Adobe. The companies’ Content Credentials feature is a technology developed over three years that tracks changes made to images, videos, and audio recordings.

Content Credentials is now an opt-in feature in the company’s photo editing software Photoshop that it says will help establish credibility for creators by adding “robust, tamper-evident provenance data about how a piece of content was produced, edited, and published,” read the announcement.

Adobe’s Connect Authenticity Initiative project is dedicated to addressing problems establishing trust after the damage caused by deepfakes. “Once we stop believing in true things, I don’t know how we are going to be able to function in society,” said Rao. “We have to believe in something.”

As part of its initiative, Adobe is working with the public sector in supporting the Deepfake Task Force Act, which was introduced in August of 2021. If adopted, the bill would establish a National Deepfake and Digital task force comprised of members from the private sector, public sector, and academia to address disinformation.

For now, said Cailin Crockett, senior advisor to the White House Gender Policy Council, it is important to educate the public on the threat of disinformation.

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