Trademark law protects brand identifiers like names, logos, words, slogans, and other things, ensuring consumers aren’t deceived about the source of a product or service. It also protects businesses from unfair competition. Core concepts include use in commerce, distinctiveness and the likelihood of confusion, which dictate whether a mark can be registered and enforced.
Whether you’re a startup founder, an artist, or just astudent of the law, understanding trademark law is essential. Here is a breakdown of the fundamentals, followed by some of the biggest trending issues in the trademark world today.
The Fundamentals of Trademark Law
A trademark is any word, name, drawing, graphic, or device used to identify the source of goods or services and distinguish them from others. The four essential requirements for a valid trademark are:
Distinctiveness
A trademark must operate not only to identify the source of a product or service but also to distinguish it from others.
It is evaluated along a spectrum:
Fanciful marks: These are completely made-up, invented words, graphics, etc. that have nothing whatsoever to do with the nature or quality of the products or services with which they are associated. These are inherently distinctive, meaning it is not necessary to prove that consumers have come to associate the mark with the source. XEROX and EXXON are examples.
Arbitrary marks: These are real words, images of real things, etc., but they bear no relationship to the product or service with which they are associated. APPLE computers is an example. These, too, are inherently distinctive.
Suggestive marks: Suggestive marks are marks that hint at the nature or a quality of the product or service, but do not directly describe it. They require some imaginative thought on the part of the consumer to “connect the dots.” JAGUAR for cars and COPPERTONE for suntan lotion are examples. A suggestive mark is inherently distinctive.
Descriptive marks. These describe a quality, ingredient, or characteristic of the product or service. Unlike suggestive marks, they don’t merely hint at it; they come right out and directly describe the product or service, or a characteristic or ingredient of it. HOLIDAY INN and INTERNATIONAL BUSINESS MACHINES are examples. Descriptive marks cannot be claimed as trademarks unless they have acquired “secondary meaning.” The burden of proof is on the claimant to show that consumers have come to identify the brand with the claimant’s product or service, and not with other sources of it.
Generic marks: These are names for a category of product or service. MILK, as a mark for milk would be an example. No trademark rights can be claimed in generic marks.
Likelihood of Confusion
The primary legal standard for both registering a mark and suing for infringement is “likelihood of confusion”. This means determining if an ordinary consumer would mistakenly believe that your product or service and someone else’s come from the same source, or are affiliated.
Courts apply a multi-factor test (primarily the DuPont factors) to assess likelihood of confusion. The most critical ones are:
Similarity of the marks: Do they look, sound, or convey a similar commercial impression?
Relatedness of the goods/services
Courts consider other factors, too.
Two marks may be confusingly similar even if they are not identical. The key is whether consumers would be likely to confuse the source of one with the source of the other.
Use in Commerce
A mark must be used in commerce as a source identifier. Otherwise, a trademark does not come into being. To register a trademark federally with the USPTO, the use must be in interstate or foreign commerce. Purely intrastate commerce will not suffice for federal registration.
Registration
In the United States, trademarks come into existence through use in commerce as a trademark. When all the elements of a valid trademark exist (distinctiveness, etc.) a “common law” trademark exists. The scope of protection a common law trademark affords, however, is limited to the geographic area of trade. To get nationwide protection and the right to use the coveted ® symbol, you must register your mark with the U.S. Patent and Trademark Office (USPTO).
My experience has been that the major stumbling blocks for people who apply to register their trademark with the USPTO are (1) lack of distinctiveness, usually due to selecting a descriptive mark without acquired meaning; (2) likelihood of confusion with another person’s or company’s trademark; and (3) improperly completing the application for registration.
Topical Issues in Trademark Law
Fraudulent filings
The USPTO has implemented rigorous enforcement frameworks to crack down on fraudulent filings. Historically, many trademark owners were in the habit of registering their marks in more than one category of goods or services, either to “keep options open” for possible company expansion into a new product line, or to prevent competitors from doing so. The USPTO is making more vigorous efforts to crack down on registrants who fraudulently claim use in connection with goods or services with which they are not actually using the mark.
Due to a massive influx of suspicious, fraudulent, or automated filing mills, the office has cracked down by requiring stricter identity verification and heavily scrutinizing specimens of use. If a brand is caught digitally altering logos or faking mock-ups of their goods in commerce, their registration is being swiftly canceled. Examiners are inspecting specimens of use more closely now, trying to ferret out digitally created mock-ups of trademarks being used in commerce. A false or fraudulent specimen of use is grounds for cancellation of registration.
