We’ve all heard the horror stories.
A job seeker spends hours tailoring his resume, finally hits “submit,” and within seconds receives a rejection email in his inbox. Clearly, no human could have actually reviewed the resume. The applicant wasn’t rejected by a person; he was rejected by a pattern-matching algorithm.
The “No Robot Bosses Act” could curtail these scenarios. The bill has bipartisan support in Congress, having been co-sponsored by Democrats Suzanne Bonamici of Oregon and Christopher Deluzio of Pennsylvania, and the Republican Delegate from Guam, James Moylan.
The core premise of the proposed No Robot Bosses Act? Employers would be prohibited from relying exclusively on automated decision systems to make employment-related decisions, including whether to hire or fire.
Under the proposed law, an “automated decision system” is defined broadly as follows:
a system, software, or process that . . . uses computation, in whole or in part, to determine outcomes, make or aid decisions (including through evaluations, metrics, or scoring), inform policy implementation, or collect data or observations, including such a system software, or process derived from machine learning, statistics, or other data processing or artificial intelligence techniques.
The bill has three main components:
No. 1: Human oversight. Humans must be involved in making employment decisions. Specifically, an employer would be prohibited from relying “exclusively on an automated decision system in making an employment-related decision. . . .”
The bill defines “employment-related decision” to include actions relating to recruiting, screening, interviewing, or selecting a candidate; firing, retaining, taking disciplinary action against, demoting, or reassigning an employee; and implementing other actions affecting the terms, conditions, and privileges of employment, such as compensation, scheduling, insurance coverage, or benefits.
Any decision made by the automated decision system would have to be independently corroborated by “meaningful oversight by a human with appropriate and relevant experience.”
No. 2: Discrimination & disparate impact liability. The bill would require employers to verify that any automated decision system complies with federal anti-discrimination laws. Employers would be required to annually analyze the results of the system for discriminatory impact. This would include disproportionate effects on the basis of protected characteristics, such as race, sex, national origin, age, disability, or genetic information.
No. 3: Transparency. Employers would be required to disclose certain information when these tools are used. The following are some examples:
- When an automated decision system is being used.
- A description of the system.
- The types of data collected by the system.
- Characteristics that the system is intended to measure.
- How the applicant or employee can interpret the system output in plain language.
- How the applicant or employee can dispute the decision made.
The bill would prohibit retaliation against those who “sought assistance” or “filed a complaint” regarding the use of an automated decision system.
Finally, the bill would provide for administrative enforcement action by the U.S. Department of Labor as well as a private right of action by individuals. Statutory damages for violations of the usage rules would range from $5,000 to $20,000 per violation, rising to $40,000 for willful or repeated violations. The maximum penalties for violating the retaliation provisions are even steeper: $50,000 per violation, and $100,000 for willful violations. In addition, individuals could recover actual damages, treble damages, and attorneys’ fees in private litigation.
We are moving from an era of “move fast and break things” to an era of “prove it works before you use it.” The introduction of the No Robot Bosses Act signals that the days of cost-effective, unsupervised algorithmic filtering may be numbered.
We will continue to keep you up to date regarding this legislation as it progresses.
Contact a member of Constangy’s EEO/Contractor Compliance, Reporting & Analytics practice group today to set up a privileged EEO analysis of your current automated decision systems.
Senior CounselShe focuses her practice on complex discrimination, harassment, and wage and hour claims, including class and PAGA matters. Komal’s litigation prowess is matched by her skill in eDiscovery, where she protects client interests ...
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