Chapter

Department of Labor

Several statutes empower the U.S. Department of Labor to protect Americans from risks that artificial intelligence poses to their wages, workplace safety and health, access to benefits, privacy, and other areas.

In this article
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Employers take resumes and talk to prospective new hires at a career fair in Lake Forest, California, on February 21, 2024. (Getty/Paul Bersebach/MediaNews Group/Orange County Register)

See other chapters in CAP’s Report: Taking Further Agency Action on AI

Authors’ note: For this report, the authors use the definition of artificial intelligence (AI) from the 2020 National Defense Authorization Act, which established the National Artificial Intelligence Initiative.1 This definition was also used by the 2023 “Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.”2 Similarly, this report makes repeated reference to “Appendix I: Purposes for Which AI is Presumed to be Safety-Impacting and Rights-Impacting” of the 2024 OMB M-24-10 memo, “Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence.”3

Read the fact sheet

The fact sheet lists all of the recommendations detailed in this chapter of the report.

The U.S. Department of Labor (DOL) oversees numerous statutes, from the Fair Labor Standards Act (FLSA) to the Family and Medical Leave Act (FMLA), that can potentially help address the challenges and opportunities of artificial intelligence (AI) as it affects workers. Governing for Impact (GFI) and the Center for American Progress have extensively researched these existing authorities in consultation with numerous subject matter experts. However, the goal is to provoke a generative discussion about the following proposals, rather than outline a definitive executive action agenda. Each potential recommendation will require further vetting before agencies act. Even if additional AI legislation is needed, this menu of potential recommendations to address AI demonstrates that there are more options for agencies to explore beyond their current work and that agencies should immediately utilize existing authorities to address AI.

The proliferation of AI and automated algorithmic technologies poses both macro and micro challenges for workers. At one extreme, sufficiently advanced AI may displace entire occupation categories, putting thousands or millions of Americans out of work. But such dramatic predictions can also overshadow how AI and automated technologies already play a role in shifting worker power to employers and denying workers statutory protections.

While the ultimate scale of workplace disruption remains unknown, the DOL is responsible for implementation and enforcement of several statutes that protect and empower workers.4 As President Joe Biden acknowledged in his 2023 “Executive Order on the Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence,” automated systems and other technology deployed in the workplace hold great potential to improve working conditions.5 But they can also pose grave risks to workers’ rights and safety if not used carefully or implemented without worker input.6 This section explains some of the known risks of AI in the workplace and identifies DOL-enforced statutes that could be used to address them through regulations, subregulatory guidance, and enforcement practices. Among other authorities, the DOL could use these statutes to ameliorate known harms by updating wage and hour regulations, guarding workers’ safety and health against the negative impacts of automated management, and ensuring that automated benefits administration is transparent and fair.

AI risks and opportunities

AI may cause harm to American workers in several known and unknown ways. Although certainly not exhaustive, the known risks can be roughly grouped into seven categories:

  • Discrimination: Algorithmic bias refers to an algorithm’s tendency toward replicating or amplifying human biases due to unrepresentative or incomplete training data or reliance on information that reflects historical inequalities.7 As one of the eight primary policies and principles of the Biden administration’s approach to AI, the 2023 executive order on AI noted: “From hiring to housing to healthcare, we have seen what happens when AI use deepens discrimination and bias, rather than improving quality of life. Artificial Intelligence systems deployed irresponsibly have reproduced and intensified existing inequities, caused new types of harmful discrimination, and exacerbated online and physical harms.”8

The May 2024 DOL “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers” lists as a priority that “AI systems should not violate or undermine workers’ … anti-discrimination and anti-retaliation protections.”9 As the Equal Employment Opportunity Commission has identified,10 algorithmic bias can be embedded in technologies that employers increasingly use to make hiring and retention decisions. Such bias can surreptitiously disadvantage workers or applicants based on any number of protected characteristics by shaping recruitment efforts toward “relevant” job seekers and narrowing the candidate pool through automated interview technology or based on historical employment data.11 For example, there is ample evidence that AI-driven interview software, which films interview responses and assesses candidates’ performance, is “definitionally discriminatory”12 against individuals with disabilities.13

  • Access to benefits: An increased use of AI in evaluating claims for benefits such as health insurance and unemployment compensation or making investment decisions in employer-sponsored retirement accounts could pose significant risk to workers’ well-being.14 This could occur because, for example, an algorithmic system denies claims at a higher rate than a human,15 or because an AI-enabled investment allocation technology could prioritize investments that trigger payment of transaction fees and commissions to a brokerage over investments that would maximize an employee’s retirement savings.16
  • Safety and health: As GFI has documented in its prior regulatory advocacy work, electronic surveillance and automated management (ESAM) can pose risks to workers’ physical and mental safety and health.17 Employers’ unrestrained use of ESAM can result in an unsustainable pace of work that increases accident rates and musculoskeletal strain.18 The Office of Management and Budget (OMB) M-24-10 memorandum on “Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence” specifically identified AI used to “control or significantly influence the outcomes of … physical movements of robots or robotic appendages within a workplace, school, housing, transportation, medical, or law enforcement setting” as presumed to be safety-impacting.19 ESAM can also heighten mental health stress for workers as they labor under extreme pressure with little privacy.20 As ESAM technologies become more sophisticated, they create even more risks to mental health—for instance, by increasing pressure on workers via technology that detects and measures emotions and thoughts. This particular risk was cited as an AI purpose presumed to be rights-impacting by the OMB M-24-10 AI memo.21 The May 2024 DOL AI principles prioritize that “AI systems should not violate or undermine workers’ … health and safety rights.”22
  • Wage and hour compliance: AI and the remote, on-demand work that it can enable raise thorny questions about employers’ obligations under wage and hour laws. As technology blurs the line between work and nonwork time, it may become more difficult to assess what time is compensable, and it therefore should be taken into account in assessing compliance with minimum wage and overtime laws.23 Additionally, if AI takes over tasks that involve discretion, creativity, and supervision, or if automated timekeeping software automatically reduces wages for time spent off-task, workers who previously were not eligible for overtime compensation may become eligible.24 Other risks include opacity and manipulation in algorithmic wage-setting technologies25 and digital wage theft enabled by an outdated regulatory regime.26 The May 2024 DOL AI principles highlight as a priority that “AI systems should not violate or undermine workers’ … wage and hour rights.”27
  • Misclassification: Most federal laws that set labor standards apply only to employees, rather than independent contractors.28 Whether a worker is an employee or an independent contractor, as well as whether an indirect employer—for example, a parent company—counts as an employer for statutory purposes, is largely determined based on the amount of control an entity possesses over the worker.29 AI-enabled, always-on ESAM makes it easier for companies to exert control over workers while avoiding the traditional hallmarks of employer control, such as on-site, human supervision.30 If companies are able to avoid being classified as a joint employer of a worker or retain independent contractor status for their workers by supplanting traditional modes of control with virtual control enabled by ESAM, they may skirt their obligations under a host of employment laws.31 For example, McDonald’s has long argued that it is not the joint employer of employees in franchised stores despite the tight control that headquarters exerts over franchise employees by tracking their productivity through point-of-sale technology.32
  • Worker power and datafication: AI can disempower workers by disrupting organizing efforts33 through, for example, surveillance and scheduling tricks and by accelerating “worker datafication.” This refers to employers’ ravenous collection, use, and resale of workers’ data without regard for workers’ ownership of, privacy regarding, or ability to benefit from the data.34 The May 2024 DOL AI principles prioritize that “AI systems should not violate or undermine workers’ right to organize” and that “Workers’ data collected, used, or created by AI systems should be limited in scope and location, used only to support legitimate business aims, and protected and handled responsibly.”35
  • Workforce training and displacement: When people think about AI’s impact on workers, a common first thought is the potential for mass layoffs and job displacement. According to one estimate, activities that account for up to 30 percent of the hours currently worked across the U.S. economy could be automated.36 Of course, the automation of existing jobs is only part of the story, as experts expect AI to create a new wave of jobs associated with the technological revolution, for which American workers must be prepared. The World Economic Forum estimated in 2020 that while AI would displace 85 million jobs worldwide by 2025, the technology would also create 97 million new roles.37 However, even if the net impact on jobs is positive, there is still the potential for significant point-in-time job losses or net losses in particular geographies, possibly at a more rapid pace than the United States has experienced before.38 The DOL AI principles note the “risks that workers will be displaced entirely from their jobs by AI” and highlight “Supporting Workers Impacted by AI” as a principle, saying that “[e]mployers should support or upskill workers during job transitions related to AI.”39

The application of AI in the realm of employment law is not all bad for workers. The technology holds great promise for federal agencies, including the DOL, to augment their enforcement capabilities. For instance, it could be used to analyze reams of wage and hour data, trace patterns, and help identify employers for further investigation of potential statutory violations—for example, failure to report expenditures on union avoidance consultants—and to ensure payment of prevailing, minimum, or overtime wages. In particular, the use of AI for analyzing, investigating, and auditing prevailing wage enforcement represents an early opportunity, given the existing data on wages and benefits. Rapid data collection and analysis fueled by AI could help occupational safety and health experts draw conclusions about workplace characteristics and job conditions that are most likely to lead to injury and illness.40 New research highlights how AI-aided enforcement strategies could dramatically reduce workplace injuries.41 AI could also be used to spotlight further review instances where investment decisions and employee benefit determinations may be rigged against workers.

