Various levels of artificial Intelligence (“AI”) have been around for a long time. As computing power and speed has increased, AI programs have become larger and are used for an increasing number of functions. AI programs are now used, for example, by many businesses as part of employee recruitment, hiring, and retention. AI systems are, of course, computer programs and algorithms used to perform tasks that might otherwise be done by human beings.

However, the increasing use of AI systems is creating a number of thorny legal issues that must be resolved either through the courts or through the legislative process. As one example, in late 2021, New York City enacted an Ordinance regulating the use of AI and machine learning in hiring. See Forbes media report here. Along similar lines, the EEOC recently issued guidelines on the use of AI in hiring decisions with respect to whether such use might amount to disability discrimination.

Some common concerns involve these types of questions:

• Do AI systems that score or classify job applicants have inherent biases that create violations of anti-discrimination laws?
• Are inputs used by AI systems biased?
• Are the AI algorithms and inputs transparent enough for courts, lawmakers and the public to search for bias or even understand how outcomes are achieved?
• Are persons who are subject to AI use given notice?
• Should consent be given?
• Should persons be permitted to opt out of having AI used with respect to decisions being made?
• What data is being collected and used and what happens to that data?
• Is data used and stored sufficiently secured from wrongful access or exfiltration by cybercriminals?

As another example, in Washington, the House Financial Services Committee has been conducting hearings on AI and machine learning in the financial industry. The Committee is asking financial regulators — like the Office of the Comptroller of Currency — to ensure that use of AI by banks and lender does result in a rise in lender discrimination. In November 2021, the Committee sent a letter to financial regulators asking for investigations. Of notable concern were these items:

• Transparency — AI systems should not be unexplainable “black boxes”
• Explainability — what is the AI modeling? What are the data sets? What are the methodologies?
• Oversight — can regulators understand the AI systems enough to conduct proper oversight?
• Enforceability — can regulators understand the AI system to properly enforce the laws?
• Consumer privacy — do the AI systems endanger consumer privacy?

All of these concerns raise another legal issue with AI use: holding persons and organizations legally liable for wrongdoing and injuries. These include legal doctrines associated with products liability, negligence law, malpractice, toxic torts and more. Will defendants avoid liability by claiming that the “AI did it?” Will judges and juries be able to understand how the events happened and how the results were achieved?

On a more mundane level, use of AI is creating some interesting legal questions for intellectual property law. For example, there is now a world-wide debate about whether an AI system can own a patent. See Guardian media report here.

Contact the Trademark Lawyers at Revision Legal

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AI and Intellectual Property: Copyright and Training Data

One of the most contested legal battlegrounds in artificial intelligence law concerns whether training AI models on copyrighted works constitutes copyright infringement. Multiple federal lawsuits are currently pending against AI developers including OpenAI, Stability AI, and others, arguing that using copyrighted text, images, and code to train large language models and image generators without authorization infringes the reproduction and derivative works rights of copyright holders under 17 U.S.C. § 106. The defendants argue that training constitutes fair use under 17 U.S.C. § 107. Courts are only beginning to resolve these questions, and the legal landscape will evolve significantly over the next several years.

Beyond training data, AI-generated outputs raise their own copyright questions. The Copyright Office has taken the position that works generated autonomously by AI — without meaningful human creative authorship in the selection and arrangement of the output — are not copyrightable. However, works where a human uses AI as a tool in the creative process, with meaningful human creative contribution to the final output, may be eligible for copyright protection in the human-authored elements. For businesses that rely on AI-generated content, understanding these distinctions is critical: content that is entirely AI-generated may not be protectable, exposing your business to competition from anyone who can recreate similar output.

AI in Employment: Anti-Discrimination Law

The use of AI and algorithmic decision-making in employment — in hiring, promotion, performance evaluation, and termination — is subject to federal anti-discrimination laws including Title VII of the Civil Rights Act of 1964, the Age Discrimination in Employment Act (ADEA), and the Americans with Disabilities Act (ADA). The EEOC has issued guidance making clear that employers are responsible for the discriminatory impact of AI tools used in employment decisions, even if those tools are purchased from third-party vendors. Under the ADA, an AI-based hiring tool that screens out qualified individuals with disabilities may violate the ADA’s requirement of reasonable accommodation in the application process. New York City’s Local Law 144, which took effect in 2023, requires employers using automated employment decision tools (AEDTs) to conduct annual bias audits and disclose their use to candidates.

AI and Data Privacy: CCPA, GDPR, and Emerging Regulations

AI systems consume vast amounts of personal data, creating significant obligations under existing privacy laws. In the United States, the California Privacy Rights Act (CPRA) gives California consumers rights to know what personal data is being used to make automated decisions about them, and in some cases the right to opt out of such decisions. The EU’s General Data Protection Regulation (GDPR) goes further, providing individuals with a right not to be subject to solely automated decisions that produce significant legal or similarly significant effects, absent explicit consent or legal necessity. Businesses that use AI to make or influence decisions about customers, employees, or other individuals must map their data flows carefully and ensure their AI use complies with all applicable privacy frameworks.

At the federal level, the FTC has signaled that deceptive or unfair AI practices — including use of AI in ways that create discriminatory outcomes, make false claims about AI capabilities, or collect personal data without proper disclosure — are within its enforcement mandate. Proactive legal counsel on AI governance is far less expensive than defending regulatory enforcement proceedings.

Revision Legal advises businesses on the full range of legal issues raised by AI adoption and AI product development. From IP clearance for training data to compliance with employment and privacy laws, contact us today to develop a legally sound AI strategy.