Arnold Peter
Founding Partner at Peter Law Group
Date: October 13, 2026
Originally published on LinkedIn
Summary: Arnold Peter examines California’s AI employment legislation through the shared questions of innovation, accountability and human dignity. In the first installment of his series, he discusses the No Robo Bosses Act, technology-driven worker displacement, algorithmic discrimination and the importance of meaningful human review. His central argument is that AI may assist employment decisions, but it cannot relieve people of responsibility for their consequences.
This is the first article in a continuing series examining California’s new artificial intelligence legislation, its implications for businesses and individuals, and the evolving relationship between technological innovation, legal accountability, and human dignity. Future installments will examine AI legislation addressing privacy, transparency, discrimination, professional responsibility, and emerging technologies.
Part One of a Series on California’s New AI Laws: The No Robo Bosses Act, Worker Displacement, and the Future of Human Judgment
A governor in Sacramento, a president in Washington, and a pope in Rome are confronting one of the most consequential technological transformations in human history. Each approaches artificial intelligence from a different perspective, yet all three are addressing a fundamental question: How do we harness the extraordinary capabilities of AI without diminishing the dignity, autonomy, and value of human beings?
Governor Gavin Newsom has emphasized California’s responsibility to establish safeguards against AI misuse, particularly where technological decisions affect employment, privacy, and individual rights. President Donald Trump has emphasized American technological leadership, economic competitiveness, and the importance of ensuring that the United States does not fall behind China or other international competitors. Pope Leo XIV, through his encyclical Magnifica Humanitas, has emphasized human dignity, moral accountability, and the principle that technology must remain subordinate to human judgment.
These approaches are not necessarily incompatible. America can lead the development of artificial intelligence while protecting workers and consumers from its misuse. Innovation and accountability need not be mutually exclusive, nor must technological progress come at the expense of human dignity.
In an earlier post, A Governor, a President and a Pope: Who Will Define the Human Future of AI?, I examined these perspectives and suggested that their differences reveal an opportunity to establish a coherent framework for responsible technological advancement.
This is the first in a series examining California’s newly enacted AI legislation, its implications for businesses and individuals, and whether our legal institutions are prepared for a world increasingly influenced by algorithms. We begin with employment, where automated decisions can have immediate and devastating personal consequences.
Your Boss Is an Algorithm. California Just Decided That Isn’t Good Enough.
Imagine arriving at work to discover that you have been terminated. You receive no meaningful explanation, no opportunity to defend yourself, and no indication that anyone independently reviewed your performance. Instead, an algorithm analyzed your productivity, evaluated your communications, assigned you a numerical score, and concluded that your employment should end. Your supervisor may never have independently made that decision.
Until recently, this scenario might have seemed like science fiction. Today, AI increasingly influences decisions about who gets hired, promoted, disciplined, and terminated. On September 30, 2026, Governor Newsom signed Senate Bill 947 and Senate Bill 951, addressing automated employment decisions and the displacement of workers through artificial intelligence.
These laws represent more than another expansion of California’s employment regulations. They reflect a principle I have explored in my recent writings concerning AI, judicial decision-making, and human dignity: Artificial intelligence may assist human judgment, but it must never become a substitute for human responsibility.
The No Robo Bosses Act: California Draws a Line
Senate Bill 947, enacted as Chapter 859 of the Statutes of 2026, adds Labor Code sections 1520 through 1526.7. Known as the No Robo Bosses Act, it becomes operative July 1, 2027, and restricts employers’ reliance on automated decision systems in disciplinary and termination decisions.
The statute broadly defines automated decision systems to include computational processes derived from machine learning, statistical modeling, data analytics, or AI that generate scores, classifications, or recommendations used to assist or replace human discretionary decision-making. Its reach extends beyond generative AI platforms to conventional algorithmic management and employee evaluation systems.