Current state

The DOL has already taken promising action on AI and plans to take more. For example, it published a blog post explaining what the White House’s AI Bill of Rights means for workers.42 The Office of Federal Contract Compliance Programs (OFCCP) collects information from federal contractors about their use of AI in recruitment, screening, and hiring.43 The Office of Disability Employment Policy funds various projects related to AI in employment, such as the Partnership on Employment and Accessible Technology’s “AI & Disability Inclusion Toolkit.”44

The 2023 executive order on AI also directed the DOL to take several steps, including preparing reports for the president and publishing guidance about wage and hour and health and safety risks related to AI.45 In response, the DOL issued a field assistance bulletin in April 2024 that describes how various federal labor standards apply to employers who use AI to manage their workforces.46 For example, the guidance document addresses how AI-enabled employee monitoring tools that track keystrokes and other activities could unlawfully deprive workers of compensation for working time spent on noncomputer tasks.47 Additionally, the bulletin highlights the potential danger of embedding errors in automated employment tools because of the potential to affect a large group of workers quickly.48

In response to the 2023 executive order on AI, the Department of Labor’ published “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers” in May 2024.49 These eight principles include a North Star of “Centering Worker Empowerment,” along with priorities that include ethical AI development, transparency, and protection of labor and employment rights.50

The executive order also directed the DOL to issue guidance for “[f]ederal contractors regarding nondiscrimination in hiring involving AI and other technology-based hiring systems,”51 which the DOL released in May 2024 as the “Artificial Intelligence and Equal Employment Opportunity for Federal Contractors.”52 The guidance includes a discussion of the types of bias that can be embedded in algorithmic decision-making processes and explains how federal contractors are responsible for compliance with nondiscrimination statutes regardless of whether their hiring decisions involve automation.53 Additionally, the guidance explicitly states that federal contractors cannot delegate compliance responsibilities to outside entities—including vendors—and provides several promising practices to maintain compliance.54

Finally, the OMB M-24-10 AI memo—primarily applicable to agencies’ procurement of AI software—focused on AI use cases that are rights-impacting, including:

… [d]etermining the terms or conditions of employment, including pre-employment screening, reasonable accommodation, pay or promotion, performance management, hiring or termination, or recommending disciplinary action; performing time-on-task tracking; or conducting workplace surveillance or automated personnel management.55

The jurisdiction of the DOL in enforcing an array of statutes is limited, at least in part, by the department’s interpretation of the statutes’ definitions of “employee” and “employer.”56 By the DOL’s terms, the laws typically do not protect individuals working as independent contractors and instead only apply to employees. Additionally, an employer can only be held accountable concerning the statutory rights of an employee if they are found to be in an employment relationship with a particular worker.57 This distinction comes into play particularly when a lead firm contracts parts of its workforce to subcontractors or franchisees. While statutes vary, a key factor in determining whether a worker is an independent contractor or an employee and whether a lead firm is a joint employer of a subcontractor’s employee is the amount of control that the employer exercises or has the authority to exercise over the worker.58

The preamble to the DOL’s rule defining “employee” under the FLSA, and therefore also the FMLA,59 recognizes this connection. It explicitly states that “whether the employer uses technological means of supervision (such as by means of a device or electronically)” is a “[fact] relevant to the employer’s control over the worker.”60 The preamble to the rule also discussed the role that electronic monitoring plays in a control analysis.61 The DOL could also consider explicitly recognizing the use of ESAM as an indicator of control for joint employer recognition under employment statutes.62 As GFI explained in a comment to the National Labor Relations Board (NLRB) in 2023, surveillance practices allow lead firms to tightly control their subcontractors’ or franchisees’ employees with whom the companies disclaim having an employment relationship.63 Ensuring that control exerted and reserved by ESAM systems is considered in joint employer analyses, even in the absence of traditional hallmarks of employer control—such as on-site, real-time, human supervision—will ensure workers can hold entities that control them accountable for the entities’ obligations under employment law.

Relevant statutory authorities

This section explains how some statutes currently enforced by the DOL could apply to AI. As explained in the introduction to this report, this list is by no means exhaustive, and each potential proposal would benefit from additional research and vetting.

Fair Labor Standards Act: Recordkeeping and reporting

At 29 U.S.C. § 211(c), the FLSA requires employers to “make, keep, and preserve” records of “wages, hours, and other conditions and practices of employment” and submit reports to the Wage and Hour Division (WHD) administrator “as he shall prescribe by regulation … as necessary or appropriate for the enforcement” of the statute.64 The DOL has used this authority to issue regulations at 29 C.F.R. Part 516 that, among other things, require employers to keep records that include regular hourly rates of pay, records of retroactive payments of wages, and documentation demonstrating whether the employee qualifies for any exemptions under the FLSA.65 

At 29 U.S.C. § 211(a), the FLSA states:

The [WHD] Administrator or his designated representatives may investigate and gather data regarding the wages, hours, and other conditions and practices of employment in any industry subject to this chapter, and may enter and inspect such places and such records (and make such transcriptions thereof), question such employees, and investigate such facts, conditions, practices, or matters as he may deem necessary or appropriate to determine whether any person has violated any provision of [the FLSA], or which may aid in the enforcement of the provisions of [the FLSA.]66

Recommendations

Based on the above-cited authority, the DOL could consider the following actions:

  • Issue new recordkeeping and reporting rules, pursuant to 29 U.S.C. § 211(c), to require employer records to ensure legibility and transparency of wage determinations made by automated systems and to require periodic reports to the WHD of those records from employers using AI-driven wage and scheduling technology. Such regulations would help combat black-box wage determination and discrimination67 that can make workers’ wages unpredictable and irregular,68 as well as ensure that such wage determinations satisfy the minimum wage and overtime requirements of the FLSA. As documented by Veena Dubal, professor of law at the University of California, Irvine, many workers are subject to algorithmic management and wage setting that withholds or reduces compensation for work when doing so benefits the company.69 This can make it difficult for workers to appreciate the connection between time spent working and amount of income generated, or to understand and correct errors in their compensation, and can also result in opaque wage setting that violates minimum wage or overtime laws.70 The DOL contemplated a similar rulemaking in the early 2010s that would have required recordkeeping and disclosure to workers about their status as employees or independent contractors and detailed information about how their pay is computed, but a regulation was never proposed.71
  • Launch investigations, pursuant to its administrative subpoena power in 29 U.S.C. § 211(a),72 of employers to ensure compliance with minimum wage and overtime provisions. The WHD could prioritize investigation of employers that are noncompliant with the reporting rules mentioned, are in industries with large numbers of employee complaints, or are in industries with high penetration of automated wage and scheduling technologies. These investigations could produce valuable information about the characteristics of automated systems that make minimum wage and overtime violations more likely to occur and encourage employers’ compliance with their legal obligations under the FLSA.

Fair Labor Standards Act: Minimum wage and overtime

At 29 U.S.C. § 206(a), the FLSA requires most employers to pay most employees a minimum wage for all hours worked.73 At 29 U.S.C. § 207(a)(1), the FLSA requires most employers to pay most employees 1.5 times their regular rate of pay for all hours worked in excess of 40 hours per week.74 At 29 U.S.C. § 254(a), the Portal-to-Portal Act amended the FLSA to exempt from “hours worked” time spent commuting and time spent on “activities which are preliminary to or postliminary to” an employee’s principal activities of work.75

In addition to the statutory amendments’ attempted clarification of what time is considered compensable for minimum wage and overtime purposes, the WHD has issued several interpretive regulations, organized at 29 C.F.R. Part 785, and pieces of guidance, field assistance bulletins,76 on the subject. At 29 C.F.R. § 781.11–13, for example, the WHD explains that an employee’s time is compensable if the employer knows or has reason to know that the employee is engaged in work, and that principle applies to work completed away from the job site “or even at home.”77 Citing administrative ease, at 29 C.F.R. § 785.47, the regulations draw on judicial precedent to set forth the WHD’s de minimis rule, which exempts “insubstantial or insignificant periods of time beyond the scheduled working hours” from compensability.78 Similarly, based on administrability rationales, current regulations permit employers to round timesheets to the nearest quarter-hour.79

Besides bona fide meal breaks,80 which are not compensable, most time in a day between an employee’s first performance of a “principal” activity and when the employee ceases such activity is compensable.81 Activities that are “principal” are those that a worker is “employed to perform,” rather than those that are preliminary or postliminary, such as commuting.82

Recommendation

Based on the above-cited authority, the DOL could consider the following action:

  • Issue updated interpretive regulations at 29 C.F.R. Part 785, pursuant to 29 U.S.C. § 211(c), that allow only employers who track time manually through analog methods to engage in timesheet rounding83 and establish a presumption against application of the de minimis rule in cases where employers use highly precise timekeeping technology.84These changes would eliminate an outdated regulatory regime that allows companies to use sophisticated timekeeping technology to facilitate wage theft by exploiting rules meant to minimize the burden of pen-and-paper wage and hour calculations. Given the ubiquity and ease of digital timekeeping, there is no longer a compelling justification for allowing practices such as rounding employees’ hours to the nearest quarter-hour or failing to treat short periods of working time as compensable for minimum wage and overtime compliance.85

Unemployment compensation

The unemployment compensation system is a joint federal-state scheme that provides support through individual benefit payments.86 The federal statute establishes broad requirements for the program, but the specifics are determined by state laws, which are administered with DOL oversight.87

At 42 U.S.C. § 503(a)(1), the federal unemployment compensation statute requires states implementing laws to include “[s]uch methods of administration … as are found by the Secretary of Labor to be reasonably calculated to insure full payment of unemployment compensation when due.”88 If the DOL determines that a state violates §503(a)(1), the statute directs the DOL, at 42 U.S.C. § 503(b), to stop payment to the state unemployment agency.89 To ensure compliance, at 42 U.S.C. § 503(a)(6), the statute requires states to make reports “in such form and containing such information, as the Secretary of Labor may from time to time require, and compliance with such provisions as the Secretary of Labor may from time to time find necessary to assure the correctness and verification of such reports.”90 42 U.S.C. § 1302 directs the secretary of labor to “make and publish such rules and regulations … as may be necessary to the efficient administration of” several social welfare programs, including unemployment compensation.91

