Hearings to examine Artificial Intelligence and housing.
Housing Opportunity and Community Development
2024-01-31
Source: Congress.gov
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Transcript
Good morning. The Subcommittee on Housing, Transportation, and Community Development will come to order. Today's hearing will focus on both the promise and the threats that artificial intelligence poses in the housing sector, and I am very much looking forward to our witnesses' testimony into this conversation. I want to thank Ranking Member Lummis and her staff for your ongoing bipartisan work as we put together this hearing. We both share, I believe, a deep interest in how we can develop federal policy that supports innovation and expands opportunity for everyone to have a safe, decent, affordable place to live. And one of the most consequential innovations in recent years is artificial intelligence. Leader Schumer, Senator Rounds, Senator Young and Senator Heinrich are leading a bipartisan effort to explore the impacts, opportunities and threats that AI poses, and they have asked Senate committees to engage in our areas of expertise, which leads us to this committee hearing today, examining what AI means for housing. So without a safe, decent, affordable place to live, nothing in your life works, not your job, your family, your education, your health. So a foundation question is how AI can help or hinder this goal. We know that some aspects of artificial intelligence have been around for a long time, and we also know that major advances are fueling the use of AI in finance and housing in ways that we need to understand. Consumers find AI when they encounter chat bots when they shop online or digital helpers that seem to be ubiquitous. And AI plays a role when a prospective tenant is looking to rent an apartment, or a renter submits a maintenance request to a management company, or a family tries to qualify for a home loan, or when a person experiencing homelessness is connected to services. These are powerful tools that hold great potential to cut costs and to target services, to reduce wait times, and to even reduce bias. But they also have the potential to bake in existing in equities and to reduce accountability and even limit opportunity.
Today, AI is being used actively in every part of the housing continuum, from emergency homelessness services to mortgage financing. And as I was preparing for this hearing, I found endless applications. AI is being deployed, for example, to help connect people experiencing homelessness with health and housing resources. AI is helping to forecast more precisely and accurately where families are at risk of eviction so that we can better target assistance. Academics and advocates are using AI and machine learning to help understand and map the country's zoning laws and codes spanning 30,000 different localities. And these insights could help us to understand the dense and complicated rules that govern where and how and what types of housing are being built so that we can make better decisions about how to boost housing supply and lower costs. So there are many opportunities. And there are also some very real concerns about the threats that AI poses. In Minnesota, some landlords are reportedly using AI-generated tenant screening reports that include incorrect and sometimes illegal or off-limits information. It's even harder for people to find a place to rent in some circumstances, and they may never know why they were declined or be able to correct the record. For landlords, maybe it's just easier to move on to the next applicant rather than consider additional information. Another example of how AI used in a bad way can be quite harmful. There's a lawsuit in Minnesota right now against a law firm that has allegedly automated the process of filing evictions for landlords. In one month, the firm filed 400 eviction complaints. These eviction filings lacked much detail about why the eviction was happening and seemed to routinely lack basic information about lease terms or to include significant errors around lease dates and rental amounts and payment information. So the fact that a firm allegedly leaned on AI to generate a large number of eviction filings with false information, apparently without any meaningful review by an attorney, that's a big problem.
Not only is the eviction illegal, but that eviction will live on in public records and hurt the tenant into the future. AI is also increasingly part of how people buy homes. It is used in credit scoring models and automated valuation models, which determine the value of a home. How AI is deployed has major implications for a person's credit scores, their mortgage rates, and whether home ownership and wealth building is even within reach. We know that we have historic systemic challenges with fairness and equity in this country. My own hometown of Minneapolis has some of the greatest disparities in home ownership between black and white families of anywhere in the country. So we need to carefully explore whether AI is extending and reinforcing these biases and how it has the potential to correct them. Our excellent witnesses here today have an unenviable task in your opening statements to ground us in both these opportunities and threats in AI and housing in five minutes. I look forward to hearing from you. And I also look very much forward to the questions from my colleagues as we follow up after your testimony. With any innovation, there are both opportunities and challenges that we need to balance. And our job is to think about these complex issues so that we can develop the best public policy. So I very much look forward to this conversation. And I now turn to Senator Lummis for her opening statement. Well, thank you, Madam Chairwoman.
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