The Trademark Modernization Act has given the USPTO new and enhanced powers to cancel unused and fraudulent registrations.
AI-Generated Counterfeits
Generative-AI is being used to create knock-offs of digital products. This is creating challenges for owners of trademarks in digital products and services.
Intermediary Platform Liability
Can an online marketplace platform or intermediary website or online service provider be held contributorily liable for facilitating or otherwise contributing to counterfeit and trademark-infringing goods being sold on their platforms?
Phrases Without Trademark Functionality
People are increasingly trying to claim trademark ownership over common words and phrases, such as, “Hello. How are you?” The USPTO and courts are rebuffing a lot of these efforts. It is still possible for a phrase to become a trademark, but proof of acquired secondary meaning as a source identifier is needed. Otherwise, an applicant is likely to experience a “failure to function as a trademark” denial.
Copyright cannot be claimed in a voice. Copyright law protects only expression, not a person’s corporeal attributes.
Painting of Nipper by Francis Barraud (1898-99); subsequently used as a trademark with “His Master’s Voice.”
Voice cloning is one of the generative-AI technologies that I have described as a perfect tool for the age of deception. Now the issues it raises are reaching the courts.
Lehrman v. Lovo, Inc.
On July 10, 2025, the federal district court for the Southern District of New York issued an Order granting in part and denying in part a motion to dismiss a putative class action lawsuit that Paul Lehrman and Linnea Sage commenced against Lovo, Inc. The lawsuit, Lehrman v. Lovo, Inc., alleges that Lovo used artificial intelligence to make and sell unauthorized “clones” of their voices.
Specifically, the complaint alleges that the plaintiffs are voice-over actors. For a fee, they read and record scripts for their clients. Lovo allegedly sells a text-to-speech subscription service that allows clients to generate voice-over narrations. The service is described as one that uses “AI-driven software known as ‘Generator’ or ‘Genny,'” which was “created using ‘1000s of voices.'” Genny allegedly creates voice clones, i.e., copies of real people’s voices. Lovo allegedly granted its customers “commercial rights for all content generated,” including “any monetized, business-related uses such as videos, audio books, advertising promotion, web page vlogging, or product integration.” (Lovo terms of service.) The complaint alleges that Lovo hired the plaintiffs to provide voice recordings for “research purposes only,” but that Lovo proceeded to exploit them commercially by licensing their use to Lovo subscribers.
This lawsuit ensued.
The complaint sets out claims for:
Copyright infringement
Trademark infringement
Breach of contract
Fraud
Conversion
Unjust enrichment
Unfair competition
New York civil rights laws
New York consumer protection laws.
The defendant moved to dismiss the complaint for failure to state a claim.
The copyright claims
Sage alleged that Lovo infringed the copyright in one of her voice recordings by reproducing it in presentations and YouTube videos. The court allowed this claim to proceed.
Plaintiffs also claimed that Lovo’s unauthorized use of their voice recordings in training its generative-AI product infringed their copyrights in the sound recordings. The court ruled that the complaint did not contain enough factual detail about how the training process infringed one of the exclusive rights of copyright ownership. Therefore, it dismissed this claim with leave to amend.
The court dismissed the plaintiffs’ claims of output infringement, i.e., claims that the “cloned” voices the AI tool generated infringed copyrights in the original sound recordings.
Copyright protection in a sound recording extends only to the actual recording itself. Fixation of sounds that imitate or simulate the ones captured in the original recording does not infringe the copyright in the sound recording.
This issue often comes up in connection with copyrights in music recordings. If Chuck Berry writes a song called “Johnny B. Goode” and records himself performing it, he will own two copyrights – one in the musical composition and one in the sound recording. If a second person then records himself performing the same song, and he doesn’t have a license (compulsory or otherwise) to do so, that person would be infringing the copyright in the music but not the copyright in the sound recording. This is true even if he is very good at imitating Berry’s voice and guitar work. For a claim of sound recording infringement to succeed, it must be shown that the actual recording itself was copied.
Plaintiffs did not allege that Lovo used Genny to output AI-generated reproductions of their original recordings. Rather, they alleged that Genny is able to create new recordings that mimic attributes of their voices.
The court added that the sound of a voice is not copyrightable expression, and even if it were, the plaintiffs had registered claims of copyright in their recordings, not in their voices.
The trademark claims
In addition to infringement, the Lanham Act creates two other potential bases of trademark liability: (1) false association; and (2) false advertising. 15 U.S.C. sec. 1125(a)(1)(A) and (B). Plaintiffs asserted both kinds of claims. The judge dismissed these claims.