The 2023 executive order on AI specifically directs the secretary of labor to assess how unemployment insurance “could be used to respond to possible future AI-related disruptions.”92 The OMB M-24-10 AI memo specifically declares AI used for:

Making decisions regarding access to, eligibility for, or revocation of critical government resources or services; allowing or denying access—through biometrics or other means (e.g., signature matching)—to IT systems for accessing services for benefits; detecting fraudulent use or attempted use of government services; assigning penalties in the context of government benefits [to be presumptively rights-impacting and subject to specific minimum risk management practices.]93

Recommendations

Based on the above-cited authority, the DOL could consider the following actions:

  • Update quality control program regulations at 20 CFR § 602.21, pursuant to 42 U.S.C. §§ 503(a)(1) and 1302, to require states to undertake audits and submit their results to the DOL for any automated or AI-driven benefits determination system. This could help ensure that states provide unemployment compensation to individuals consistent with federal law, provide for human in-the-loop review of any algorithmic denial of benefits, and ensure fair human adjudication for appeals of those denials. The current quality control program regulations were promulgated based on this same statutory authority.94 These regulations would guard against states’ use of automated systems to deny coverage to eligible individuals (or worse, wrongfully accuse them of fraud),95 a use case cited by the OMB as presumptively rights-impacting, and therefore it should be subject to heightened scrutiny.96 This proposal is closely related to the actions directed in Section 7.2(b) of the president’s 2023 executive order on AI, which aims to ensure the equitable distribution of public benefits. For example, the executive order directs the U.S. Department of Agriculture to issue guidance to state, local, and Tribal governments that address the use of AI systems in benefits distribution. It requires such guidance to ensure that such systems, among other things, maximize program access; require governments to notify the Department of Agriculture of AI use; create opt-out opportunities for benefit denial appeal; and enable auditing to ensure equitable outcomes.97
  • Issue a new unemployment insurance program letter (UIPL) to guide states specifically on where and how AI can and should be implemented for unemployment insurance administration. This new UIPL should incorporate the minimum risk management practices for the presumed rights-impacting use of AI from the OMB M-24-10 AI memo98 and any subsequent guidance. For example, utilizing AI to flag potential fraud must be accompanied by the minimum risk practices from the OMB M-24-10 AI memo, such as carrying out AI impact assessments, testing the systems in the real world before widespread deployment, and ongoing monitoring to ensure equity.99 The DOL should clarify that these requirements extend to any vendor a state unemployment insurance system contracts with to provide services.

Occupational Safety and Health Act

Congress enacted the Occupational Safety and Health (OSH) Act with the purpose of “[assuring] so far as possible every working man and woman in the Nation safe and healthful working conditions.”100 An examination of the congressional record makes clear that Congress established the Occupational Safety and Health Administration (OSHA) because the field of occupational safety and health was changing quickly.101 Congress decided that it needed to empower a federal agency with the authority to keep up with changes in the organization of work and establish rules to protect workers. As a congressional report explained, “technological advances and new processes in American industry have brought numerous new hazards to the workplace.”102 New “processes are being introduced into industry at a much faster rate than the present meager resources of occupational health can keep up with.”103

At 29 U.S.C. § 654(a)(2), the OSH Act requires employers to comply with “occupational safety and health standards promulgated under” the law.104 At 29 U.S.C. § 652(8), the statute defines “occupational safety and health standard” as “a standard which requires conditions, or the adoption or use of one or more practices, means, methods, operations, or processes, reasonably necessary or appropriate to provide safe or healthful employment and places of employment.”105 At 29 U.S.C. § 655(b), the statute establishes how OSHA may prescribe such standards.106 OSHA has used this authority repeatedly to issue regulations at 29 C.F.R. Part 1910 that protect workers from workplace exposure to lead, ergonomic risk,107 and many other hazards. OSHA also has experience regulating and issuing guidance about mental health hazards that threaten workers.108

In addition to the law’s substantive requirements, the OSH Act requires employers to record and report information, including about workplace injuries, to OSHA. At 29 U.S.C. § 657(c)(1), the statute mandates that employers “make, keep and preserve, and make available to the Secretary [of Labor] … such records regarding his activities relating to this Act as the Secretary . . . may prescribe by regulation as necessary or appropriate for the enforcement of this Act or for developing information regarding the causes and prevention of occupational accidents and illnesses.”109 At 29 U.S.C. § 657(c)(2), the statute directs the secretary of labor to prescribe regulations “requiring employers to maintain accurate records of, and to make periodic reports on, work-related deaths, injuries and illnesses other than minor injuries.”110

At 29 U.S.C. § 671(d), the statute directs the National Institute for Occupational Safety and Health (NIOSH) to conduct, upon its own initiative or “upon the request of the Secretary” of labor or health and human services, research “necessary for the development of criteria for new and improved occupational safety and health standards.”111

Recommendations

Based on the above-cited authority, the DOL could consider the following actions:

  • Begin the standard-setting process, pursuant to 29 U.S.C. § 655(b), to regulate the use of ESAM in the workplace to the extent that it creates hazards to workers’ physical and mental safety and health. Such regulation could mitigate the increasingly unsustainable pace of work enforced by these systems, which leads to ergonomic injury and increased risk of accidents. For example, the Washington State Department of Labor and Industries has fined Amazon repeatedly for forcing its warehouse workers to work at punishing speeds that exacerbate the risk of injury.112 The state’s citations specifically reference the “direct connection” between Amazon’s ESAM and workplace musculoskeletal disorders.113 A standard on ESAM would also reduce the harmful effects that these systems can have on workers’ mental health. As early as 1987, the now-defunct U.S. Office of Technology Assessment recognized that ESAM increases employee stress, heightening job strain risk.114

Of course, OSHA’s standard-setting process is uniquely slow and resource intensive for the agency,115 and the process would need to be informed by additional research to design an effective policy. So, in the meantime, the following recommendations should be considered:

  • Issue new subregulatory guidance and bring general duty clause enforcement actions related to companies’ use of ESAM in ways that harm worker safety and health. As GFI has urged in past advocacy efforts, OSHA should follow the lead of Washington state by more directly tying ESAM use to physical and mental health hazards.116 Enforcement actions based on unsafe ESAM use could be taken because of the already ongoing DOL investigation into high injury rates at Amazon warehouses.117
  • Update existing subregulatory guidance about sector-specific ergonomic risks to include a discussion of how ESAM can increase musculoskeletal injury risk. As described in a GFI report in 2023, OSHA could update the ergonomics guidance documents for poultry processing and grocery warehousing and create a new ESAM-conscious ergonomic risks guidance document for the warehousing industry.118 The guidance could describe best practices to prevent ergonomic injuries—such as quota transparency, worker involvement in quota setting, and rest breaks—and how ESAM systems should be adjusted to accommodate those best practices.
  • Update injury reporting regulations at 29 C.F.R. Part 1904, pursuant to 29 U.S.C. § 657, revising OSHA’s log of work-related injuries and illnesses (Form 300) to collect information about automated systems used in the tasks, job roles, or workplaces in which the worker was working at the time of injury or illness. Additionally, OSHA could update Form 300 to include a column identifying when injuries are musculoskeletal.119 This would allow OSHA to develop a better understanding of the precise causal mechanisms between ESAM and these injuries and inform the substantive policymaking described above.
  • Request research from NIOSH, pursuant to 29 U.S.C. § 671(d), to fund and conduct further research to study ESAM’s effect on job strain and physical injury.120

While all policies that affect workers should benefit from workers’ input, these workplace safety recommendations should take into account the views of labor unions and other worker advocates who have been involved in regulating workplace technology for decades and have notched important wins through, for example, contract negotiations.

Employee Retirement Income Security Act: Adverse benefits determination and disclosure

Congress enacted the Employee Retirement Income Security Act (ERISA) to establish a comprehensive regulatory scheme for employee pension and welfare benefit plans, including group health insurance plans, offered by private sector employers.121 The act creates protections for plan participants and beneficiaries by setting requirements related to disclosure and reporting about decisions regarding benefit eligibility, benefit accrual, investing and plan administration, and plan funding.122

At 29 U.S.C. § 1133, the statute requires:

In accordance with regulations of the Secretary [of Labor], every employee benefit plan shall—(1) provide adequate notice in writing to any participant or beneficiary whose claim for benefits under the plan has been denied, setting forth the specific reasons for such denial, written in a manner calculated to be understood by the participant, and (2) afford a reasonable opportunity to any participant whose claim for benefits has been denied for a full and fair review by the appropriate named fiduciary of the decision denying the claim.123

At 29 U.S.C. § 1022, the statute requires that a “summary plan description of any employee benefit plan shall be furnished to participants and beneficiaries,” which shall include a description of the “circumstances which may result in disqualification, ineligibility, or denial or loss of benefits.”124 At 29 U.S.C. § 1029(c), the statute authorizes the secretary of labor to “prescribe the format and content of the summary plan description.”125

At 29 U.S.C. § 1135, the statute permits the secretary of labor to “prescribe such regulations as he finds necessary or appropriate to carry out” ERISA’s requirements.

