WASHINGTON, November 12, 2019 – The advent of artificial intelligence raises the concern of whether online algorithms harm or help user bias, experts said at a Tuesday Brookings panel.
The remarkable lack of transparency is evident in how companies analyze algorithms, said Solon Barocas, information science professor at Cornell University. Before technology became ubiquitous, it was easier for people to recognized blatant discrimination from companies. Now, he said, it’s more difficult to detect these signs from an online platform.
The reasons creditors provide to customers for adverse decisions, Barocas said, are not entirely useful.
The main difficulty is identifying and challenging algorithmic biases in the first place, said Center for Democracy and Technology Analyst Natasha Duarte. What experts do know, she said, is that certain user characteristics impact decisions made by online platforms.
Companies don’t know if algorithms can filter out discrimination, Duarte continued, which is why some organizations have imposed moratoriums on online recognition tools, until proper safeguards have been placed.
It’s not enough for an algorithm to have adequate accuracy, she said. These tools need to be frequently tested to ensure that they can administer appropriate results and prevent the acceptance of low-quality content.
That is especially true for facial recognition technology, as grainy image matching can have an adverse impact. There are multiple aspects to facial recognition that aren’t commonly discussed, said Karl Ricanek, computer science professor at the University of North Carolina, Wilmington.
The umbrella term of facial recognition, he said, is the process of matching a face with another in a different image. Facial analysis, on the other hand, investigate certain attributes of a person’s face to provide a more detailed description. Affective computing can also be used to analyze visible facial expressions.
Despite the vast science behind facial recognition technology, Ricanek said, members in both the public and private sectors don’t completely understand the decisions algorithms make for individuals daily.
Regulators are behind the curve, he said, because they are still trying to understand the most basic technology. Companies are also not performing the necessary due diligence to make sure their algorithms lack bias.
The bottom line, however, said Ricanek, is that current algorithms can’t tell everything that users want to know. Experts should still use common sense and analyze existing literature on the subject. Moreover, there needs to be assurance that machine learning isn’t being used to replace simple solutions that may have more political ramifications.
Deepfakes Pose National Security Threat, Private Sector Tackles Issue
Content manipulation can include misinformation from authoritarian governments.
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.
Should the Federal Government Regulate Artificial Intelligence?
Two experts were on opposite sides of the debate about how to mitigate the downsides of AI.
WASHINGTON, July 12, 2022 – Representatives from academia and a nonprofit diverged at a Bipartisan Policy Center event Tuesday about whether the government should step in and minimize problems associated with artificial intelligence, including bias and discrimination in algorithms.
“We really do want actors to help us establish national and international guidelines,” said Miriam Vogel, president, and CEO of EqualAI, a nonprofit that seeks to reduce bias in AI. “We are driving full speed without lanes, without speed limits to manage the expectations.”
While acknowledging the benefits of AI in society today, Vogel said its algorithms present risk that often leads to bias and discrimination. She shared the example of how facial recognition misses certain voices or skin tones.
AI is used in various sectors and powers algorithms that cater services to individuals. Panelists referenced the use of AI algorithms in suspect identification for criminal justice, in disease diagnosis in health care, and for movie and employment recommendations.
Vogel said regulation will establish clear expectations for AI companies to minimize such risks.
Adam Thierer, a senior research fellow at the Mercatus Center at George Mason University, said 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. He called this an “educational institution approach.”
He said that because of how long federal law takes to enact, he wants to reach AI workers directly, such as the computer programmers and AI innovators “of tomorrow” to do a better job of “baking best practices” into AI.
“I think baking best practice principles in by design begins with an educational focus,” said Thierer.
Thierer said he wants to give this job to trusted third parties to suggest pathways forward, including ethical evaluations and consultations with AI companies. He said that when it comes to AI rules across different sectors, “we don’t need one overarching standard to rule them all.”
Thierer added that because of how fast AI is changing, “it can’t go through the same regulatory process.” He argued if regulation is put in place, we will lose AI innovators.
Vogel disagreed with Thierer, saying she doesn’t believe that there is a risk of losing innovators with regulating AI, and instead, said, “I see regulation is the partner to innovation.”
She said that because there is no government regulation for AI, companies are left to do it themselves if they choose, referencing the Badge Program at EqualAI that seeks to help companies navigate risks.
“We need to have a governance system put in place to make sure continual testing is taking place,” said Vogel.
FTC Commissioner Says Agency Report on AI for Online Harms Did Not Consult Outside Experts
The FTC released a report that warned about the dangers of AI’s use to combat online harms.
WASHINGTON, June 22, 2022 – Federal Trade Commissioner Noah Phillips said last week that a report by the commission about the use of artificial intelligence to tackle online harms did not consult outside experts as Congress asked.
The FTC’s “Combatting Online Harms through Innovation” report – approved by a 4-1 vote to send to Congress and released on June 16 – warns against using AI as a policy solution for online problems, as the commission says it contains inherent design flaws, bias and discrimination, and features commercial surveillance concerns. The commission concluded that the potential adoption of AI could increase additional harms.
However, the report found that amid the use of AI by Big Tech platforms to address online harms, “lawmakers should consider focusing on developing legal frameworks that would ensure that AI tools do not cause additional harm.”
The one dissenting opinion on the report was from Phillips, who said the FTC did not do the study that was required by Congress. As part of the 2021 Consolidated Appropriations Act, Congress asked the FTC to conduct a study on how artificial intelligence could address online harms such as fake reviews, hate crimes and harassment and child sexual abuse.
“I do not believe we conducted the requisite study, and I do not think the report on AI issued by the Commission takes sufficient care to answer the questions Congress asked,” Phillips said in his dissenting statement.
Phillips said the report mainly focuses on the technology of AI itself and lacks the outside perspective from individuals and companies who use AI and try to combat the harms of AI online, which he said is “precisely what Congress asked us to evaluate.”
Phillips added that in the 12 months the FTC was given to complete this study, “rather than use this time to solicit input from all relevant stakeholders, the Commission chose to conduct a kind of literature review.
Phillips said in his statement he would have liked to see interviews of market participants or surveys conducted, which allegedly isn’t included in the recent report and adds that he is instead concerned about the “quantity of self-reference” used by the FTC in the report.
“Still, we should at least endeavor to produce a report that reflects the full diversity of experiences and viewpoints on these important issues concerning AI.” Phillips also noted the report doesn’t include a serious cost-benefit analysis of using AI to combat online harms.
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