{"id":6640,"date":"2022-08-31T19:08:00","date_gmt":"2022-08-31T19:08:00","guid":{"rendered":"https:\/\/www.brightmine.com\/us\/?post_type=resources&p=6640"},"modified":"2025-04-23T09:25:45","modified_gmt":"2025-04-23T09:25:45","slug":"ai-discrimination-prevent-disability-discrimination","status":"publish","type":"resources","link":"https:\/\/www.brightmine.com\/us\/resources\/hr-compliance\/discrimination\/ai-discrimination-prevent-disability-discrimination\/","title":{"rendered":"AI discrimination: Preventing unintentional disability discrimination"},"content":{"rendered":"\n
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Prevent your AI from causing unintentional disability discrimination<\/h1>\n\n\n\n

AI discrimination is still a real concern HR leaders shouldn’t ignore. One specific type of discrimination that AI create is disability discrimination. Learn how this could happen and how to prevent it.<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Published: August 31, 2022 | by Robert S. Teachout<\/strong>, Legal Editor at Brightmine<\/p>\n\n\n\n

Artificial intelligence (AI) is transforming HR and the workplace by enabling and improving organizations’ ability to make data-based human resource decisions. These new technologies can play a key role that positively impacts an organization’s work, workplace and workforce. They can facilitate talent acquisition with smart forms, shape curated and personalized onboarding experiences, facilitate collaboration and even make the workplace more democratic and accessible via AI-driven technology.<\/p>\n\n\n\n

When implemented with foresight and care, AI also has the potential to improve compliance and risk management by mitigating discrimination in hiring and promotions. But without proper preparation and precautions, an employer runs the risk of its AI unintentionally screening out qualified candidates for discriminatory reasons, including applicants with disabilities.<\/p>\n\n\n\n

The problems in an AI system may arise from inadequate testing, programming bias or the AI tool learning bias based on the data of past employer decisions provided for analysis. To help employers recognize the risk of bias and take steps to mitigate it, the Equal Employment Opportunity Commission (EEOC) released new guidance on the Americans With Disability Act and the use of AI<\/a>.<\/p>\n\n\n\n

Algorithmic tools are often designed to predict whether an applicant can do a job under typical working conditions, or to look for a profile that fits current, successful employees, explained Sharon Rennert, a senior attorney advisor at the EEOC’s ADA\/GINA Division during a Brightmine<\/a> (formerly XpertHR) webinar<\/a>.<\/p>\n\n\n\n

“Typical working conditions do not include the use of reasonable accommodation,” Rennert reminded attendees, “and a typical profile does not reflect the differences between a successful non-disabled employees and a person with a disability who can be successful if provided with a reasonable accommodation.”<\/p>\n\n\n\n

An unlawful “screen-out” may occur when an AI tool prevents a job applicant or employee from meeting (or lowers their performance on) a selection criterion, resulting in that individual losing a job opportunity. Take, for instance, a situation in which a chatbot program automatically screens out anyone who has a significant employment gap. Rennert asked, “What if the applicant had a six-month gap due to a mental health condition 20 years earlier, but has since had over 19-and-a-half years of uninterrupted service? In reality, this employee with a disability is very qualified.” Although the criterion is neutral on its face, in practice the AI has caused an unlawful discriminatory hiring decision.<\/p>\n\n\n\n

There also is the risk of AI learning bias based on patterns in the data provided to train the system, patterns that can unintentionally disadvantage an individual on the basis of many characteristics. For example, Amazon developed an automated talent search program to review resumes and vet applicants. Screening was based on patterns the AI learned from the resumes of successful candidates submitted to the company over a 10-year period. Amazon had to quickly halt the program after it became apparent that the system’s hiring recommendations were biased against women. It turned out that the sampling of resumes used in the programming were mostly from men, reflecting the male dominance in the tech industry.<\/p>\n\n\n\n

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Want to make smarter, more-informed decisions?<\/h2>\n\n\n\n
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Learn more<\/a><\/div>\n<\/div>\n<\/div>\n\n\n\n

To minimize disadvantaging persons with disabilities when using an AI decision-making tool, Rennert recommended:<\/p>\n\n\n\n