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Artificial Intelligence

Brookings Panelists Emphasize Importance of Addressing Biases in Artificial Intelligence Technology



Photo of Economic Justice Project Director Dariely Rodriguez courtesy D.C. Bar

June 19, 2020 — “The potential for discrimination increases with each generation of technology,” said Nicol Turner Lee, a fellow at the Center for Technology Innovation, in a Friday webinar hosted by the Brookings Institution about the intersection of race, artificial intelligence and structural inequalities.

AI systems hold an incredible amount of power, as they increasingly play an important role in decisions between who starves and who eats, who has housing and who remains homeless, who receives healthcare and who is sent home, and which neighborhoods are policed, panelists said.

Machine learning algorithms have become routinely utilized in decisions regarding housing, healthcare, employment, policing and the administration of public programs. But AI systems are not free of prejudice and tend to replicate and solidify the discriminatory biases of their creators.

Panelists discussed the matrix of biases that AI applications could potentially perpetuate, as the technology continues to remain largely unregulated.

“When we think about algorithms, they have to come from somewhere,” said Rashawn Ray, a David M. Rubenstein Fellow. “People think that computers are free of biases, but humans created them.”

“It’s critical to ask who is at the table in the design of these models,” said Dariely Rodriguez, director of the Economic Justice Project.

If certain demographics are excluded from the initial algorithmic design process, that will impact the ultimate technology released.

Systemic discrimination has resulted in underrepresentation of Black individuals in supervisory and executive roles, Rodriguez said.

“Only 5 percent of PhDs awarded this year went to Black women and only 3.5 percent went to Black men,” said Fay Cobb Payton, a professor of information technology and business analytics at North Carolina State University.

Panelists agreed that greater representation of diverse voices in the construction process of AI technology will improve the chances of an equitable end design.

“I think what often happens is developers approach creating algorithms in a color blind way, thinking if they don’t think about race, it won’t become an issue,” said Ray. “However, in order to create inclusive technologies, we have to center race in the models we create.”

According to Ray, Black men and women are 33 percent less likely to trust facial recognition than white populations. This mistrust is well-founded; one study found that AI facial recognition technology misidentified over one-third of Black women, compared to 1 percent of white men.

Not only are disparities built into AI technology, but the technology itself is disproportionately weaponized against Black individuals.

Ray highlighted an incident that took place on the University of North Carolina’s campus, when protests over the removal of Confederate statues brought two opposing groups of demonstrators together. The police used geofencing warrants, which allow police to collect GPS information about devices in specific areas, only on the group of protestors calling for the removal of the statue.

“All these technologies are being used on protestors right now,” said Ray. “Law enforcement is utilizing vast sources of AI technology to surveille.”

Looking forward, the panelists suggested certain steps to make AI a more democratic technology.

Payton called for the utilization of “small data” to train algorithms to better understand lived human experiences.

Ray argued that safeguards need to be put in place to ensure that technology is doing what it is programmed to do.

Finally, Rodriguez called for increased transparency and regulation in the development and implementation of such technologies.

“AI can be harnessed for good — we need to create AI that is equitable, fair, and inclusive,” Lee concluded.

Contributing Reporter Jericho Casper graduated from the University of Virginia studying media policy. She grew up in Newport News in an area heavily impacted by the digital divide and has a passion for universal access and a vendetta against anyone who stands in the way of her getting better broadband.

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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.



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.



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.



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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