News media headlines are trumpeting that the Executive Order preempts state AI laws. This is not true. It directs this administration to try to strike down some state AI laws. It contemplates working with Congress to formulate and enact preemptive legislation. It is doubtful that a President could constitutionally preempt state laws by executive order.
On December 11, 2025, President Trump issued another Executive Order. This one is intended to promote “national dominance” in “a race with adversaries for supremacy.” To “win,” the Order says, AI companies should not be encumbered by state regulation. “The policy of the United States,” the Order says, is “to sustain and enhance the United States’ global AI dominance through a minimally burdensome national policy framework for AI.” It sets up an AI Litigation Task Force to challenge state AI laws that allegedly do not do that.
Excepted from the Order are state laws on child safety protections, data center infrastructure, and state government use of AI.
Which State AI Laws?
The Order speaks generally about “state AI laws,” but does not define the term. In fact, AI legal issues are wide-ranging. Here are some examples of state AI laws:
Stalking and Harassment
A North Dakota statute criminalizes using a robot to frighten or harass another person. It defines a robot to include a drone or other system that uses AI technology. (N.D. Cent. Code § 12.1-17-07.(1), (2)(f)). This appears to be a “state AI law.” North Dakota statutes also prohibit stalking accomplished by using either a robot or a non-AI form of technology. (N.D. Cent. Code § 12.1-17-07.1(1)(d)). Preempting this statute would produce an anomalous result. It would be a crime to stalk somebody unless you use an AI-powered device to do it.
Political Deepfakes
Several states have enacted laws prohibiting the distribution of political deepfakes to influence an election. Regulations range from a prohibition against the distribution of a deepfake to influence an election within a specified time period before the election to requiring disclosure that it is AI-generated. Minn. Stat. § 609.771 is an example of such a regulation. The need for this kind of statute was highlighted in 2024 when someone used AI to clone Joe Biden’s voice and generate an audio file that sounded like Mr. Biden himself was urging people not to vote for him.
Sexual Deepfakes
Both state and federal governments have enacted laws aimed at curbing the proliferation of “revenge porn.” The TAKE IT DOWN Act is an example. Minn. Stat. § 604.32 is another example (deepfakes depicting intimate body parts or sexual acts).
State and federal laws in this area cover much of the same ground. The principal difference is that the federal crime must involve interstate commerce; state crimes do not. The only practical effect of preemption of this kind of state AI law, therefore, would be to eliminate state prohibitions of wholly intrastate sexual deepfakes. If the Executive Order succeeds in its objectives, then state laws that prohibit the creation or distribution of sexual deepfakes wholly within the same state, as some do, would be preempted, with the result that making and distributing sexual deepfakes would be lawful so long as you only transmit it to other people in your state and not to someone in a different state.
Digital Replicas
Many states have enacted laws prohibiting or regulating the unauthorized creation and exploitation of digital replicas. The California Digital Replicas Act and Tennessee’s ELVIS Act are examples. AI is used in the creation of digital replicas. It is unclear whether these kinds of enactments are “state AI laws.” Arguably, a person could use technologies more primitive than generative-AI to create a digital image of a person. If these statutes are preempted only to the extent they apply to AI-generated digital replicas, then it would seem that unauthorized exploiters of other people’s faces and voices for commercial gain would be incentivized to use AI to engage in unauthorized commerceial exploitation of other people.
Child Pornography
Several states have either enacted laws or amended existing laws to bring AI-generated images of what look like real children within the prohibition against child pornography. See, e.g., N.D. Cent. Code § 12.1.-27.2—01. The Executive Order exempts “child safety protections,” but real children do not necessarily have to be used in AI-generated images. This kind of state statute arguably would not come within the meaning of a “child safety protection.”
Health Care Oversight
California’s Physicians Make Decisions Act requires a human person to oversee health care decisions about medical necessity. This is to ensure that medical care is not left entirely up to an AI bot. The law was enacted with the support of the California Medical Association to ensure that patients receive adequate health care. If the law is nullified, then it would seem that hospitals would be free to replace doctors with AI chatbots.
Chatbots
Some states prohibit the deceptive use of a chatbot, such as by falsely representing to people who interact with one that they are interacting with a real person. In addition, some states have enacted laws requiring disclosure to consumers when they are interacting with a non-human AI. See, e.g., the Colorado Artificial Intelligence Act.
