New York City issues final rules on Automated Employment Decision Tools (AEDT)

On April 6, 2023, the New York City Department of Consumer and Worker Protection (“Department”) issued its final rules regarding automated employment decision tools (“AEDT”). The AEDT law’s enactment was initially introduced under Local Law 144 of 2021, which prohibited employers and employment agencies from using AEDT unless they met certain requirements.

Overview of Local Law 144 of 2021: AEDT Law

The Local Law 144 of 2021, introduced in New York City, regulates how employers and employment agencies use automated employment decision tools (AEDTs) for hiring, promotions, job performance evaluations, and termination of employment. The ordinance requires that employers take measures to keep their AEDTs transparent, unbiased and that they have a valid reason for use.

An expanded definition of AEDT could be that it involves the application of machine learning, statistical modeling, data analytics, or artificial intelligence.

The final rules introduced by the Department of Consumer and Worker Protection expand the AEDT definition from initial machine learning to include statistical modeling, data analytics, and artificial intelligence. The expanded definition of AEDT ensures that employers of different types and sizes that use automated systems for employment practices come under regulatory scrutiny.

Permitted exclusions from bias audits: categories comprising less than 2% of data

One of the critical final rules laid out by the Department of Consumer and Worker Protection permits independent audits to exclude a category that comprises less than 2% of the data used for calculating the bias audit’s impact ratio. This rule eases compliance concerns for employers and employment agencies that use AEDT for employment practices in specific industries such as small businesses.

Examples of bias audits for AEDT

1. Conduct a gender bias audit by analyzing language used in job descriptions and performance evaluations to ensure that gender-neutral language is used and that evaluations are free of gender bias.

2. Conduct a cultural bias audit by reviewing training materials and policies to ensure that they are inclusive of different cultures and do not discriminate against any specific cultural group.

3. Conduct a disability bias audit by reviewing the accessibility of workplace facilities and policies to guarantee that they are accessible to employees with disabilities.

4. Conduct a racial bias audit by reviewing the language used in job descriptions, performance evaluations, policies, and procedures to guarantee that they are free of racial bias and do not discriminate against any specific racial group.

5. Conduct an age bias audit by reviewing policies and practices to make sure they do not discriminate against employees on the basis of their age, and that the language used is age-neutral.

The Department of Consumer and Worker Protection has included several examples of bias audits in the Final Rules. These examples will guide employers and employment agencies on the measures they can take to ensure compliance with AEDT requirements. The audits will enable employers to determine whether their automated systems have unintentional biases that prevent certain groups from being treated fairly.

Relying on Bias Audits Using Historical or Test Data from Other Employers or Employment Agencies

The Final Rules also provide guidance on when an employer or employment agency may rely on a bias audit conducted using historical data or test data from other employers or employment agencies. This guidance is particularly helpful for new entrants, small businesses, and under-resourced companies to comply with ADEA requirements in a cost-effective manner.

Compliance Deadline: AEDT Law Goes into Effect on April 15th, 2023.

With the regulatory roadmap laid out by the Department of Consumer and Worker Protection through the Final Rules, employers and employment agencies have the necessary information to begin complying with AEDT law when it goes into effect on April 15, 2023, next week. Employers who use automated systems in their hiring and employment practices must take swift measures to ensure transparency and fairness.

Monitoring regulatory and enforcement updates: data analytics, privacy, data, and cybersecurity practices

The Data Analytics and Privacy, Data, and Cybersecurity practices of Jackson Lewis P.C. will continue to monitor regulatory and enforcement updates necessary to protect employers from risks and potential liability. As ADEA law and regulations evolve, incorporating trends in technologies and employment practices, Jackson Lewis P.C. will provide the necessary guidance to ensure compliance.

Assistance with navigating AEDT law: Contact any member of Jackson Lewis P.C.

Employers and employment agencies that require assistance with navigating the ADEA law or the Final Rules may contact any member of Jackson Lewis P.C. Our team of experts provides practical legal analysis and advice to help navigate the complexities of ADEA regulations.

The Final Rules introduced by the New York City Department of Consumer and Worker Protection provide a much-needed regulatory roadmap for employers and employment agencies that use Automated Employment Decision Tools (AEDT). The expansion of the definition of AEDT, rules permitting exclusions from bias audits, examples of bias audits, guidance on relying on recent data sets, and a compliance deadline are essential components of AEDT regulation. Jackson Lewis P.C. will continue to monitor regulatory and enforcement updates and is ready to provide assistance to employers and employment agencies that require guidance.

Explore more

How DevOps Solves Multi-Cloud Infrastructure Challenges

High-stakes technology leaders often find that the very redundancy meant to protect their systems from localized provider failures actually introduces a paralyzing layer of complexity across the entire operational stack. When a single service outage at a major cloud provider can paralyze a global enterprise, distributing workloads across multiple providers seems like the logical remedy. However, this strategy frequently transforms

What Is the Roadmap to Becoming a DevOps Engineer in 2026?

The current state of modern infrastructure requires a deep understanding of systemic integration that goes far beyond simply knowing how to use a handful of popular software applications. Aspiring engineers frequently encounter a paradox where they possess knowledge of specific tools yet struggle to orchestrate a seamless deployment pipeline in a live production environment. This disconnect occurs because the industry

New Payment Rails Unlock Financial Autonomy for AI Agents

For years, sophisticated software has been capable of suggesting the perfect vacation destination or outlining a marketing strategy, yet these digital minds have remained paralyzed when asked to actually pay for the services they propose. This gap between planning and execution represents the final frontier for artificial intelligence, marking the boundary between a tool that assists and an agent that

Asian Central Banks Set Global Standards for AI Governance

The global financial architecture is currently undergoing a quiet yet profound shift as digital intelligence replaces legacy systems to become the central nervous system of modern economic prosperity and resilience. Artificial intelligence is no longer an experimental project for tech enthusiasts; it has become the primary engine driving modern economic stability and growth. Just as the internet fundamentally changed global

How Is AI Unifying Family Office Wealth Management?

Managing a staggering one hundred and ten billion dollars in private wealth requires a level of logistical precision that often exceeds the actual financial strategies employed to grow it. Even the largest firms have historically been hamstrung by a surprisingly simple problem: disconnected data. When a client’s tax strategy, estate plan, and investment portfolio live in separate digital silos, the