False association
The Second Circuit court of appeals recently held, in Electra v. 59 Murray Enter., Inc. and Souza v. Exotic Island Enters., Inc., that using a person’s likeness to create an endorsement without the person’s permission can constitute a “false association” violation. In other words, a federally-protected, trademark-like interest in one’s image, likeness, personality and identity exists. (See, e.g., Jackson v. Odenat.)
Although acknowledging that this right extends to one’s voice, the judge ruled that the voices in this case did not function as trademarks. They did not identify the source of a product or service. Rather, they were themselves the product or service. For this reason, the judge ruled that the plaintiffs had failed to show that their voices, as such, are protectable trademarks under Section 43(a)(1)(A) of the Lanham Act.
False Advertising
Section 43(a)(1)(B) of the Lanham Act (codified at 15 U.S.C. sec. 1125(a)(1)(B)) prohibits misrepresentations about “the nature, characteristics, qualities, or geographic origin of . . . goods, services, or commercial activities.” The plaintiffs claimed that Lovo marketed their voices under different names (“Kyle Snow” and “Sally Coleman.”) The court determined that this was not fraudulent, however, because Lovo marketed them as what they were, namely, synthetic clones of the actors’ voices, not as their actual voices.
Plaintiffs also claimed that Lovo’s marketing materials falsely stated that the cloned voices “came with all commercial rights.” They asserted that they had not granted those rights to Lovo. The court ruled, however, that even if Lovo was guilty of misrepresentation, it was not the kind of misrepresentation that comes within Section 43(a)(1)(B), as it did not concern the nature, characteristics, qualities, or geographic origin of the voices.
State law claims
Although the court dismissed the copyright and trademark claims, it allowed some state law claims to proceed. Specifically, the court denied the motion to dismiss claims for breach of contract, violations of sections 50 and 51 of the New York Civil Rights Law, and violations of New York consumer protection law.
Both the common law and the New York Civil Rights Law prohibit the commercial use of a living person’s name, likeness or voice without consent. Known as “misappropriation of personality” or violation of publicity or privacy rights, this is emerging as one of the leading issues in AI law.
The court also allowed state law claims of false advertising and deceptive trade practices to proceed. The New York laws are not subject to the “nature, characteristics, qualities, or geographic origin” limitation set out in Section 43(a) of the Lanham Act.
Conclusion
I expect this case will come to be cited for the rule that copyright cannot be claimed in a voice. Copyright law protects only expression, not a person’s corporeal attributes. The lack of copyright protection for a person’s voice, however, does not mean that voice cloning is “legal.” Depending on the particular facts and circumstances, it may violate one or more other laws.
It also should be noted that after the Joe Biden voice-cloning incident of 2024, states have been enacting statutes regulating the creation and distribution of voice clones. Even where a specific statute is not applicable, though, a broader statute (such as the FTC Act or a similar state law) might cover the situation.
Images and references in this blog post are for illustrative purposes only. No endorsement, sponsorship or affiliation with any person, organization, company, brand, product or service is intended, implied, or exists.
Official portrait of Vice President Joe Biden in his West Wing Office at the White House, Jan. 10, 2013. (Official White House Photo by David Lienemann)
While Congress and the courts grapple with generative-AI copyright issues, the FTC weighs in on the risks of unfair competition, monopolization, and consumer deception.
FTC Press Release exceprt
While Congress and the courts are grappling with the copyright issues that AI has generated, the federal government’s primary consumer watchdog has made a rare entry into the the realm of copyright law. The Federal Trade Commission (FTC) has filed a Comment with the U.S. Copyright Office suggesting that generative-AI could be (or be used as) an unfair or deceptive trade practice. The Comment was filed in response to the Copyright Office’s request for comments as it prepares to begin rule-making on the subject of artificial intelligence (AI), particularly, generative-AI.
Monopolization
The FTC is responsible for enforcing the FTC Act, which broadly prohibits “unfair or deceptive” practices. The Act protects consumers from deceptive and unscrupulous business practices. It is also intended to promote fair and healthy competition in U.S. markets. The Supreme Court has held that all violations of the Sherman Act also violate the FTC Act.
So how does generative-AI raise monopolization concerns? The Comment suggests that incumbents in the generative-AI industry could engage in anti-competitive behavior to ensure continuing and exclusive control over the use of the technology. (More on that here.)
