Housing and high finance are the two sectors of the economy where government regulation of artificial intelligence (AI) is most needed, a working group of the House Financial Services Committee concluded after a series of meetings with industry stakeholders.
The working group said the committee should “play a leadership role in overseeing the adoption of AI in the financial services and housing industries” in a new report.
The report is from the 12-member House Financial Services AI working group, which was released in January and includes both Democrats and Republicans. The report’s lead authors are committee chairman Patrick McHenry (RN.C.) and ranking member Maxine Waters (D-Calif.).
It paints a picture of AI being infused into various financial subsectors and stitched into the transactional fabric of the economy.
It describes how AI is being used in capital markets for widespread surveillance, raising questions about the extent to which conventional forces are still operational in securities markets, where algorithmic momentum has driven up to 70% of daily trading, according to with market data. researchers and former Federal Reserve bankers.
Brokers and investors told the committee that AI is reducing levels of price volatility through channels such as trading timing.
The report also details how AI is proliferating in business practices, including loan underwriting, fraud detection and debt collection, as well as customer service more broadly.
Questions about privacy and the amount of information companies can acquire about customers through the use of AI are subject to review by the working group.
In one case, companies spoke to the committee about using “computer vision technology to verify know-your-customer (KYC) information” as a way to combat fraud.
In the housing sector, different types of companies are using AI to underwrite mortgages and insurance policies, screen tenants and perform data analysis.
The committee said these uses present challenges to fair housing practices and consumer protection, as well as anti-discrimination laws.
“AI can lead to bias and discrimination and make such outcomes more difficult to detect due to a lack of explainability,” he noted.
Regulators participating in the discussion noted that companies would be expected to “follow all laws, including anti-discrimination laws and other consumer protection laws, in a technologically neutral manner.”
AI and algorithms more broadly have recently been criticized in various sectors of the economy in the context of companies’ pricing strategies. Officials and researchers say they can result in forms of price fixing that can effectively turn competitive industries into collusive cartels.
The Department of Justice recently became involved in a New Jersey lawsuit involving the hotel industry, filing a statement of interest in an “algorithmic hotel room price fixing case.”
“Companies across the economy increasingly use algorithms to determine their prices. When a small group of algorithm vendors can influence an important segment of a market, competitors are more able to use the algorithm vendor to facilitate collusion,” the DOJ said in March. declaration.
“Competitors cannot legally cooperate to set their prices, whether through their employees or an algorithm, even if competitors never communicate directly with each other,” the agency warned.
Academic research confirms the cartelizing effects of algorithmic pricing.
“Widespread adoption of the same algorithm could also lead to price coordination, resulting in high prices,” researchers at the University of Pennsylvania concluded in a 2023 studysoftware used in the multifamily housing rental market.
They found that the most algorithmically tuned markets had “higher rents and lower occupancy” and that the patterns they observed were “consistent with price coordination through the algorithm or widespread pricing errors.”
Algorithmic pricing has been on the radar of investigative journalists and policymakers in recent years.
ProPublica researchers found in 2022 that the rents for 70% of all apartments and houses in a Seattle neighborhood, which were operated by ten different property managers, were all set using pricing software for a single company called Real Page, raising questions about the extent to which “markets” are even functioning in algorithmic pricing environments.
“RealPage not only provides customers with access to anonymous, non-public information, but has also created a forum – RealPage User Group – that encourages owners to work together on issues such as revenue management,” Sens. Elizabeth Warren (D-Mass.), Tina Smith (D-Minn.), Edward Markey (D-Mass.), and Bernie Sanders (I-Vt.) wrote in a letter for the company in 2022.
Different pricing behavior, enabled by high-powered algorithms known as dynamic pricing or dynamic pricing, in which prices change from moment to moment, was also addressed in the report released on Thursday.
A housing professional told the committee that dynamic pricing needed oversight, noting “the potential for market participants to collaborate on dynamic pricing algorithms.”
The person said federal agencies should look into the use of rent-setting technologies.
Calls to regulate AI are also being heard internationally.
Technology advocates in the United Kingdom, where a new Labor government has just taken power with a sweeping reform agenda after 14 years of Conservative rule, say they want more to be done on AI.
“What concerns me in terms of the way this government is approaching AI is that they are not being inclusive and talking to the rest of civil society, as well as leading academics and researchers,” said technology commentator Stephanie Hare to the BBC on Wednesday.
This story originally appeared on thehill.com read the full story