Recommendations

Based on the above-cited authority, the DOL could consider the following actions:

  • Update regulations at 29 C.F.R. § 2560.503-1, which implement the denial-of-claims disclosure and appeal requirements at 29 U.S.C. § 1133. The current regulations state, for example, that in the case of an adverse benefit determination by a group health plan, a participant is entitled to request a copy of any “internal rule, guideline, protocol, or other similar criterion” that was relied on in making the adverse determination.126 An updated regulation could require affirmative disclosure of a plain-language description of any algorithmic determination involved in a benefits determination, as well as the results of an equity audit conducted in a manner similar to that recommended in the OMB M-24-10 AI memo.127 Additionally, the updated regulations could clarify that the appeal process authorized by 29 U.S.C. § 1133(2) and outlined at 29 C.F.R. § 2560.503-1(h) requires that appeals of benefits denials be heard by a human. This update could come as part of the DOL’s announced review of ERISA disclosures pursuant to the Setting Every Community Up for Retirement Enhancement (SECURE) Act 2.0.128
  • Update regulations at 29 C.F.R. § 2520.102-3(l) to amend the summary of plan description to include a plain language description of any automated and algorithmic systems that the plan uses to make determinations that could “result in disqualification, ineligibility, or denial or loss of benefits,”129 as well as whether the system has been externally audited or the administrator has instituted safeguards such as opt-out mechanisms for participants who would prefer human-made determinations. This would provide some transparency to workers and advocates about the decisions that plan administrators make with the help of AI-driven systems. This update could also come as part of the DOL’s announced review of ERISA disclosures pursuant to the SECURE Act 2.0.130

Employee Retirement Income Security Act: Investment advice

At 29 U.S.C. § 1104, ERISA imposes responsibilities on plan fiduciaries, who are individuals that are responsible for plan management and operations.131 Among them are the duties of prudence and loyalty.132 At 29 U.S.C. § 1104(c)(5), the statute requires default investment allocations for retirement savings plans to be “invested by the plan in accordance with regulations prescribed by the Secretary.”133 The DOL recently issued a proposed rule to revise the scope of ERISA’s coverage of investment advice fiduciaries to keep pace with the modern economy.134

Recommendations

Based on the above-cited authority, the DOL could consider the following actions:

  • Update regulations at 29 C.F.R. § 2550.404a-1(c), pursuant to 29 U.S.C. § 1104, to revise the investment duty of loyalty in light of the risks that AI-driven investment allocation technologies can create and potential conflicts of interest. The updated regulation could be similar to the Securities and Exchange Commission’s rulemaking proceedings that seek to prevent investment advisers from using algorithms that create conflicts of interest between the adviser and the investor’s retirement goals.135 Importantly, plan fiduciaries should be required to ensure that AI-driven investment advice or allocations are not improperly weighted toward decisions that maximize fees and commissions at the expense of retirement savers. Such regulations could also require an audit of any AI-driven or otherwise automated investment allocation technologies for the potential for conflicts of interest.
  • Issue new regulations, pursuant to 29 U.S.C. § 1104(c)(5), requiring algorithmic transparency and legibility to plan participants and beneficiaries for default asset allocations.136
  • Update the statutory transactions exemption at 29 C.F.R. § 2550.408g-1(b)(4), “Arrangements that use computer models,” to strengthen the existing auditing requirements and institute other AI-specific requirements, taking into account the DOL’s approach in the proposed revisions to the Prohibited Transaction Exemption 2020-02.137 Alternatively, or in addition to updating the exemption, the DOL could issue guidance that more fully describes the term “computer model” and identifies AI applications to which this exemption may apply.

Labor Management Reporting and Disclosure Act

Congress passed the Labor Management Reporting and Disclosure Act (LMRDA) to level the playing field between management and labor by providing transparency for workers, government, and advocates into the complex anti-union persuasion industry.138 The law requires a series of disclosures from unions, employers, and union-avoidance consultants and law firms to ensure that workers know the sources of the huge sums of money that go into urging them one way or another on unionization.139

At 29 U.S.C. § 433(a)(3), the LMRDA requires employers to file a report to DOL “in a form prescribed by” the secretary of labor if the employer makes “any expenditure, during the fiscal year, where an object thereof, directly or indirectly, is to interfere with, restrain, or coerce employees in the exercise of the right to organize and bargain collectively through representatives of their own choosing, or is to obtain information concerning the activities of employees or a labor organization in connection with a labor dispute involving such employer.”140 The DOL has used this authority to specify what information employers must report in LM-10 forms, including, most recently, the DOL’s proposed rule requiring employers to identify themselves as federal contractors.141Additionally, the LM-10 form instructions identify what types of transactions employers must report.142

Recommendation

Based on the above-cited authority, the DOL could consider the following action:

  • Issue a regulation or subregulatory guidance, in the form of independent guidance documents or in the LM-10 form instructions, that explains how forms of ESAM can chill workers’ exercise of their Section 7 rights under the National Labor Relations Act and when they must be reported in employers’ LM-10 forms. The use of worker surveillance to thwart organizing activities is well documented.143 The regulation or guidance could explain how that might require employers to report their expenditures on such technologies. They could reference the memo issued by the NLRB’s general counsel on the subject,144 as well as prior guidance from the DOL on surveillance reporting.145 Additional guidance may empower workers, unions, and labor watchdogs to report employer noncompliance to the DOL.

Worker Adjustment and Retraining Notification Act

Congress enacted the Worker Adjustment and Retraining Notification (WARN) Act to help workers and communities prepare for economic dislocation caused by mass job losses.146 At 29 U.S.C. § 2102, the WARN Act requires prior worker and governmental notification in the event of a plant closing or mass layoff.147 29 U.S.C § 2101(a) defines plant closing and mass layoffs to include, during any 30-day period, a plant closing resulting in employment losses of at least 50 employees; a mass layoff of at least 50 employees where the employment loss consists of at least 33 percent of employment at the site; or a mass layoff with an employment loss of 500 or more at a single site of employment, regardless of its proportion of total employment at the site or if the employment loss is part of a plant closing.148 Sixty days prior to a termination event that triggers the WARN Act, 29 U.S.C. § 2102(a) requires the employer to give written notice of the planned terminations: “(1) to each representative of the affected employees as of the time of the notice or, if there is no such representative at that time, to each affected employee; and (2) to the State or entity designated by the State to carry out rapid response activities under [the Workforce Innovation and Opportunity Act], and the chief elected official of the unit of local government within which such closing or layoff is to occur.”149

At 29 U.S.C. § 2107(a), the statute provides the DOL with the authority to “prescribe such regulations as may be necessary to carry out” the act.150 The DOL recently announced its intention to revise its implementing regulations at 20 C.F.R. Part 639 to update the definition of “single site of employment” as it relates to remote and telecommuting workers.151

Recommendation

Based on the above-cited authority, the DOL could consider the following action:

  • Update regulations at 20 C.F.R. § 639.3(i), pursuant to 29 U.S.C. § 2107(a), to explain that, in the case of a completely or primarily remote workforce, the term “single site of employment” applies to the employer’s entire workforce. In the case of algorithmic management, the DOL should clarify that all workers subject to the same or similar algorithm are considered one single site of employment. Updated regulations could also ensure that workers subject to intermittent deplatforming caused by algorithmic optimization have maximal protections possible under the WARN Act.

Family and Medical Leave Act

The Family and Medical Leave Act (FMLA) at 29 U.S.C. § 2612(a)(1)1 et seq., requires covered employers to offer most employees 12 weeks of unpaid, job-protected leave for the birth and care of a child; to care for an adopted or foster child; to care for a spouse, a child under age 18, or a parent with a serious health condition; or because the employee is unable to work due to a serious health condition.152

29 U.S.C. § 2615(a)(1) makes it unlawful for an “employer to interfere with, restrain, or deny the exercise of or the attempt to exercise, any right provided” under the act.153 29 U.S.C. § 265 authorizes the DOL to issue regulations “as are necessary to carry out” the act.154

Recommendations

Based on the above-cited authority, the DOL could consider the following actions:

  • Update regulations at 29 C.F.R. Part 825, pursuant to 29 U.S.C. §§ 2615(a)(1) and 2654, to require legibility and transparency of automated systems155 that make any determinations bearing on the allocation or approval of FMLA leave, along with any other applicable minimum practices for rights-impacting AI from the OMB M-24-10 AI memo.156 This would implement the transparency protections recommended by the White House’s AI Bill of Rights and ensure that employers’ use of automated systems does not unlawfully restrain workers’ exercise of their rights under the FMLA. Because FMLA determination algorithms are likely bound up in other human resource management systems, this proposal could also provide transparency of those benefits processes as well. Specifically, these updated regulations should require:
    • At 29 C.F.R. § 825.301, legibility and transparency around use of automated systems to make FMLA designations
    • Legibility and transparency around use of automated systems to review, request, or otherwise process certifications under 29 U.S.C. § 2613
    • Legibility and transparency around use of automated systems to provide eligibility notices, at 29 C.F.R § 825.300(b); rights and responsibilities notices, at 29 C.F.R. § 825.300(c); and designation notices, at 29 C.F.R. § 825.300(d)
    • At 29 C.F.R. § 825.302, legibility and transparency around use of automated systems for employees to provide notice of the use of leave or to transmit information around scheduling of intermittent leave under 9 U.S.C. § 2612(b) and (e)
  • Update regulations by modifying 29 C.F.R. § 825.220, pursuant to 29 U.S.C. §§ 2615(a)(1) and 2654, to prohibit employers from using FMLA data as inputs to any automated management system that may make an employment decision based, in part, on an employee’s use or nonuse of FMLA leave. This would reduce employers’ ability to weaponize employees’ data against them to retaliate for using FMLA leave. Under these recommended updated regulations, the automated management system must strictly segregate and keep confidential any information provided for FMLA certification pursuant to 29 C.F.R. § 825.500(g).
  • Update subregulatory guidance under 29 C.F.R. § 825.301(a) prohibiting automated systems from using information other than that received from the employee or the employee’s authorized spokesperson in designating FMLA leave pursuant to 29 C.F.R. § 825.301(a). Existing regulation already prohibits the conduct for employers and would also apply to automated systems used by employers, but additional clarification is essential to restrict automated systems that would improperly combine data sources.

Conclusion

Firms already rely on automated systems to manage workforces, a trend that seems likely to accelerate given the proliferation of new AI technologies. But technological innovation does not exempt employers from preexisting statutory obligations. Several statutes empower the DOL to address certain AI issues. GFI and CAP hope this chapter offers inspiration to worker advocates and policymakers interested in how the federal government could update regulatory regimes to account for the ways in which new developments in AI may affect the American workforce.

