Employer Pointers As Wage And Hour AI Risks Emerge

*This article was originally published on Law360.
On Oct. 30, 2023, President Joe Biden issued an expansive executive order on artificial intelligence.

The executive order dealt with many predictable topics, such as safety standards for AI technology, watermarking of AI content and intellectual property rights. One arguably surprising section, however, noted the possibility that the use of AI tools by employers could implicate federal — and presumably also state — wage and hour laws.

The reference to potential wage and hour issues in the October executive order is brief, but sheds some light on the Biden administration's potential enforcement priorities.

The executive order emphasizes the need to "support employees whose work is monitored or augmented by AI in being compensated appropriately for all of their work time" while directing the secretary of labor to issue guidance to "make clear that employers that deploy AI to monitor or augment employees' work must continue to comply with protections that ensure that workers are compensated for their hours worked."

As we await further guidance from the US Department of Labor, employers using or considering the use of AI tools should carefully assess whether such use could increase their exposure to liability under federal and state wage and hour laws, particularly as it relates to calculating or logging working time, proper classification of employees and discrimination claims.

AI offers a host of powerful new tools for employers, but the executive order is a warning to employers to proceed cautiously when implementing these new tools.

Working Time and Classification Issues

The Fair Labor Standards Act has defined the 40-hour workweek and other compensable time for nonexempt employees since "The War of the Worlds" put Martians on the radio. AI was barely on science fiction's mind.

Now, AI is an everyday reality, and is especially plugged into the workplace. From recording employee productivity to maximizing efficiency in human resources, AI holds tremendous potential for employers. But AI's capabilities and detriments are also testing the limits of the FLSA and analogous state laws.

Using AI to Surveil and Monitor Employees

The COVID-19 pandemic expedited the use of AI-powered surveillance and monitoring tools for employee computer activity — and impromptu mouse jigglers as work-arounds. Now, AI monitors the keystrokes, mouse activity and/or webcams of many remote and in-person employees. Through that AI surveillance, employers can calculate a nonexempt employee's compensable time without relying on the traditional clock in and out.

But what happens when the entirety of an employee's job is not wired to a desk or computer? For instance, an AI monitor might not account for an employee's time if the employee prints and reads reports away from their workstation. Similarly, if the employee meets a client in person, the AI may not be able to capture that time.

If the employer glances at the AI-manicured time sheet, the employer might assign more at-station work for the employee. But once the unaccounted time is reported, and the at-station time tallied, that employee's time could pass the 40-hour threshold for overtime pay.

The Band-Aid fix would be to make the employee responsible for recording their off-station time. However, the FLSA generally places the burden on the employer to accurately record all employee hours worked by nonexempt employees. So, as the AI technological and legal landscape evolves, the question remains of how to fully account for an employee's time when AI monitoring is employed.

Employees Losing Their Exemption Status Due to AI

AI and robots might not be replacing all workers, but they may be changing employees' exemption statuses.

Currently, an employee may be exempt under the FLSA and analogous state laws under some tests if the employee exercises discretion and independent judgment regarding significant matters. But what happens when the exempt employee only manages the AI that chooses the best outcome? If the employee retains no discretion, then they may no longer be exempt.

Other novel questions that affect exemption status likewise remain open: Is it possible to hire or fire a robot for purposes of managerial exemptions? Does an employee manage a robot by adding new directives or by performing physical or technical maintenance? Also, exemption statuses that may be affected by state and local laws could further muddle these scenarios.

Changing Into Wearable Technology Might Be Compensable

Generally, time spent changing into gear that is integral to the work — such as scrubs at a pork processing plant — is compensable under the FLSA.

As wearable technology in the workforce becomes commonplace, the time to put on the tech may become compensable, i.e., the half-hour spent by a warehouse employee to strap on an AI-integrated exoskeleton might be compensable. However, this raises additional issues.

For example, an employee's lunch break is unpaid if the break is uninterrupted by work. Would wearing cumbersome technology be considered an interruption? Or would the employer compensate the employee to change out of, and then back into, the gear?

On the other hand, donning items such as a hard hat or an AI-imbued watch might not be compensable if the time commitment is de minimis.

Turning Commute Time in an Autonomous Vehicle Into Compensable Time

Compensable time during an employee's drive to work was a nonissue with manually driven cars. Employees are generally not compensated for the time spent commuting before the start of the workday and after the end of the workday. For instance, a retail employee's compensable time generally starts after clocking in at the store.

Similarly, an office worker's compensable time begins after arriving at the office and performing their first task.

With the accelerated development of autonomous vehicles, however, drivers might one day be legally allowed to take their eyes off the road. And, for some employees, their eyes would fixate on their work during the commute. Meaningful work performed during that commute could then count toward the 40-hour threshold for nonexempt employees.

Potential for AI's Algorithmic Discrimination

Gone are the days of dredging through stacks of resumes or, for some companies, synchronous interviews. AI is utilized to weed out candidates who lack the qualifications set by the hirer. But not all HR dreams come true. Without proper data application, parameters and oversight, AI processes can perpetuate discrimination and violate federal or state law.

One example is EEOC v. iTutorGroup Inc., in the US District Court for the Eastern District of New York, where the US Equal Employment Opportunity Commission alleged that an AI hiring tool automatically rejected women over 55 and men over 60. The company settled the case for $365,000 in August 2023.

Less blatantly, in Baker v. CVS Health Corp., a job applicant alleged that CVS used AI facial recognition software to make credibility assessments akin to a lie detector, which is illegal in Massachusetts. In October 2023, the US District Court for the District of Massachusetts denied CVS' motion to dismiss the case.

Another interesting question has recently arisen: Can third-party AI vendors be held liable for discrimination under Title VII?

In Mobley v. Workday Inc., Workday is being sued by a class of applicants in the US District Court for the Northern District of California for selling employee-screening AI that is allegedly discriminating against candidates on the basis of age and ethnicity.


Ultimately, it is still critical for employers to closely supervise their employees and not to outsource key employment-related decisions to AI tools.

AI poses significant risk of algorithmic discrimination, bias and inaccurate or incomplete reporting. Additional guidance from the courts and the DOL may one day help employers adopt safeguards and improve tool performance, but for now employers should proceed cautiously.

*This article was originally published by Law360. (Subscription required)


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