Defendants can have a disparate impact case dismissed if they can show that the inputs of the model are not highly correlated to protected class, or if the algorithm was generated by a third party. The burden then shifts back to the plaintiff to prove that the defendant’s interests could be achieved with a policy or practice that is less discriminatory.The proposal also carves out new defenses for landlords and lenders who use algorithmic models to determine factors like credit-worthiness or risk.
For the first three years of Trump’s term, Congress has rebuffed the administration’s cuts and funding levels have maintained the status quo. By turning algorithm use into a shield for discriminators, HUD once again seeks to make federal policy the agent of discrimination, not the cure for it.You’ve run out of free articles. Housing is the greatest store of wealth that Americans have, and for many years, federal law and policy The proposal, while billed as a mere update to bring regulations in line with the Supreme Court’s 2015 decision, creates entirely new rules for landlords using algorithms.
New HUD Guidelines for an Emotional Support Animal Landlord Concerns for Allowing Pets in a Rental. This is a major development for owners of ESAs and the first comprehensive update to ESA housing rules since HUD last issued guidance in 2013. So if a hypothetical landlord decides to predict number of noise complaints as a proxy for difficult tenants, using music streaming data they somehow obtained, they might find a correlation between preferred musical genre and how difficult a tenant is. There are functionally two separate defenses being created. It’s no different for the rental industry. If you value our work, please disable your ad blocker.By joining Slate Plus you support our work and get exclusive content. 12 Important Facts ESA Owners Need to Know The HUD proposal is designed to make it harder for plaintiffs to win these cases.
“With this harmful proposal, the Trump administration continues its pattern of attempts to weaken and disrupt the federal government’s responsibility to uphold its fair housing obligations under the law.”Under the current Disparate Impact rule, the plaintiff, or the party making the accusation of discrimination, has to prove that a policy is causing a discriminatory effect. When it comes to discussions about algorithmic discrimination, the concern is not only that someone might use a well-known substitute for protected class, like ZIP code, as an input when they secretly want to use race. L. No.
Then the defendant has to prove that the policy is necessary for legitimate, nondiscriminatory results.
Landlords who do not want to discriminate will have peace of mind that they need never be troubled by pesky discrimination lawsuits again as long as they buy industry-standard software, leaving their own discriminatory choices unexamined. Algorithms present a more complex problem: Machine learning models rely on interaction When the proposal’s new rule allows defendants to prove nondiscrimination feature by feature, it misses the whole point.
Nowhere is that more likely the case than in housing—a fact that the people working in HUD surely know well.
It has proposed dramatic cuts to rental subsidies, public housing, and Community Development Block Grants.
That is a standard concern for disparate impact and would still be a concern after this rule is implemented, but it’s not a problem new to algorithmic discrimination. Section 209 of the Economic Growth, Regulatory Relief, and Consumer Protection Act: Guidance for Shared Waiting Lists - Through this notice, the U.S. Department of Housing and Urban Development (HUD) complies with Section 209(e) of the Economic Growth, Regulatory Relief and Consumer Protection Act of 2018, Pub. 115-174, by providing guidance regarding how to facilitate the voluntary use … Right now, those industry standards don’t exist, but organizations such as the While HUD claims that its rule “is not intended to provide a special exemption for parties who use algorithmic models,” the agency’s stated goal is to limit potential disparate impact liability, to make it easier to make “practical business choices and profit-related decisions.” If its new rule stands, HUD will be wildly successful in that goal. Join Slate Plus to continue reading, and you’ll get unlimited access to all our work—and support Slate’s independent journalism. And the results of machine learning algorithms are highly sensitive to the The third-party defense, which is designed to let landlords use industry-standard tools, is no better. Landlords have a concern... HUD New Guidelines for Reasonable Accommodation Requests. Malicious actors can easily devise algorithms that functionally Beginning today, there is a 60-day period when public comments are accepted.
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