Under Labor Code section 1522(b), employers cannot rely exclusively on automated systems when disciplining or terminating employees. When an employer primarily relies on an automated output, a human reviewer must corroborate the decision using underlying data or other relevant information, including supervisory evaluations, personnel records, employee work product, or witness interviews.
If the output cannot be corroborated, or the reviewer determines that it is inaccurate, incomplete, or misleading, the employer cannot rely on it to discipline or terminate the employee.
California is therefore requiring more than a supervisor’s signature on a computer-generated recommendation. It is imposing a substantive obligation to verify the information supporting the decision.
Nevertheless, an important question remains: What constitutes meaningful human review? A supervisor who mechanically approves an algorithm’s recommendation without independently evaluating the circumstances provides little protection. Human participation becomes an administrative formality rather than a meaningful safeguard.
An Employee’s Right to Know What the Machine Decided
One of SB 947’s most consequential provisions concerns transparency. Under Labor Code section 1524, when an employer primarily relies on an automated system to discipline or terminate an employee, it must provide a separate, plain-language written notice identifying that reliance, confirming human review and corroboration, and providing contact information for someone who can answer questions.
Under section 1522(d), employees may also request a meaningful, objective description of their own data used by the automated system, subject to protections for other individuals’ personal information.
These provisions may fundamentally change how employers document disciplinary decisions. An employee who previously received only a conclusory explanation for termination may now have a statutory basis to discover whether an algorithm materially influenced the decision and what information it evaluated.
The legislation also prohibits using automated systems to infer protected characteristics or predict and take adverse action against workers for exercising legally protected rights. An employer cannot lawfully use an algorithm to identify employees supposedly likely to file discrimination complaints or exercise workplace rights and then penalize them on that basis.
A New Frontier in Employment Litigation
Labor Code section 1526.1 establishes significant enforcement mechanisms, including proceedings by the Labor Commissioner and public prosecutors, civil penalties of $500 per violation, and specified judicial remedies that may include injunctive relief, punitive damages, and attorneys’ fees.
Particularly significant is section 1526.1(c), which establishes an evidentiary burden on employers in certain enforcement proceedings. Once the use of an automated system in a disciplinary or deactivation decision is demonstrated, the employer must establish that it did not primarily rely on the system or that it complied with applicable requirements.
This could materially change litigation involving algorithmic employment decisions. Rather than leaving employees entirely dependent upon obtaining proprietary information about a technology platform, the statute requires employers, once the applicable threshold is established, to demonstrate the nature of their reliance or compliance.
Discovery may increasingly involve algorithmic outputs, training data, validation materials, vendor communications, and evidence concerning the independence of human reviewers. The traditional wrongful termination case asks what a supervisor knew, said, or intended. The emerging AI employment case may ask what a machine calculated, why it reached its conclusion, and whether anyone verified its accuracy.
SB 951: When Artificial Intelligence Eliminates the Job Entirely
Senate Bill 951, enacted as Chapter 860 of the Statutes of 2026, addresses a different problem: What happens when artificial intelligence does not merely evaluate employees but replaces them?
SB 951 amends California’s Worker Adjustment and Retraining Notification Act, commonly known as Cal-WARN. Under the existing framework, covered employers generally must provide 60 days’ advance written notice of qualifying mass layoffs, relocations, or terminations. A covered establishment generally employs, or has employed during the preceding 12 months, at least 75 persons, while a mass layoff generally involves 50 or more employees during a 30-day period at a covered establishment.
SB 951 preserves these thresholds while adding disclosure obligations when an otherwise covered employment action is caused in whole or in substantial part by AI or other automated technology replacing or automating positions.
Under Labor Code section 1401(d), the notice must identify the number, classifications or occupations, and work locations of affected workers whose displacement is substantially attributable to automation. It must also identify the job functions being automated and the category or type of technology responsible.
The notice must prominently state: “This notice is for a technology displacement.”
Consider an entertainment studio that eliminates dozens of production, editing, administrative, or creative positions after implementing generative AI. Management might characterize the decision as an economic restructuring, while employees may contend that their positions were eliminated because technology replaced human labor.