The agency cited the usual suspects: bundling, tying, exclusive or discriminatory dealing, mergers, acquisitions. Those kinds of concerns, of course, are common in any business sector. They are not unique to generative-AI. The FTC also described some things that are matters of special concern in the AI space, though.
Network effects
Because positive feedback loops improve the performance of generative-AI, it gets better as more people use it. This results in concentrated market power in incumbent generative-AI companies with diminishing possibilities for new entrants to the market. According to the FTC, “network effects can supercharge a company’s ability and incentive to engage in unfair methods of competition.”
Platform effects
As AI users come to be dependent on a particular incumbent generative-AI platform, the company that owns the platform could take steps to lock their customers into using their platform exclusively.
Copyrights and AI competition
The FTC Comment indicates that the agency is not only weighing the possibility that AI unfairly harms creators’ ability to compete. (The use of pirated or the misuse of copyrighted materials can be an unfair method of competition under Section 5 of the FTC Act.) It is also considering that generative-AI may deceive, or be used to deceive, consumers. Specifically, the FTC expressed a concern that “consumers may be deceived when authorship does not align with consumer expectations, such as when a consumer thinks a work has been created by a particular musician or other artist, but it has been generated by someone else using an AI tool.” (Comment, page 5.) Once again, generative-AI is a tool that is a perfect fit for the age of deception.
In one of my favorite passages in the Comment, the FTC suggests that training AI on protected expression without consent, or selling output generated “in the style of” a particular writer or artist, may be an unfair method of competition, “especially when the copyright violation deceives consumers, exploits a creator’s reputation or diminishes the value of her existing or future works….” (Comment, pages 5 – 6).
Fair Use
The significance of the FTC’s injection of itself into the generative-AI copyright fray cannot be overstated. It is extremely likely that during their legislative and rule-making deliberations, both Congress and the Copyright Office are going to be focusing the lion’s share of their attention on the fair use doctrine. They are most likely going to try to allow generative-AI outfits to continue to infringe copyrights (It is already a multi-billion-dollar industry, after all, and with obvious potential political value), while at the same time imposing at least some kinds of limitations to preserve a few shards of the copyright system. Maybe they will devise a system of statutory licensing like they did when online streaming — and the widespread copyright infringement it facilitated– became a thing.
Whatever happens, the overarching question for Congress is going to be, “What kinds of copyright infringement should be considered “fair” use.
Copyright fair use normally is assessed using a four-prong test set out in the Copyright Act. Considerations about unfair competition arguably are subsumed within the fourth factor in that analysis – the effect the infringing use has on the market for the original work.
The other objective of the FTC Act – protecting consumers from deception — does not neatly fit into one of the four statutory factors for copyright fair use. I believe a good argument can be made that it should come within the coverage of the first prong of the four-factor test: the purpose and character of the use. The task for Congress and the Copyright Office, then, should be to determine which particular purposes and kinds of uses of generative-AI should be thought of as fair. There is no reason the Copyright Office should avoid considering Congress’s objectives, expressed in the FTC Act and other laws, when making that determination.
For many reasons, the new millennium might well be described as the Age of Deception. Cokato Copyright Attorney Tom James explains why generative-AI is a perfect fit for it.
Image by Gerd Altmann on Pixabay.
What is generative AI?
“AI,” of course, stands for artificial intelligence. Generative AI is a variety of it that can produce content such as text and images, seemingly of its own creation. I say “seemingly” because in reality these kinds of AI tools are not really independently creating these images and lines of text. Rather, they are “trained” to emulate existing works created by humans. Essentially, they are derivative work generation machines that enable the creation of derivative works based on potentially millions of human-created works.
AI has been around for decades. It wasn’t until 2014, however, that the technology began to be refined to the point that it could generate text, images, video and audio so similar to real people and their creations that it is difficult, if not impossible, for the average person to tell the difference.
Rapid advances in the technology in the past few years have yielded generative-AI tools that can write entire stories and articles, seemingly paint artistic images, and even generate what appear to be photographic images of people. As I explained in AI Legal Issues, AI holds great potential as a facilitator of deception. Deception is so ubiquitous now, in fact, that AI tools themselves are joining in.
AI “hallucinations” (aka lies)
In the AI field, a “hallucination” occurs when an AI tool (such as ChatGPT) generates a confident response that is not justified by the data on which it has been trained.
For example, I queried ChatGPT about whether a company owned equally by a husband and wife could qualify for the preferences the federal government sets aside for women-owned businesses. The chatbot responded with something along the lines of “Certainly” or “Absolutely,” explaining that the U.S. government is required to provide equal opportunities to all people without discriminating on the basis of sex, or something along those lines. When I cited the provision of federal law that contradicts what the chatbot had just asserted, it replied with an apology and something to the effect of “My bad.”