Read the fact sheet

The fact sheet lists all of the recommendations detailed in this chapter of the report.

Endnotes

  1. Office of the Law Revision Counsel, “15 USC 9401(3): Definitions,” available at https://uscode.house.gov/view.xhtml?req=(title:15%20section:9401%20edition:prelim) (last accessed May 2024).
  2. Executive Office of the President, “Executive Order 14110: Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence,” Federal Register 88 (210) (2023): 75191–75226, available at https://www.federalregister.gov/documents/2023/11/01/2023-24283/safe-secure-and-trustworthy-development-and-use-of-artificial-intelligence.
  3. Shalanda D. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence” (Washington: Office of Management and Budget, 2024), available at https://www.whitehouse.gov/wp-content/uploads/2024/03/M-24-10-Advancing-Governance-Innovation-and-Risk-Management-for-Agency-Use-of-Artificial-Intelligence.pdf.
  4. USA.gov, “U.S. Department of Labor (DOL),” available at https://www.usa.gov/agencies/u-s-department-of-labor#:~:text=The%20Department%20of%20Labor%20administers,employment%20discrimination%2C%20and%20unemployment%20insurance (last accessed February 2024).
  5. Executive Office of the President, “Executive Order 14110: Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.”
  6. The White House and European Commission, “The Impact of Artificial Intelligence on the Future of Workforces in the European Union and the United States of America” (Washington: 2022), available at https://www.whitehouse.gov/wp-content/uploads/2022/12/TTC-EC-CEA-AI-Report-12052022-1.pdf; Aurelia Glass, “Unions Give Workers a Voice Over How AI Affects Their Jobs” (Washington: Center for American Progress, 2023), available at https://www.americanprogress.org/article/unions-give-workers-a-voice-over-how-ai-affects-their-jobs/.
  7. Nicol Turner Lee, Paul Resnick, and Genie Barton, “Algorithmic bias detection and mitigation: Best practices and policies to reduce consumer harms” (Washington: Brookings Institution, 2019), available at https://www.brookings.edu/articles/algorithmic-bias-detection-and-mitigation-best-practices-and-policies-to-reduce-consumer-harms/.
  8. Executive Office of the President, “Executive Order 14110: Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.”
  9. U.S. Department of Labor, “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers,” available at https://www.dol.gov/general/AI-Principles (last accessed May 2024).
  10. U.S. Equal Employment Opportunity Commission, “Artificial Intelligence and Algorithmic Fairness Initiative,” available at https://www.eeoc.gov/ai (last accessed February 2024).
  11. Miranda Bogen, “All the Ways Hiring Algorithms Can Introduce Bias,” Harvard Business Review, May 6, 2019, available at https://hbr.org/2019/05/all-the-ways-hiring-algorithms-can-introduce-bias.
  12. Alex Engler, “The EEOC wants to make AI hiring fairer for people with disabilities,” Brookings Institution, May 26, 2022, available at https://www.brookings.edu/articles/the-eeoc-wants-to-make-ai-hiring-fairer-for-people-with-disabilities/.
  13. For example, individuals with disabilities may use body language or display facial expressions in a way that could trigger software denials.
  14. Martin Tierney, Carrie Byrnes, and Luke Habeeb, “Weighing The Risks Of AI For Employee Benefits Admin,” Law360, June 13, 2023, available at https://www.law360.com/articles/1687381/weighing-the-risks-of-ai-for-employee-benefits-admin.
  15. See, for example, Casey Ross and Bob Herman, “UnitedHealth faces class action lawsuit over algorithmic care denials in Medicare Advantage plans,” STAT, November 14, 2023, available at https://www.statnews.com/2023/11/14/unitedhealth-class-action-lawsuit-algorithm-medicare-advantage/. See also, Robert N. Charette, “Michigan’s MiDAS Unemployment System: Algorithm Alchemy Created Lead, Not Gold,” IEEE Spectrum, January 24, 2018, available at https://spectrum.ieee.org/michigans-midas-unemployment-system-algorithm-alchemy-that-created-lead-not-gold.
  16. U.S. Securities and Exchange Commission, “Conflicts of Interest Associated With the Use of Predictive Data Analytics by Broker-Dealers and Investment Advisers,” Federal Register 88 (152) (2023): 53960–54024, available at https://www.federalregister.gov/documents/2023/08/09/2023-16377/conflicts-of-interest-associated-with-the-use-of-predictive-data-analytics-by-broker-dealers-and.
  17. Governing for Impact and Center for Democracy and Technology, “Memos to the White House and federal agencies,” April 3, 2023, available at https://governingforimpact.org/wp-content/uploads/2023/04/Surveillance_Package.pdf.
  18. Ibid.
  19. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence,” Appendix I, 1.c., p. 31.
  20. Ibid. See also, Aditi Shrikant, “Companies use AI to monitor workers—45% of employees say it has a negative effect on their mental health,” CNBC, September 8, 2023, available at https://www.cnbc.com/2023/09/08/employers-using-ai-to-monitor-workers-has-negative-impact-on-employees.html; Emma Oppenheim, “Worker surveillance poses potential privacy harms,” Consumer Financial Protection Bureau, June 20, 2023, available at https://www.consumerfinance.gov/about-us/blog/worker-surveillance-poses-potential-privacy-harms/.
  21. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence,” Appendix I, 2.i., p. 32.
  22. U.S. Department of Labor, “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers.”
  23. Bradford J. Kelley, “Wage Against the Machine: Artificial Intelligence and the Fair Labor Standards Act,” Stanford Law and Policy Review 34 (261) (2023): 261–310, available at https://law.stanford.edu/wp-content/uploads/2023/06/SLPR_Kelley_34.2.261.pdf.
  24. Ibid., p. 292.
  25. Veena Dubal, “The House Always Wins: the Algorithmic Gamblification of Work,” LPE Project, January 23, 2023, available at https://lpeproject.org/blog/the-house-always-wins-the-algorithmic-gamblification-of-work/. See also, Zephyr Teachout, “Surveillance Wages: A Taxonomy,” LPE Project, November 6, 2023, available at https://lpeproject.org/blog/surveillance-wages-a-taxonomy/.
  26. Elizabeth Chika Tippett, “How Employers Profit from Digital Wage Theft Under the FLSA,” American Business Law Journal 55 (2) (2018): 315–401, available at https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3877641.
  27. U.S. Department of Labor, “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers.”
  28. U.S. Department of Labor, “Employee or Independent Contractor Classification Under the Fair Labor Standards Act,” Federal Register 89 (7) (2024): 1638–1743, available at https://www.federalregister.gov/documents/2024/01/10/2024-00067/employee-or-independent-contractor-classification-under-the-fair-labor-standards-act#:~:text=The%202021%20IC%20Rule%20explained,overtime%20pay%2C%20or%20recordkeeping%20requirements.
  29. U.S. Department of Labor, “Fact Sheet 13: Employee or Independent Contractor Classification Under the Fair Labor Standards Act (FLSA),” available at https://www.dol.gov/agencies/whd/fact-sheets/13-flsa-employment-relationship (last accessed February 2024).
  30. Governing for Impact and Center for Democracy and Technology, “Memos to the White House and federal agencies.”
  31. For more information, see Emily Andrews, Lorena Roque, and Reed Shaw, “Comments Regarding DOL’s Notice of Proposed Rulemaking on the Employee or Independent Contractor Classification Under the Fair Labor Standards Act, RIN 1235-AA43,” Center for Law and Social Policy and Governing for Impact, December 12, 2022, available at https://governingforimpact.org/wp-content/uploads/2022/12/CLASP-Governing-for-Impact-DOL-Independent-Contractor-Rule-Comment.pdf; Amaury Pineda and Reed Shaw, “Comments Regarding NLRB’s Notice of Proposed Rulemaking on the Standard for Determining Joint-Employer Status, RIN 3142-AA21,” Jobs With Justice and Governing for Impact, December 5, 2022, available at https://governingforimpact.org/wp-content/uploads/2022/12/Jobs-With-Justice-Governing-for-Impact-NLRB-Joint-Employment-Comment.pdf.
  32. See Reed Shaw, “Electronic Surveillance is Short-Circuiting Employment and Labor Law,” The Law and Political Economy Project, February 6, 2023, available at https://lpeproject.org/blog/electron-surveillance-is-short-circuiting-employment-and-labor-law/.
  33. National Labor Relations Board, “NLRB General Counsel Issues Memo on Unlawful Electronic Surveillance and Automated Management Practices,” Press release, October 31, 2022, available at https://www.nlrb.gov/news-outreach/news-story/nlrb-general-counsel-issues-memo-on-unlawful-electronic-surveillance-and.
  34. Sam Adler-Bell and Michelle Miller, “The Datafication of Employment” (New York: The Century Foundation, 2018), available at https://tcf.org/content/report/datafication-employment-surveillance-capitalism-shaping-workers-futures-without-knowledge/; Alexandra Mateescu, “Explainer: Challenging Worker Datafication” (Washington: Data & Society, 2023), available at https://datasociety.net/wp-content/uploads/2023/11/DS_Explainer-Challenging-Worker-Datafication.pdf.
  35. U.S. Department of Labor, “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers.”
  36. Kweilin Ellingrud and others, “Generative AI and the future of work in America” (Washington: McKinsey Global Institute, 2023), available at https://www.mckinsey.com/mgi/our-research/generative-ai-and-the-future-of-work-in-america. According to a report, by 2031, AI-driven conversational AI chatbots and virtual assistants are expected to handle 30 percent of basic interactions that would have otherwise been handled by a human agent (See Kelley, “Wage Against the Machine: Artificial Intelligence and the Fair Labor Standards Act,” p. 274) as well as automatic ordering at McDonald’s (See Kelley, “Wage Against the Machine: Artificial Intelligence and the Fair Labor Standards Act,” 275).