Determining whether AI substantially caused the displacement may require examining internal communications, technology implementation plans, financial projections, and management’s decision-making process. The statute’s failure to define precisely what constitutes displacement attributable to AI “in substantial part” may itself become a source of litigation.
The entertainment industry presents additional complications because Cal-WARN contains exceptions for certain project-based employment, including qualifying work governed by broadcasting and motion picture industry wage orders.
What Happens When AI Eliminates Jobs Before Anyone Is Hired?
SB 951 also requires the Employment Development Department to publish summaries of reported technological displacements and report to the Legislature by January 1, 2028, concerning AI’s effects on hiring practices, industries, and occupations.
The required analysis includes consideration of future notice obligations when employers permanently discontinue hiring for positions because of AI.
This may prove particularly consequential. A company need not terminate employees to reduce employment opportunities. It may simply stop hiring workers for positions that AI can perform.
What happens when technology eliminates entry-level positions, reduces opportunities for young professionals, or makes certain career paths economically unsustainable? California is beginning to confront these questions, although SB 951 does not impose a general notice requirement whenever employers discontinue hiring because of automation.
When Discrimination Becomes Invisible
California’s new laws build upon regulations under the Fair Employment and Housing Act, effective October 1, 2025, addressing discrimination involving automated employment decision systems.
Imagine an AI recruiting system that consistently ranks applicants with employment gaps below other candidates. Those gaps may disproportionately affect women who interrupted their careers for caregiving, individuals with disabilities, or employees who took protected medical leave. The algorithm may never explicitly consider gender or disability, yet the information it evaluates may function as a proxy for protected characteristics.
What makes these problems particularly troubling is the apparent objectivity of technology. A manager’s prejudice may be recognizable, while an algorithm’s prejudice may arrive disguised as mathematics.
As an employment attorney, I believe these disputes will increasingly require sophisticated discovery involving algorithmic inputs, training data, validation studies, and statistical evidence. The underlying legal principle remains unchanged: An employer cannot escape responsibility for discrimination merely because the decision originated with software rather than a human supervisor.
From the Courtroom to the Workplace: The Verdict Must Remain Human
In my recent writings on AI and judicial decision-making, including The Verdict Must Remain Human, I examined whether algorithms should influence determinations of criminal responsibility.
Suppose an AI system could analyze evidence, evaluate witness credibility, and predict guilt with greater statistical accuracy than a human jury. Would that justify allowing the machine to determine whether a defendant should be convicted?
My conclusion was no, not because AI necessarily lacks analytical sophistication, but because judgment involves more than calculation. Human decision-making encompasses context, moral responsibility, compassion, and circumstances that cannot always be reduced to quantifiable variables.
The same reasoning applies to employment. An algorithm might correctly determine that an employee’s productivity declined by 15 percent, but can it adequately understand that the employee was caring for a dying parent, recovering from a serious illness, or experiencing circumstances warranting accommodation rather than punishment?
Human managers are hardly infallible. They can be prejudiced, inconsistent, and profoundly mistaken. Properly designed AI systems may help identify those weaknesses, but the answer to imperfect human judgment should be better-informed human judgment, not the abandonment of human accountability.
The algorithm may identify the problem. A human being must remain responsible for deciding what justice requires.
What a Nineteenth-Century Pope Might Teach Silicon Valley
In 1891, Pope Leo XIII issued Rerum Novarum, addressing the social and economic consequences of the Industrial Revolution. Industrialization generated extraordinary wealth but also created conditions in which human labor risked being treated primarily as an economic commodity.
Pope Leo XIII insisted that economic progress must be evaluated in light of human dignity, workers’ rights, and employers’ responsibilities. More than a century later, Pope Leo XIV confronts a remarkably similar transformation, one in which AI promises extraordinary productivity gains while potentially subordinating human workers to systems designed principally for economic optimization.