I also asked ChatGPT if any U.S. law imposes unequal obligations on male citizens. The chatbot cheerily reported back to me that no, no such laws exist. I then cited the provision of the United States Code that imposes an obligation to register for Selective Service only upon male citizens. The bot responded that while that is true, it is unimportant and irrelevant because there has not been a draft in a long time and there is not likely to be one anytime soon. I explained to the bot that this response was irrelevant. Young men can be, and are, denied the right to government employment and other civic rights and benefits if they fail to register, regardless of whether a draft is in place or not, and regardless of whether they are prosecuted criminally or not. At this point, ChatGPT announced that it would not be able to continue this conversation with me. In addition, it made up some excuse. I don’t remember what it was, but it was something like too many users were currently logged on.
These are all examples of AI hallucinations. If a human being were to say them, we would call them “lies.”
Generating lie after lie
AI tools regularly concoct lies. For example, when asked to generate a financial statement for a company, a popular AI tool falsely stated that the company’s revenue was some number it apparently had simply made up. According to Slate, in their article, “The Alarming Deceptions at the Heart of an Astounding New Chatbot,” users of large language models like ChatGPT have been complaining that these tools randomly insert falsehoods into the text they generate. Experts now consider frequent “hallucination” (aka lying) to be a major problem in chatbots.
ChatGPT has also generated fake case precedents, replete with plausible-sounding citations. This phenomenon made the news when Stephen Schwartz submitted six fake ChatGPT-generated case precedents in his brief to the federal district court for the Southern District of New York in Mata v. Avianca. Schwartz reported that ChatGPT continued to insist the fake cases were authentic even after their nonexistence was discovered. The judge proceeded to ban the submission of AI-generated filings that have not been reviewed by a human, saying that generative-AI tools
are prone to hallucinations and bias…. [T]hey make stuff up – even quotes and citations. Another issue is reliability or bias. While attorneys swear an oath to set aside their personal prejudices,… generative artificial intelligence is the product of programming devised by humans who did not have to swear such an oath. As such, these systems hold no allegiance to…the truth.
Section 230 of the Communications Decency Act generally shields Facebook, Google and other online services from liability for providing a platform for users to publish false and defamatory information about other people. That has been a real boon for people who like to destroy other people’s reputations by means of spreading lies and misinformation about them online. It can be difficult and expensive to sue an individual for defamation, particularly when the individual has taken steps to conceal and/or lie about his or her identity. Generative AI tools make the job of defaming people even simpler and easier.
More concerning than the malicious defamatory liars, however, are the many people who earnestly rely on AI as a research tool. In July, 2023, Mark Walters filed a lawsuit against OpenAI, claiming its ChatGPT tool provided false and defamatory misinformation about him to journalist Fred Riehl. I wrote about this lawsuit in a previous blog post. Shortly after this lawsuit was filed, a defamation lawsuit was filed against Microsoft, alleging that its AI tool, too, had generated defamatory lies about an individual. Generative-AI tools can generate false and defamation statements about individuals even if no one has any intention of defaming anyone or ruining another person’s reputation.
Facilitating false light invasion of privacy
Generative AI is also highly effective in portraying people in a false light. In one recently filed lawsuit, Jack Flora and others allege, among other things, that Prisma Labs’ Lensa app generates sexualized images from images of fully-clothed people, and that the company failed to notify users about the biometric data it collects and how it will be stored and/or destroyed.Flora et al. v. Prisma Labs, Inc., No. 23-cv-00680 (N.D. Calif. February 15, 2023).
Voice cloning has also become a problem. Scammers are using recordings of people’s voices to create what sound like messages coming from the person in the recording. Using voice cloning in combination with generative-AI technology, it is possible to create what sounds like a politician urging voters not to vote for him, or a teenage child requesting money to help him out of a jam. The FTC has noted the possibility of using AI to generate false endorsements, and other ways of using generative-AI as an unfair trade practice. The possibilities are endless.
Pot, meet kettle; kettle, pot
“False news is harmful to our community, it makes the world less informed, and it erodes trust. . . . At Meta, we’re working to fight the spread of false news.” Meta (nee Facebook) published that statement back in 2017. Since then, it has engaged in what is arguably the most ambitious campaign in history to monitor and regulate the content of conversations among humans. Yet, it has also joined other mega-organizations Google and Microsoft in investing billions of dollars in what is the greatest boon to fake news in recorded history: generative-AI.