  37. World Economic Forum, “The Future of Jobs Report 2020” (Cologny, Switzerland: 2020), available at https://www3.weforum.org/docs/WEF_Future_of_Jobs_2020.pdf.
  38. Patrick Gaspard, “Patrick Gaspard’s Statement for the Senate AI Insight Forum on Workforce,” Center for American Progress, November 1, 2023, available at https://www.americanprogress.org/wp-content/uploads/sites/2/2024/01/PG-SenateAIinsight-statement.pdf.
  39. U.S. Department of Labor, “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers.”
  40. Microsoft 365 Team, “Work Smarter, Not Harder: 10 Benefits of AI in Your Workplace,” Microsoft, November 17, 2023, available at https://www.microsoft.com/en-us/microsoft-365/business-insights-ideas/resources/benefits-of-ai-in-your-workplace.
  41. Matthew S. Johnson, David I. Levine, and Michael W. Toffel, “Making Workplaces Safer Through Machine Learning,” The Regulatory Review, February 26, 2024, available at https://www.theregreview.org/2024/02/26/johnson-levine-toffel-making-workplaces-safer-through-machine-learning/; Matthew S. Johnson, David I. Levine, and Michael W. Toffel, “Improving Regulatory Effectiveness through Better Targeting: Evidence from OSHA,” American Economic Journal: Applied Economics 15 (4) (2023): 30–67, available at https://www.aeaweb.org/articles?id=10.1257/app.20200659&from=f.
  42. Tanya Goldman, “What the Blueprint for an AI Bill of Rights Means for Workers,” U.S. Department of Labor Blog, October 4, 2022, available at https://blog.dol.gov/2022/10/04/what-the-blueprint-for-an-ai-bill-of-rights-means-for-workers.
  43. Bradford J. Kelley and others, “OFCCP Preparing to Scrutinize Federal Contractors’ Use of AI Hiring Tools and Other Technology-based Selection Procedures,” Littler Mendelson P.C., September 7, 2023, available at https://www.littler.com/publication-press/publication/ofccp-preparing-scrutinize-federal-contractors-use-ai-hiring-tools-0; Office of Management and Budget, “Supply and Service Program: OMB 1250-0003” (Washington: 2023), available athttps://www.dol.gov/agencies/ofccp/manual/fccm/figures-1-6/figure-f-3-combined-scheduling-letter-and-itemized-listing.
  44. Partnership on Employment and Accessible Technology, “AI & Disability Inclusion Toolkit,” available at https://www.peatworks.org/ai-disability-inclusion-toolkit/ (last accessed February 2024).
  45. Executive Office of the President, “Executive Order 14110: Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence.”
  46. Wage and Hour Division, “Field Assistance Bulletin No. 2024-1, ‘Artificial Intelligence and Automated Systems in the Workplace under the Fair Labor Standards Act and Other Federal Labor Standards’” (Washington: U.S. Department of Labor, 2024), available at https://www.dol.gov/sites/dolgov/files/WHD/fab/fab2024_1.pdf.
  47. Ibid., p. 3.
  48. Ibid., p. 9.
  49. U.S. Department of Labor, “Artificial Intelligence and Worker Well-being: Principles for Developers and Employers.”
  50. Ibid.
  51. Executive Office of the President, “Executive Order 14110: Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence,” Section 7.3.
  52. Office of Federal Contract Compliance Programs, “Artificial Intelligence and Equal Employment Opportunity for Federal Contractors,” U.S. Department of Labor, available at https://www.dol.gov/agencies/ofccp/ai/ai-eeo-guide (last updated April 2024).
  53. Ibid.
  54. Ibid.
  55. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence,” Appendix I, 2.i., p. 32.
  56. At 29 U.S.C. § 203(d), the FLSA defines an employer to include “any person who acts, directly or indirectly, in the interest of an employer to any of the employees of such employer.” At 29 U.S.C. § 203(e)(1), the FLSA defines an “employee” as “any individual employed by an employer.” (“Employ, in turn, is defined at 29 U.S.C. § 203(e) as “suffer or permit to work”); See Legal Information Institute, “29 U.S.C. § 203 – Definitions,” available at https://www.law.cornell.edu/uscode/text/29/203 (last accessed May 2024). At 29 U.S.C. § 2611(4)(A)(ii)(I), the FMLA defines an employer to include “any person who acts, directly or indirectly, in the interest of an employer to any of the employees of such employer.” At 29 U.S.C. § 2611(3), the FMLA adopts the FLSA’s definition of “employee” and “employ”; See Legal Information Institute, “29 U.S.C. § 2611 – Definitions,” available at https://www.law.cornell.edu/uscode/text/29/2611 (last accessed May 2024).At 29 U.S.C. § 402(e), the LMRDA defines an employer to include “any person acting directly or indirectly as an employer or as an agent of an employer in relation to an employee.” At 29 U.S.C. § 402(f), the LMRDA defines an employee as “any individual employed by an employer”; See Legal Information Institute, “29 U.S.C. § 402 – Definitions,” available at https://www.law.cornell.edu/uscode/text/29/402 (last accessed May 2024). At 29 U.S.C. § 652(5), the OSH Act defines an employer as “a person engaged in a business affecting commerce who has employees.” At 29 U.S.C. § 652(6), the OSH Act defines any employee as an “employee of an employer”; See Legal Information Institute, “29 U.S.C. § 652 – Definitions,” available at https://www.law.cornell.edu/uscode/text/29/652 (last accessed May 2024).
  57. U.S. Department of Labor, “Fact Sheet 13: Employee or Independent Contractor Classification Under the Fair Labor Standards Act (FLSA).”
  58. Ibid.
  59. At 29 U.S.C. § 2611(3), the FMLA adopts the FLSA’s definition of “employee” and “employ.”
  60. U.S. Department of Labor, “Employee or Independent Contractor Classification Under the Fair Labor Standards Act,” Federal Register 87 (197) (2022): 62218–62275, available at https://www.federalregister.gov/documents/2022/10/13/2022-21454/employee-or-independent-contractor-classification-under-the-fair-labor-standards-actat 62275.
  61. U.S. Department of Labor, “Employee or Independent Contractor Classification Under the Fair Labor Standards Act,” Federal Register 89 (7) (2024): 1638–1743, p. 1698, available at https://www.federalregister.gov/documents/2024/01/10/2024-00067/employee-or-independent-contractor-classification-under-the-fair-labor-standards-act#citation-409-p1699 (explaining that “supervision can come in many different forms beyond physical ‘over the shoulder’ supervision, which may not be immediately apparent”).
  62. At OSHA, the relevant update should occur in the agency’s multiemployer policy or be codified into regulation. See Occupational Safety and Health Administration, “Multi-Employer Citation Policy,” December 10, 1999, available at https://www.osha.gov/enforcement/directives/cpl-02-00-124.
  63. Pineda and Shaw, “Comments Regarding NLRB’s Notice of Proposed Rulemaking on the Standard for Determining Joint-Employer Status, RIN 3142-AA21.”
  64. Legal Information Institute, “29 U.S.C. § 211(c) – Collection of data,” available at https://www.law.cornell.edu/uscode/text/29/211 (last accessed May 2024).
  65. Regulations also require employers to keep these records accessible to the DOL. See, generally, 29 C.F.R. § 516.2–3.
  66. Legal Information Institute, “29 U.S.C. § 211(a) – Collection of data,” available at https://www.law.cornell.edu/uscode/text/29/211 (last accessed May 2024).
  67. See Dubal, “The House Always Wins: The Algorithmic Gamblification of Work.” See also, Teachout, “Surveillance Wages: A Taxonomy.”
  68. For example, in one 2017 lawsuit against Uber, a class of drivers alleged that there was a discrepancy between their contracted rate (a fixed proportion of an often-inflated rider’s fare payment) and their actual rate (a backend mileage- and time-based rate), which resulted in systematic underpayment and breach of contract. See Dulberg v. Uber Technologies Inc. and Rasier, class action complaint, U.S. District Court for the Northern District of California, 3:17-cv-00850 (February 21, 2017), available at https://www.classaction.org/media/dulberg-v-uber.pdf.
  69. Many are misclassified as independent contractors and may be beyond the reach of the FLSA, though the DOL’s new rulemaking on independent contractor versus employee status will reduce the severity of misclassification.
  70. See Dubal, “The House Always Wins: The Algorithmic Gamblification of Work.” See also, Teachout, “Surveillance Wages: A Taxonomy.”
  71. Office of Information and Regulatory Affairs, “Right to Know Under the Fair Labor Standards Act,” available at https://www.reginfo.gov/public/do/eAgendaViewRule?pubId=201404&RIN=1235-AA04 (last accessed May 2024); Office of Information and Regulatory Affairs, “Right to Know Under the Fair Labor Standards Act,” available at https://www.reginfo.gov/public/do/eAgendaViewRule?pubId=201104&RIN=1235-AA04 (last accessed May 2024).
  72. See U.S. Department of Justice, “Report to Congress on the Use of Administrative Subpoena Authorities by Executive Branch Agencies and Entities” (Washington: 2002), available at https://www.justice.gov/archive/olp/rpt_to_congress.htm#1a for a thorough discussion of administrative subpoena powers held by executive agencies.
  73. Legal Information Institute, “29 U.S.C. § 206(a) – Minimum wage,” available at https://www.law.cornell.edu/uscode/text/29/206 (last accessed May 2024).
  74. Legal Information Institute, “29 U.S.C. §207(a)(1) – Maximum hours,” available at https://www.law.cornell.edu/uscode/text/29/207 (last accessed May 2024).