In Magnifica Humanitas, Pope Leo XIV emphasizes preserving human accountability throughout the development and use of AI. The concern is not simply whether automated systems produce accurate results, but whether human beings retain the ability to understand, challenge, and take responsibility for consequential decisions.
The historical parallel is striking. During the Industrial Revolution, the concern was whether machines would diminish the dignity of physical labor. During the Artificial Intelligence Revolution, the question is whether machines will diminish the dignity of human judgment itself.
AI can expand opportunity, improve accessibility, and liberate workers from repetitive tasks. But technological progress must remain subordinate to human purposes. An economy that becomes more productive while rendering human beings increasingly powerless over decisions affecting their lives cannot automatically be described as progress.
What Employers Must Do Now
California employers should examine their existing use of automated employment systems before SB 947 becomes operative in July 2027. They should identify technologies influencing disciplinary and termination decisions, determine whether their outputs can be independently verified, and establish documented procedures for meaningful human review.
Employers should also review disciplinary notices, personnel policies, record-retention practices, and contracts with AI vendors. For anticipated workforce reductions, they should determine whether automation projects could trigger Cal-WARN obligations and whether notices must incorporate SB 951’s technology-displacement disclosures.
These are not merely technical compliance issues. Employers may face enforcement proceedings and litigation concerning the reliability of algorithmic recommendations and whether human reviewers exercised genuinely independent judgment.
The future employment lawyer may need to question an algorithm’s reliability with the same rigor traditionally applied to a supervisor’s credibility.
The Future of Work Must Remain Human
California’s newest AI employment laws represent an important beginning, but they cannot resolve every question raised by the increasingly automated workplace. They cannot guarantee independent human judgment, eliminate economic disruption, or ensure that workers share meaningfully in the prosperity generated by AI.
Returning to the governor, the president, and the pope, their respective concerns need not be mutually exclusive. California’s interest in protecting workers, Washington’s emphasis on technological leadership, and the Vatican’s commitment to human dignity can each contribute to a more responsible understanding of technological progress.
Artificial intelligence will transform the American workplace. It may eliminate certain occupations while creating others, make businesses more efficient, and increase productivity across entire industries. We should welcome those possibilities while insisting that technological advancement remain accountable to the people it is intended to serve.
Employment is not simply a mathematical relationship between productivity and compensation. Work provides economic security, personal identity, social relationships, and opportunities for human development. Decisions affecting employment therefore implicate interests extending far beyond an employer’s balance sheet.
The question is no longer whether AI will participate in decisions affecting human lives. It already does. The question is whether we will retain the wisdom and responsibility to ensure those decisions remain fundamentally human.
A computer may recommend that an employee be fired. It should never be permitted to relieve a human being of responsibility for that decision.
Artificial intelligence may transform the future of work. It must not be allowed to erase the humanity of the worker.
Artificial intelligence may transform the future of work. It must not be allowed to erase the humanity of the worker.
Frequently Asked Questions About AI and Workplace Decisions
What is the article’s central argument?
Arnold Peter argues that AI can assist workplace decisions, but human beings must remain responsible for decisions affecting workers’ livelihoods and dignity.
What does the article say about the No Robo Bosses Act?
The article examines SB 947 and its approach to human review, corroboration and transparency when automated systems influence employee discipline or termination.
How does the article distinguish SB 951 from SB 947?
Peter discusses SB 947 in relation to automated employment decisions and SB 951 in relation to technology-driven job displacement and Cal-WARN disclosures.
Why is meaningful human review important?
Peter distinguishes independent evaluation of the underlying information from simply approving an algorithm’s recommendation. He emphasizes context, accuracy and accountability.
What risks of algorithmic discrimination does the article discuss?
The article explains how apparently neutral inputs, such as employment gaps, can function as proxies for protected characteristics and obscure discriminatory outcomes.
What should employers review, according to the article?
Peter recommends examining automated employment tools, human-review procedures, disciplinary notices, record retention, vendor contracts and plans for workforce reductions.
