Written By Employment Screening Resources® (ESR)
Government agencies in the United States such as the Federal Trade Commission (FTC), the Consumer Financial Protection Bureau (CFPB), and the Equal Employment Opportunity Commission (EEOC) will increase scrutiny on how Artificial Intelligence (AI) is used in background screening, according to the “ESR Top Ten Background Check Trends” for 2021 compiled by leading global background check firm Employment Screening Resources® (ESR).
In April 2020, the FTC – the nation’s primary privacy and data security enforcer – issued guidance to businesses on “Using Artificial Intelligence and Algorithms” written by Director of FTC Bureau of Consumer Protection Andrew Smith on the use of AI for Machine Learning (ML) technology and automated decision making with regard to federal laws that included the Fair Credit Reporting Act (FCRA) that regulates background checks.
“Headlines tout rapid improvements in artificial intelligence technology. The use of AI technology – machines and algorithms – to make predictions, recommendations, or decisions has enormous potential to improve welfare and productivity. But it also presents risks, such as the potential for unfair or discriminatory outcomes or the perpetuation of existing socioeconomic disparities,” Director Smith wrote in the FTC guidance.
“The good news is that, while the sophistication of AI and machine learning technology is new, automated decision-making is not, and we at the FTC have long experience dealing with the challenges presented by the use of data and algorithms to make decisions about consumers,” Smith wrote. In 2016, the FTC issued a report on “Big Data: A Tool for Inclusion or Exclusion?” In 2018, the FTC held a hearing to explore AI and algorithms.
In July 2020, the Consumer Financial Protection Bureau (CFPB) – a government agency that helps businesses comply with federal consumer financial law – published a blog on “Providing adverse action notices when using AI/ML models” that addressed industry concerns about how the use of AI interacts with the existing regulatory framework. One issue is how complex AI models address the adverse action notice requirements in the FCRA.
“FCRA also includes adverse action notice requirements. For example, when adverse action is based in whole or in part on a credit score obtained from a consumer reporting agency (CRA), creditors must disclose key factors that adversely affected the score, the name and contact information of the CRA, and additional content. These notice provisions serve important anti-discrimination, educational, and accuracy purposes,” the blog stated.
“There may be questions about how institutions can comply with these requirements if the reasons driving an AI decision are based on complex interrelationships. Industry continues to develop tools to accurately explain complex AI decisions… These developments hold great promise to enhance the explainability of AI and facilitate use of AI for credit underwriting compatible with adverse action notice requirements,” the blog concluded.
In December 2020, ten Democratic members of the United States Senate sent a letter requesting clarification from the U.S. Equal Employment Opportunity Commission (EEOC) Chair Janet Dhillon regarding the EEOC’s authority to investigate bias in AI driven hiring technologies, according to a press release on the website of U.S. Senator Michael Bennet (D-Colorado), one of the Senators who signed the letter.
“While hiring technologies can sometimes reduce the role of individual hiring managers’ biases, they can also reproduce and deepen systemic patterns of discrimination reflected in today’s workforce data… Combatting systemic discrimination takes deliberate and proactive work from vendors, employers, and the Commission,” Bennet and the other nine Senators wrote in the letter to EEOC Chair Dhillon.
“Today, far too little is known about the design, use, and effects of hiring technologies. Job applicants and employers depend on the Commission to conduct robust research and oversight of the industry and provide appropriate guidance. It is essential that these hiring processes advance equity in hiring, rather than erect artificial and discriminatory barriers to employment,” the Senators continued in the letter.
“Machine learning is based on the idea that machines should be able to learn and adapt through experience and Artificial Intelligence refers to the broader idea that machines can execute tasks intelligently to simulate human thinking and capability and behavior to learn from data without being programmed explicitly,” explained Attorney Lester Rosen, founder and chief executive officer (CEO) of ESR.
“There have certainly been technological advances including back-office efficiencies and strides towards better integrations that streamline the employment screening process. However, does that qualify as machine learning or AI? In reality, true machine learning and artificial intelligence and the role it is likely to play in the future could fuel a new source of litigation for plaintiff’s class action attorneys,” said Rosen.
“Proponents of AI argue that it will make the processes faster and take bias out of hiring decisions. It is doubtful that civil rights advocates and the EEOC will see it that way. The use of AI for decision making is contrary to one of the most fundamental bedrock principles of employment – that each person should be treated as an individual, and not processed as a group or based upon data points,” Rosen concluded.
Employment Screening Resources® (ESR) – a leading global background check provider that was ranked the number one screening firm by HRO Today in 2020 – offers the award-winning ESR Assured Compliance® system, which is part of The ESRCheck® Solution, for real-time compliance that offers automated notices, disclosures, and consents for employers performing background checks. To learn more about ESR, visit www.esrcheck.com.
Since 2008, Employment Screening Resources® (ESR) has annually selected the “ESR Top Ten Background Check Trends” that feature emerging and influential trends in the background screening industry. Each of the top background check trends for 2021 will be announced via the ESR News Blog and listed on the ESR background check trends web page at www.esrcheck.com/Tools-Resources/ESR-Top-Ten-Background-Check-Trends/.
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