  75. Legal Information Institute, “29 U.S.C. §254(a) – Relief from liability and punishment under the Fair Labor Standards Act of 1938, the Walsh-Healey Act, and the Bacon-Davis Act for failure to pay minimum wage or overtime compensation,” available at https://www.law.cornell.edu/uscode/text/29/254 (last accessed May 2024).
  76. Wage and Hour Division, “Field Assistance Bulletin No. 2020-5: Employers’ obligation to exercise reasonable diligence in tracking employees’ hours of work” (Washington: U.S. Department of Labor, 2020), available at https://www.dol.gov/sites/dolgov/files/WHD/legacy/files/fab_2020_5.pdf.
  77. Legal Information Institute, “29 C.F.R. § 781.11-13 – General,” available at https://www.law.cornell.edu/cfr/text/29/785.11 (last accessed May 2024); Legal Information Institute, “29 C.F.R. § 781.12 – Work performed away from the job site,” available at https://www.law.cornell.edu/cfr/text/29/785.12 (last accessed May 2024); Legal Information Institute, 29 C.F.R. § 781.13 – Duty of management,” available at https://www.law.cornell.edu/cfr/text/29/785.13 (last accessed May 2024).
  78. Legal Information Institute, “29 C.F.R. § 785.47 – Where records show insubstantial or insignificant periods of time,” available at https://www.law.cornell.edu/cfr/text/29/785.47 (last accessed May 2024).
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  80. Legal Information Institute, “29 CFR 785.19 – Meal,” available at https://www.law.cornell.edu/cfr/text/29/785.19 (last accessed May 2024).
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  82. Legal Information Institute, “29 C.F.R. § 790.8 – ‘Principal’ activities,” available at https://www.law.cornell.edu/cfr/text/29/790.8 (last accessed May 2024).
  83. Legal Information Institute, “29 C.F.R. § 785.48(b).”
  84. Legal Information Institute, “29 C.F.R. § 785.47.”
  85. Tippett, “How Employers Profit from Digital Wage Theft Under the FLSA.” The regulations that permit timesheet rounding do so provided that it is used in such a manner that it “will not result, over a period of time, in failure to compensate the employees properly for all the time they have actually worked.” This does not sufficiently protect workers, however, because it turns the legality of rounding practices into a question of fact that must be demonstrated in court. This permits employers to implement the systems knowing that it will, in combination with their attendance policies, likely accrue to their benefit, but “[b]ecause it cannot be said with 100% certainty in advance that the system will systematically disfavor employees, employers can tell themselves that they are colorably complying with the rule.” See Charlotte S. Alexander and Elizabeth Tippett, “The Hacking of Employment Law,” Missouri Law Review 82 (4) (2017): 973–1022, p. 990, available at https://scholarship.law.missouri.edu/cgi/viewcontent.cgi?article=4299&context=mlr.
  86. Julie Whittaker and Katelin Isaacs, “Unemployment Insurance: Programs and Benefits” (Washington: Congressional Research Service, 2019), available at https://crsreports.congress.gov/product/pdf/RL/RL33362#:~:text=The%20cornerstone%20of%20this%20income,income%20support%20are%20more%20specialized.
  87. Congressional Research Service, “The Fundamentals of Unemployment Compensation” (Washington: 2023), available at https://crsreports.congress.gov/product/pdf/IF/IF10336.
  88. Legal Information Institute, “42 U.S.C. § 503(a)(1) – State laws,” available at https://www.law.cornell.edu/uscode/text/42/503 (last accessed May 2024).
  89. Ibid., § 503(b).
  90. Ibid., § 503(a)(6).
  91. Legal Information Institute, “42 U.S.C. § 1302 – Rules and regulations; impact analyses of Medicare and Medicaid rules and regulations on small rural hospitals,” available at https://www.law.cornell.edu/uscode/text/42/1302 (last accessed May 2024).
  92. This is specifically mentioned as part of the report that the DOL must submit to the president as part of the October 2023 executive order on AI, at Section 6(a)(ii)(A).
  93. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence,” Appendix I, 2.i., p. 32.
  94. The Reagan-era DOL finalized these regulations despite commenters’ arguments that they exceeded the scope of the DOL’s authority. See S. Department of Labor, “Final Rule, Federal-State Unemployment Compensation Program; Unemployment Insurance Quality Control Program,” Federal Register 52 (171) (1987): 33506–33522, available at https://archives.federalregister.gov/issue_slice/1987/9/3/33506-33533.pdf.
  95. See, for example, Charette, “Michigan’s MiDAS Unemployment System: Algorithm Alchemy Created Lead, Not Gold.”
  96. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence,” Appendix I, 2.l., p. 33.
  97. Executive Office of the President, “Executive Order 14110: Safe, Secure, and Trustworthy Development and Use of Artificial Intelligence,” at Section 7.2(b).
  98. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence,” at 5.c., pp. 15–24.
  99. Ibid., at 5.c.iv.A.,5.c.iv.B and 5.c.i.v.C, pp. 17–23.
  100. Legal Information Institute, “29 U.S.C. § 651(b) – Congressional statement of findings and declaration of purpose and policy,” available at https://www.law.cornell.edu/uscode/text/29/651 (last accessed May 2024).
  101. David Michaels, “Letter to OSHA on Mental Health,” Governing for Impact, September 20, 2023, p. 7, available at https://governingforimpact.org/wp-content/uploads/2023/09/Letter-to-OSHA-on-Mental-Health.pdf.
  102. Senate Report 91-1282: Occupational Safety and Health Act of 1970, 91st Cong., 2nd sess. (October 5, 1970), on file with authors.
  103. Ibid.
  104. Legal Information Institute, “29 U.S.C. § 654(a)(2) – Duties of employers and employees,” available at https://www.law.cornell.edu/uscode/text/29/654 (last accessed May 2024).
  105. Legal Information Institute, “29 U.S.C. § 652(8) – Definitions,” available at https://www.law.cornell.edu/uscode/text/29/652 (last accessed May 2024).
  106. Legal Information Institute, “29 U.S.C. § 655(b) – Standards,” available at https://www.law.cornell.edu/uscode/text/29/655 (last accessed May 2024).
  107. The ergonomics standard was repealed by Congress through a joint resolution under the Congressional Review Act.
  108. Michaels, “Letter to OSHA on Mental Health,” pp. 8–9; Occupational Safety and Health Administration, “Workplace Stress: Make Work Better – Mental Health Matters,” available at https://www.osha.gov/workplace-stress (last accessed March 2024); EHS Today, “Regulatory Update: OSHA Aims to Prevent Construction Industry Suicides,” September 5, 2022, available at https://www.ehstoday.com/construction/article/21250223/regulatory-update-osha-aims-to-prevent-construction-industry-suicides; Occupational Safety and Health Administration, “Occupational Injury and Illness Recording and Reporting Requirements,” Federal Register 66 (13) (2001): 5916–5919, available at https://www.federalregister.gov/documents/2001/01/19/01-725/occupational-injury-and-illness-recording-and-reporting-requirements (requiring that employers record and report workplace mental injuries for which employees provide a doctor’s note vouching that the injury is work-related and noting that it had “required the recording of [mental health] illnesses since the inception of the OSH Act” and collecting the information is crucial to “assess[ing] occupational hazards”).
  109. Legal Information Institute, “29 U.S.C. § 657(c)(1) – Inspections, investigations, and recordkeeping,” available at https://www.law.cornell.edu/uscode/text/29/657 (last accessed May 2024).
  110. Ibid., § 657(c)(2).
  111. Legal Information Institute, “29 U.S.C. § 671(d) – National Institute for Occupational Safety and Health,” available at https://www.law.cornell.edu/uscode/text/29/671 (last accessed May 2024).
  112. Lauren Rosenblatt, “Fine with fines? Amazon isn’t making enough changes to protect warehouse workers, Washington state says,” Tech Xplore, March 29, 2022, available at https://techxplore.com/news/2022-03-fine-fines-amazon-isnt-warehouse.html.
  113. Washington State Department of Labor and Industries, “Citation and Notice: Amazon Com Services,” May 4, 2021, available at https://s3.documentcloud.org/documents/20787752/amazon-dupont-citation-and-notice-may-2021.pdf.
  114. Office of Technology Assessment, “The Electronic Supervisor: New Technology, New Tensions” (Washington: U.S. Government Printing Office, 1987), available at https://ota.fas.org/reports/8708.pdf. See, generally, Governing for Impact and Center for Democracy and Technology, “Memos to the White House and federal agencies.”
  115. David Michaels and Jordan Barab, “The Occupational Safety and Health Administration at 50: Protecting Workers in a Changing Economy,” American Journal of Public Health 110 (5) (2020): 631–635, available at https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144438/; U.S. Government Accountability Office, “Report to Congressional Requesters: Workplace Health and Safety: Multiple Challenges Lengthen OSHA’s Standard Setting” (Washington: 2012), available at https://www.gao.gov/assets/gao-12-330.pdf.
  116. Governing for Impact and Center for Democracy and Technology, “Memos to the White House and federal agencies.”
  117. U.S. Department of Labor, “US Department of Labor finds Amazon exposed workers to unsafe conditions, ergonomic hazards at three more warehouses in Colorado, Idaho, New York,” Press release, February 1, 2023, available at https://www.osha.gov/news/newsreleases/national/02012023. While making up roughly one-third of the national warehouse workforce, Amazon workers account for 49 percent of all warehouse injuries in the country. See Mitchell Clark, “Amazon workers made up almost half of all warehouse injuries last year,” The Verge, April 12, 2022, available at https://www.theverge.com/2022/4/12/23022107/amazon-warehouse-injuries-us-half.