Toward a braver new world
It would be difficult to imagine a more efficient method of facilitating widespread lying and deception (not to mention false and hateful rhetoric) – and therefore propaganda – than generative-AI. Yet, these mega-organizations continue to sink more and more money into further development and deployment of these lie-generators.
I dread what the future holds in store for our children and theirs.
AI has been trained not just to perform customer service tasks, but also to perform analytics and diagnostic tests; to repair products; to update software; to drive cars; and even to write articles and create images and videos. These developments may be helping to streamline tasks and improve productivity, but they have also generated a range of new legal issues.
AI is not new. Its implementation also is not new. In fact, consumers regularly interact with AI-powered systems every day. Online help systems often use AI to provide quick answers to questions that customers routinely ask. Sometimes these are designed to give a user the impression that s/he is communicating with a person.
AI systems also perform discrete functions such as analyzing a credit report and rendering a decision on a loan or credit card application, or screening employment applications.
Many other uses have been found for AI and new ones are being developed all the time. AI has been trained not just to perform customer service tasks, but also to perform analytics and diagnostic tests; to repair products; to update software; to drive cars; and even to write articles and create images and videos. These developments may be helping to streamline tasks and improve productivity, but they have also generated a range of new legal issues.
Tort liability
While there are many different kinds of tort claims, the elements of tort claims are basically the same: (1) The person sought to be held liable for damages or ordered to comply with a court order must have owed a duty to the person who is seeking the legal remedy; (2) the person breached that duty; (3) the person seeking the legal remedy experienced harm, i.e., real or threatened injury; and (4) the breach was the actual and proximate cause of the harm.
The kind of harm that must be demonstrated varies depending on the kind of tort claim. For example, a claim of negligent driving might involve bodily injury, while a claim of defamation might involve injury to reputation. For some kinds of tort claims, the harm might involve financial or economic injury.
The duty may be specified in a statute or contract, or it might be judge-made (“common law.”) It may take the form of an affirmative obligation (such as a doctor’s obligation to provide a requisite level of care to a patient), or it may take a negative form, such as the common law duty to refrain from assaulting another person.
The advent of AI does not really require any change in these basic principles, but they can be more difficult to apply to scenarios that involve the use of an AI system.
Example. Acme Co. manufactures and markets Auto-Doc, a machine that diagnoses and repairs car problems. Mike’s Repair Shop lays off its automotive technician employees and replaces them with one of these machines. Suzie Consumer brings her VW Jetta to Mikes Repair Shop for service because she has been hearing a sound that she describes as being a grinding noise that she thinks is coming from either the engine or the glove compartment. The Auto-Doc machine adds engine oil, replaces belts, and removes the contents of the glove compartment. Later that day, Suzie’s brakes fail and her vehicle hits and kills a pedestrian in a crosswalk. A forensic investigation reveals that her brakes failed because they were badly worn. Who should be held liable for the pedestrian’s death – Suzie, Mike’s, Acme Co., some combination of two of them, all of them, or none of them?
The allocation of responsibility will depend, in part, on the degree of autonomy the AI machine possesses. Of course, if it can be shown that Suzie knew or should have known that her brakes were bad, then she most likely could be held responsible for causing the pedestrian’s death. But what about the others? Their liability, or share of liability, is affected by the degree of autonomy the AI machine possesses. If it is completely autonomous, then Acme might be held responsible for failing to program the machine in such a way that it would test for and detect worn brake pads even if a customer expresses an erroneous belief that the sound is coming from the engine or the glove compartment. On the other hand, if the machine is designed only to offer suggestions of possible problems and solutions, leaving it up to a mechanic to accept or reject them, then Mike’s might be held responsible for negligently accepting the machine’s recommendations.
Assuming the Auto-Doc machine is fully autonomous, should Mike’s be faulted for relying on it to correctly diagnose car problems? Is Mike’s entitled to rely on Acme’s representations about Auto-Doc’s capabilities, or would the repair shop have a duty to inquire about and/or investigate Auto-Doc’s limitations? Assuming Suzie did not know, and had no reason to suspect, her brakes were worn out, should she be faulted for relying on a fully autonomous machine instead of taking the car to a trained human mechanic? Why or why not?
Deception
AI tools are notorious for making things up. Many attorneys have gotten into trouble for filing briefs with citations to non-existent cases in them. Known as AI hallucinations, they can be comical at times.
