JOINT STATEMENT ON ENFORCEMENT EFFORTS AGAINST 

DISCRIMINATION AND BIAS IN AUTOMATED SYSTEMS 

Rohit Chopra, Director of the Consumer Financial Protection Bureau,

Kristen Clarke, Assistant Attorney General for the Justice Department’s Civil Rights Division,

Charlotte A. Burrows, Chair of the Equal Employment Opportunity Commission, and

Lina M. Khan, Chair of the Federal Trade Commission 

issued the following joint statement about enforcement efforts to protect the public

from bias in automated systems and artificial intelligence: 

America’s commitment to the core principles of fairness, equality, and justice is

deeply embedded in the federal laws that our agencies enforce to protect civil rights, fair

competition, consumer protection, and equal opportunity. These established laws have 

long served to protect individuals even as our society has navigated emerging 

technologies. Responsible innovation is not incompatible with these laws. Indeed,

innovation and adherence to the law can complement each other and bring tangible 

benefits to people in a fair and competitive manner, such as increased access to 

opportunities as well as better products and services at lower costs.

Today, the use of automated systems, including those sometimes marketed as

“artificial intelligence” or “AI,” is becoming increasingly common in our daily lives. We 

use the term “automated systems” broadly to mean software and algorithmic processes,

including AI, that are used to automate workflows and help people complete tasks or

make decisions. Private and public entities use these systems to make critical decisions

that impact individuals’ rights and opportunities, including fair and equal access to a job,

housing, credit opportunities, and other goods and services. These automated systems

are often advertised as providing insights and breakthroughs, increasing efficiencies

and cost-savings, and modernizing existing practices. Although many of these tools

offer the promise of advancement, their use also has the potential to perpetuate

unlawful bias, automate unlawful discrimination, and produce other harmful outcomes.

Our Agencies’ Enforcement Authorities Apply to Automated Systems

Existing legal authorities apply to the use of automated systems and innovative 

new technologies just as they apply to other practices. The Consumer Financial
2 

Protection Bureau, the Department of Justice’s Civil Rights Division, the Equal 

Employment Opportunity Commission, and the Federal Trade Commission are among 

the federal agencies responsible for enforcing civil rights, non-discrimination, fair 

competition, consumer protection, and other vitally important legal protections. We take 

seriously our responsibility to ensure that these rapidly evolving automated systems are 

developed and used in a manner consistent with federal laws, and each of our agencies 

has previously expressed concern about potentially harmful uses of automated 

systems. For example:

• The Consumer Financial Protection Bureau (CFPB) supervises, sets rules 

for, and enforces numerous federal consumer financial laws and guards

consumers in the financial marketplace from unfair, deceptive, or abusive acts 

or practices and from discrimination. The CFPB published a circular

confirming that federal consumer financial laws and adverse action 

requirements apply regardless of the technology being used. The circular also 

made clear that the fact that the technology used to make a credit decision is 

too complex, opaque, or new is not a defense for violating these laws. 

• The Department of Justice’s Civil Rights Division (Division) enforces 

constitutional provisions and federal statutes prohibiting discrimination across 

many facets of life, including in education, the criminal justice system, 

employment, housing, lending, and voting. Among the Division’s other work 

on issues related to AI and automated systems, the Division recently filed a 

statement of interest in federal court explaining that the Fair Housing Act 

applies to algorithm-based tenant screening services. 

• The Equal Employment Opportunity Commission (EEOC) enforces 

federal laws that make it illegal for an employer, union, or employment 

agency to discriminate against an applicant or employee due to a person’s 

race, color, religion, sex (including pregnancy, gender identity, and sexual 

orientation), national origin, age (40 or older), disability, or genetic information 

(including family medical history). In addition to the EEOC’s enforcement 

activities on discrimination related to AI and automated systems, the EEOC 

issued a technical assistance document explaining how the Americans with 

Disabilities Act applies to the use of software, algorithms, and AI to make 

employment-related decisions about job applicants and employees.

• The Federal Trade Commission (FTC) protects consumers from deceptive 

or unfair business practices and unfair methods of competition across most 

sectors of the U.S. economy by enforcing the FTC Act and numerous other 

laws and regulations. The FTC issued a report evaluating the use and impact 

of AI in combatting online harms identified by Congress. The report outlines

significant concerns that AI tools can be inaccurate, biased, and 

discriminatory by design and incentivize relying on increasingly invasive forms 

of commercial surveillance. The FTC has also warned market participants 

that it may violate the FTC Act to use automated tools that have 
3 

discriminatory impacts, to make claims about AI that are not substantiated, or 

to deploy AI before taking steps to assess and mitigate risks. Finally, the FTC 

has required firms to destroy algorithms or other work product that were 

trained on data that should not have been collected.

Automated Systems May Contribute to Unlawful Discrimination and 

Otherwise Violate Federal Law

Many automated systems rely on vast amounts of data to find patterns or 

correlations, and then apply those patterns to new data to perform tasks or make 

recommendations and predictions. While these tools can be useful, they also have the 

potential to produce outcomes that result in unlawful discrimination. Potential 

discrimination in automated systems may come from different sources, including 

problems with:

• Data and Datasets: Automated system outcomes can be skewed by 

unrepresentative or imbalanced datasets, datasets that incorporate historical 

bias, or datasets that contain other types of errors. Automated systems also 

can correlate data with protected classes, which can lead to discriminatory 

outcomes.

• Model Opacity and Access: Many automated systems are “black boxes” 

whose internal workings are not clear to most people and, in some cases, 

even the developer of the tool. This lack of transparency often makes it all the 

more difficult for developers, businesses, and individuals to know whether an 

automated system is fair. 

• Design and Use: Developers do not always understand or account for the 

contexts in which private or public entities will use their automated systems. 

Developers may design a system on the basis of flawed assumptions about 

its users, relevant context, or the underlying practices or procedures it may 

replace.

Today, our agencies reiterate our resolve to monitor the development and use of 

automated systems and promote responsible innovation. We also pledge to vigorously 

use our collective authorities to protect individuals’ rights regardless of whether legal 

violations occur through traditional means or advanced technologies. 

Note: This document is for informational purposes only and does not provide technical assistance about 

how to comply with federal law. It does not constitute final agency action and does not have an immediate 

and direct legal effect. It does not create any new rights or obligations and it is not enforceable.