  118. Governing for Impact and Center for Democracy and Technology, “Memos to the White House and federal agencies.”
  119. After Congress used the Congressional Review Act in 2001 to repeal the ergonomics rule, OSHA finalized an injury reporting rule to add a musculoskeletal disorders (MSD) column to the log of work-related injuries and illnesses (Form 300). After President George W. Bush’s inauguration, OSHA repeatedly delayed the implementation of and eventually rescinded the rule in 2003. The Obama administration began work on a proposal to include an MSD column but backtracked in 2011 due to concerns from small businesses. See U.S. Department of Labor, “US Labor Department’s OSHA temporarily withdraws proposed column for work-related musculoskeletal disorders, reaches out to small businesses,” Press release, January 25, 2011, available at https://www.osha.gov/news/newsreleases/national/01252011; Occupational Safety and Health Administration, “Occupational Injury and Illness Recording and Reporting Requirements” (Washington: U.S. Department of Labor, 2003), available at https://www.osha.gov/laws-regs/federalregister/2003-06-30.
  120. Governing for Impact and Center for Democracy and Technology, “Memos to the White House and federal agencies,” 02-1.
  121. Patrick Purcell and Jennifer Staman, “Summary of the Employee Retirement Income Security Act (ERISA)” (Washington: Congressional Research Service, 2009), “Summary,” available at https://crsreports.congress.gov/product/pdf/RL/RL34443/6.
  122. Ibid.
  123. Legal Information Institute, “29 U.S.C. § 1133 – Claims procedure,” available at https://www.law.cornell.edu/uscode/text/29/1133 (last accessed May 2024).
  124. Legal Information Institute, “29 U.S.C. § 1022 – Summary plan description,” available at https://www.law.cornell.edu/uscode/text/29/1022 (last accessed May 2024).
  125. Legal Information Institute, “29 U.S.C. § 1029(c) – Forms,” available at https://www.law.cornell.edu/uscode/text/29/1029 (last accessed May 2024).
  126. Legal Information Institute, “29 C.F.R. § 2560.503-1(g)(1) – Claims procedure,” available at https://www.law.cornell.edu/cfr/text/29/2560.503-1 (last accessed May 2024).
  127. Young, “M-24-10 Memorandum For The Heads Of Executive Departments And Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence,” at 5.c.v.A., p. 21.
  128. Office of Information and Regulatory Affairs, “Improving Participant Engagement and Effectiveness of ERISA Retirement Plan Disclosures,” available at https://www.reginfo.gov/public/do/eAgendaViewRule?pubId=202310&RIN=1210-AC09 (last accessed May 2024).
  129. Legal Information Institute, “29 U.S.C. § 1022(b) – Summary plan description.”
  130. Office of Information and Regulatory Affairs, “Improving Participant Engagement and Effectiveness of ERISA Retirement Plan Disclosures.”
  131. Legal Information Institute, “29 U.S.C. § 1104 – Fiduciary duties,” available at https://www.law.cornell.edu/uscode/text/29/1104 (last accessed May 2024).
  132. Ibid., § 1104(a)(1) (explaining that “a fiduciary shall discharge his duties with respect to a plan solely in the interest of the participants and beneficiaries and … with the care, skill, prudence, and diligence under the circumstances then prevailing that a prudent man acting in a like capacity and familiar with such matters would use in the conduct of an enterprise of a like character and with like aims”).
  133. Ibid., § 1104(c)(5).
  134. Employee Benefits Security Administration, “Retirement Security Rule: Definition of an Investment Advice Fiduciary,” Federal Register 88 (212) (2023): 75890–75979, available at https://www.federalregister.gov/documents/2023/11/03/2023-23779/retirement-security-rule-definition-of-an-investment-advice-fiduciary.
  135. U.S. Securities and Exchange Commission, “Fact Sheet: Conflicts of Interest and Predictive Data Analytics” (Washington: 2023), available at https://www.sec.gov/files/34-97990-fact-sheet.pdf.
  136. Amy Caiazza, Rob Rosenblum, and Danielle Sartain, “Investment Advisers’ Fiduciary Duties: The Use of Artificial Intelligence,” Harvard Law School Forum on Corporate Governance, June 11, 2020, available at https://corpgov.law.harvard.edu/2020/06/11/investment-advisers-fiduciary-duties-the-use-of-artificial-intelligence/.
  137. Employee Benefits Security Administration, “Proposed Amendment to Prohibited Transaction Exemption 2020-02,” Federal Register 88 (212) (2023): 75979–76003, available at https://www.federalregister.gov/documents/2023/11/03/2023-23780/proposed-amendment-to-prohibited-transaction-exemption-2020-02; Fred Reish, “The New Fiduciary Rule (8): Special Issues—Robo Advice and Investment Education,” JD Supra, December 4, 2023, available at https://www.jdsupra.com/legalnews/the-new-fiduciary-rule-8-special-issues-9929375/.
  138. Office of Labor-Management Standards, “Labor Management Reporting and Disclosure Act,” available at https://www.dol.gov/agencies/olms/compliance-assistance/fact-sheet/lmrda#:~:text=The%20Labor%2DManagement%20Reporting%20and,of%20Rights%20for%20union%20members (last accessed February 2024).
  139. Ibid.
  140. Legal Information Institute, “29 U.S.C. § 433(a)(3) – Report of employers,” available at https://www.law.cornell.edu/uscode/text/29/433 (last accessed May 2024).
  141. Office of Labor-Management Standards, “Revision of the Form LM-10 Employer Report,” Federal Register 88 (144) (2023): 49230–49265, available at https://www.federalregister.gov/documents/2023/07/28/2023-15510/revision-of-the-form-lm-10-employer-report.
  142. Office of Labor-Management Standards, “Instructions For Form LM-10 Employer Report,” available at https://www.dol.gov/sites/dolgov/files/OLMS/regs/compliance/GPEA_Forms/instructions/lm-10_instructions_final_11.23.pdf (last accessed May 2024).
  143. See, for example, Jo Constantz, “‘They Were Spying On Us’: Amazon, Walmart, Use Surveillance Technology to Bust Unions,” Newsweek, December 13, 2021, available at https://www.newsweek.com/they-were-spying-us-amazon-walmart-use-surveillance-technology-bust-unions-1658603; Indigo Oliver, “McDonald’s spies on union activists – that’s how scared they are of workers’ rights,” The Guardian, March 2, 2021, available at https://www.theguardian.com/commentisfree/2021/mar/02/mcdonalds-unions-workers-rights#:~:text=This%20includes%20using%20data%20collection,the%20Chicago%20and%20London%20offices%E2%80%9D.&text=This%20comes%20after%20years%20of,unionization%20of%20their%20o.
  144. National Labor Relations Board, “NLRB General Counsel Issues Memo on Unlawful Electronic Surveillance and Automated Management Practices.”
  145. U.S. Department of Labor, “OLMS Fact Sheet: Form LM-10 Employer Reporting Transparency Concerning Persuader, Surveillance, and Unfair Labor Practice Expenditures” (Washington: 2022), available at https://www.dol.gov/sites/dolgov/files/OLMS/regs/compliance/LM10_FactSheet.pdf?_ga=2.185647721.1329945632.1706553922-76066306.1688999107; Jeffrey Freund, “How We’re Ramping Up Our Enforcement of Surveillance Reporting,” U.S. Department of Labor Blog, September 15, 2022, available at https://blog.dol.gov/2022/09/15/how-were-ramping-up-our-enforcement-of-surveillance-reporting.
  146. U.S. Department of Labor, “Plant Closings and Layoffs,” available at https://www.dol.gov/general/topic/termination/plantclosings#:~:text=Worker%20Adjustment%20and%20Retraining%20Notification%20Act%20(WARN)%20(29%20USC,plant%20closings%20and%20mass%20layoffs(last accessed February 2024).
  147. Legal Information Institute, “29 U.S.C. § 2102 – Notice required before plant closings and mass layoffs,” available at https://www.law.cornell.edu/uscode/text/29/2102 (last accessed May 2024).
  148. Linda Levine, “Worker Adjustment and Retraining Notification (WARN) Act: A Primer” (Washington: Congressional Research Service, 2023), p. 2, available at https://crsreports.congress.gov/product/pdf/R/R42693/8; Legal Information Institute, “29 U.S.C. § 2101(a)(2)–(3) – Definitions; exclusions from definition of loss of employment,” available at https://www.law.cornell.edu/uscode/text/29/2101 (last accessed May 2024).
  149. Legal Information Institute, “29 U.S.C. § 2102(a) – Notice required before plant closings and mass layoffs.”
  150. Legal Information Institute, “29 U.S.C. § 2107(a) – Authority to prescribe regulations,” available at https://www.law.cornell.edu/uscode/text/29/2107 (last accessed May 2024).
  151. Office of Information and Regulatory Affairs, “Worker Adjustment and Retraining Notification; Amendments for Clarifications,” available at https://www.reginfo.gov/public/do/eAgendaViewRule?pubId=202310&RIN=1205-AC17 (last accessed May 2024).
  152. Gerald Mayer, “The Family and Medical Leave Act (FMLA): An Overview” (Washington: Congressional Research Service, 2012), available at https://sgp.fas.org/crs/misc/R42758.pdf.
  153. Legal Information Institute, “29 U.S.C. § 2615(a)(1) – Prohibited acts,” available at https://www.law.cornell.edu/uscode/text/29/2615 (last accessed May 2024).
  154. Legal Information Institute, “29 U.S.C. § 2654 – Regulations,” available at https://www.law.cornell.edu/uscode/text/29/2654 (last accessed May 2024).
  155. See, for example, Ecotime by HBS, “Ensure Time-Savings and Compliance With FMLA Software,” available at https://ecotimebyhbs.com/solutions/fmla/ (last accessed February 2024).
  156. Young, “M-24-10 Memorandum for the Heads of Executive Departments and Agencies: Advancing Governance, Innovation, and Risk Management for Agency Use of Artificial Intelligence.”

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