The people in this AI-generated image appear to be such hot beverage aficionados that they keep one of their many cups of the stuff suspended in mid-air in front of them. And of course, the man has six digits on his right hand – five fingers and a thumb – a standard in the world of AI hallucinations now.
(This is an AI hallucination.)
Unfortunately, AI can also hallucinate false information about people. It can also be prompted to create false and defamatory statements, false product or political candidate endorsements, books and other creative works “in the style of” a well-known author or artist that are then falsely advertised as originals, digital replicas, voice clones, and sexual deepfakes. Comical hallucinations notwithstanding, generative-AI tools are capable of great deception and therefore great harm.
It is conceivable that an AI system might engage in activity that is prohibited by an applicable jurisdiction’s criminal laws. E-mail address harvesting is an example. In the United States, for example, the CAN-SPAM Act makes it a crime to send a commercial email message to an email address that was obtained by automated scraping of Internet websites for email addresses. Of course, if a person intentionally uses an AI system for scraping, then liability should be clear. But what if an AI system “learns” to engage in scraping?
AI-generated criminal output may also be a problem. Some countries have made it a crime to display a Nazi symbol, such as a swastika, on a website. Will criminal liability attach if a website or blog owner uses AI to generate illustrated articles about World War II and the system generates and displays articles that are illustrated with World War II era German flags and military uniforms? In the United States, creating or possessing child pornography is illegal. Will criminal liability attach if an AI system generates it?
Some of these kinds of issues can be resolved through traditional legal analysis of the intent and scienter elements of the definitions of crimes. A jurisdiction might wish to consider, however, whether AI systems should be regulated to require system creators to implement measures that would prevent illegal uses of the technology. This raises policy and feasibility questions, such as whether and what kinds of restraints on machine learning should be required, and how to enforce them. Further, would prior restraints on the design and/or use of AI-powered expressive-content-generating systems infringe on First Amendment rights?
Product liability
Related to the problem of allocating responsibility for harm caused by the use of an AI mechanism is the question whether anyone should be held liable for harm caused when the mechanism is not defective, that is to say, when it is operating as it should.
Example. Acme Co. manufactures and sells Auto-Article, a software program that is designed to create content of a type and kind the user specifies. The purpose of the product is to enable a website owner to generate and publish a large volume of content frequently, thereby improving the website’s search engine ranking. It operates by scouring the Internet and analyzing instances of the content the user specifies to produce new content that “looks like” them. XYZ Co. uses the software to generate articles on medical topics. One of these articles explains that chest pain can be caused by esophageal spasms but that these typically do not require treatment unless they occur frequently enough to interfere with a person’s ability to eat or drink. Joe is experiencing chest pain. He does not seek medical help, however, because he read the article and therefore believes he is experiencing esophageal spasms. He later collapses and dies from a heart attack. A medical doctor is prepared to testify that his death could have been prevented if he had sought medical attention when he began experiencing the pain.
Should either Acme or XYZ Co. be held liable for Joe’s death? Acme could argue that its product was not defective. It was fit for its intended purposes, namely, a machine learning system that generates articles that look like articles of the kind a user specifies. What about XYZ Co.? Would the answer be different if XYZ had published a notice on its site that the information provided in its articles is not necessarily complete and that the articles are not a substitute for advice from a qualified medical professional? If XYZ incurs liability as a result of the publication, would it have a claim against Acme, such as for failure to warn it of the risks of using AI to generate articles on medical topics?
Consumer protection
AI system deployment raises significant health and safety concerns. There is the obvious example of an AI system making incorrect medical diagnoses or treatment recommendations. Autonomous (“self-driving”) motor vehicles are also examples. An extensive body of consumer protection regulations may be anticipated.
Forensic and evidentiary issues
In situations involving the use of semi-autonomous AI, allocating responsibility for harm resulting from the operation of the AI system may be difficult. The most basic question in this respect is whether an AI system was in use or not. For example, if a motor vehicle that can be operated in either manual or autonomous mode is involved in an accident, and fault or the extent of liability depends on that (See the discussion of tort liability, above), then a way of determining the mode in which the car was being driven at the time will be needed.
If, in the case of a semi-autonomous AI system, tort liability must be allocated between the creator of the system and a user of it, the question of fault may depend on who actually caused a particular tortious operation to be executed – the system creator or the user. In that event, some method of retracing the steps the AI system used may be essential. This may also be necessary in situations where some factor other than AI contributed, or might have contributed, to the injury. Regulation may be needed to ensure that the steps in an AI system’s operations are, in fact, capable of being ascertained.
Transparency problems also fall into this category. As explained in the Journal of Responsible Technology, people might be put on no-fly lists, denied jobs or benefits, or refused credit without knowing anything more than that the decision was made through some sort of automated process. Even if transparency is achieved and/or mandated, contestability will also be an issue.
Data Privacy
To the extent an AI system collects and stores personal or private information, there is a risk that someone may gain unauthorized access to it.. Depending on how the system is designed to function, there is also a risk that it might autonomously disclose legally protected personal or private information. Security breaches can cause catastrophic problems for data subjects.
Publicity rights
Many jurisdictions recognize a cause of action for violation of a person’s publicity rights (sometimes called “misappropriation of personality.”) In these jurisdictions, a person has an exclusive legal right to commercially exploit his or her own name, likeness or voice. To what extent, and under what circumstances, should liability attach if a commercialized AI system analyzes the name, likeness or voice of a person that it discovers on the Internet? Will the answer depend on how much information about a particular individual’s voice, name or likeness the system uses, on one hand, or how closely the generated output resembles that individual’s voice, name or likeness, on the other?
Contracts
The primary AI-related contract concern is about drafting agreements that adequately and effectively allocate liability for losses resulting from the use of AI technology. Insurance can be expected to play a larger role as the use of AI spreads into more areas.
Bias, Discrimination, Diversity & Inclusion
Some legislators have expressed concern that AI systems will reflect and perpetuate biases and perhaps discriminatory patterns of culture. To what extent should AI system developers be required to ensure that the data their systems use are collected from a diverse mixture of races, ethnicities, genders, gender identities, sexual orientations, abilities and disabilities, socioeconomic classes, and so on? Should developers be required to apply some sort of principle of “equity” with respect to these classifications, and if so, whose vision of equity should they be required to enforce? To what extent should government be involved in making these decisions for system developers and users?
Copyright
AI-generated works like articles, drawings, animations, music and so on, raise three kinds of copyright issues:
Input infringement issues, i.e., questions like whether AI systems that are designed to create new works based on existing copyright-protected works infringe the copyrights in those works. The highest-stake legal battleground today centers on this. I provide a layperson-friendly explanation of this issue and the initial lawsuits raising it in Does AI Infringe Copyright?
Output infringement issues, i.e., whether output generated by AI tools infringes copyrights in the works on which the AI was trained
Output ownership issues, namely, who, if anybody, owns the copyright in an AI-generated work (assuming it does not infringe anyone else’s copyright.) This issue really gets down to the core of what a copyright is and how (and by whom or by what) it is created. For a deeper dive into the theoretical and historical framework for non-human authorship, read my article, AI Can Create But Is It Art?
As debate around the interplay of artificial intelligence and intellectual property rights intensifies, legislators and regulators can be expected to attempt to establish formal frameworks, rules and guidelines. The United States Copyright Office has been among the first to enter the fray. It has issued a series of Guidances on AI legal issues. I wrote a blog post summarizing issues addressed in one of these Copyright Office reports in New AI Copyright Guidance.
Patents, Trademarks, and other IP
Computer programs can be patented. AI systems can be devised to write computer programs. Can an AI-generated computer program that meets the usual criteria for patentability (novelty, utility, etc.) be patented?
Is existing intellectual property law adequate to deal with AI-generated inventions and creative works? The World Intellectual Property Organization (WIPO) apparently does not think so. It is formulating recommendations for new regulations to deal with the intellectual property aspects of AI.
Trademark issues like infringement and dilution can come up in AI litigation, too, as one of the Getty Images lawsuits demonstrates.
AI Policy
As state and federal governments act to regulate in this area, expect to see a greater focus among policy-makers on public policy questions on fundamental issues like the desirability of uniform legislation, policies on governmental use of AI technology, federalism issues (state vs. federal control), as well as global AI regulation. President Trump’s Executive Order on AI is an example. Time permitting, I will try to provide updates on new AI-related laws as they are enacted, at least to the extent they touch on copyright questions.
Conclusion
AI systems raise a wide range of legal issues. The ones identified in this article are merely a sampling, not a complete listing of all possible issues. Not all of these legal issues have answers yet. It can be expected that more AI regulatory measures, in more jurisdictions around the globe, will be coming down the pike very soon.
Get updates on the courts: Follow my AI Lawsuits Roundup page for a look at current litigation against generative AI platforms.
Contact attorney Thomas James
Contact Minnesota attorney Thomas James for help with copyright and trademark registration and other copyright and trademark-related matters.