Privacy
Some states have enacted either stand-alone laws or amended existing privacy laws to ensure they protect the privacy of personally identifiable information stored by AI systems. See, e.g., Utah Code 13-721-201, -203 (regulating the sharing of a person’s mental health information by a chatbot); and amendments to the California Consumer Privacy Act making it applicable to information stored in an AI system.
The Texas Responsible Artificial Intelligence Governance Act
Among other things, the Texas Responsible AI Governance Act prohibits the use of AI to restrict constitutional rights, to discriminate on the basis of race, or to encourage criminal activity. These seem like reasonable proscriptions.
Trump’s “AI czar,” venture capitalist David Sacks, has said the administration is not gong to “push back” on all state laws, only “the most onerous” ones. It is unclear which of these will be deemed “onerous.”
State AI Laws are Not Preempted
News media headlines are trumpeting that the Executive Order preempts state AI laws. This is not true. It directs this administration to try to strike down some state AI laws. It contemplates working with Congress to formulate and enact preemptive legislation. It is doubtful that a President could constitutionally preempt state laws by executive order.
Postscript
Striving for uniformity in the regulation of artificial intelligence is not a bad idea. There should be room, though, for both federal and state legislation. Rather than abolishing state laws, a uniform code or model act for states might be a better idea. Moreover, if we are going to start caring about an onerous complex of differing state laws, and feeling a need to establish a national framework, perhaps the President and Congress might wish to address the sprawling morass of privacy and data security regulations in the United States.
Congressional legislation to regulate artificial intelligence (“AI”) and AI companies is in the early formative stages. Just about the only thing that is certain at this point is that federal regulation in the United States is coming.
Congressional legislation to regulate artificial intelligence (“AI”) and AI companies is in the early formative stages. Just about the only thing that is certain at this point is that federal regulation in the United States is coming.
In August, 2023, Senators Richard Blumenthal (D-CT) and Josh Hawley (R-MO) introduced a Bipartisan Framework for U.S. AI Act. The Framework sets out five bullet points identifying Congressional legislative objectives:
Establish a federal regulatory regime implemented through licensing AI companies, to include requirements that AI companies provide information about their AI models and maintain “risk management, pre-deployment testing, data governance, and adverse incident reporting programs.”
Ensure accountability for harms through both administrative enforcement and private rights of action, where “harms” include private or civil right violations. The Framework proposes making Section 230 of the Communications Decency Act inapplicable to these kinds of actions. (Second 230 is the provision that generally grants immunity to Facebook, Google and other online service providers for user-provided content.) The Framework identifies the harms about which it is most concerned as “explicit deepfake imagery of real people, production of child sexual abuse material from generative A.I. and election interference.” These are not, by any means, the only AI legal issues there are. Noticeably absent, for example, is any mention of harms caused by copyright infringement.
Restrict the sharing of AI technology with Russia, China or other “adversary nations.”
Promote transparency: The Framework would require AI companies to disclose information about the limitations, accuracy and safety of their AI models to users; would give consumers a right to notice when they are interacting with an AI system; would require providers to watermark or otherwise disclose AI-generated deepfakes; and would establish a public database of AI-related “adverse incidents” and harm-causing failures.
Protect consumers and kids. “Consumer should have control over how their personal data is used in A.I. systems and strict limits should be imposed on generative A.I. involving kids.”
The Framework does not address copyright infringement, whether of the input or the output variety.
The Senate Judiciary Committee Subcommittee on Privacy, Technology, and the Law held a hearing on September 12, 2023. Witnesses called to testify generally approved of the Framework as a starting point.
The Senate Commerce, Science, and Transportation Subcommittee on Consumer Protection, Product Safety and Data Security also held a hearing on September 12, called The Need for Transparency in Artificial Intelligence. One of the witnesses, Dr. Ramayya Krishnan, Carnegie Mellon University, did raise a concern about the use of copyrighted material by AI systems and the economic harm it causes for creators.
On September 13, 2023, Sen. Chuck Schumer (D-NY) held an “AI Roundtable.” Invited attendees present at the closed-door session included Bill Gates (Microsoft), Elon Musk (xAI, Neuralink, etc.) Sundar Pichai (Google), Charlie Rivkin (MPA), and Mark Zuckerberg (Meta). Gates, whose Microsoft company, like those headed by some of the other invitees, has been investing heavily in generative-AI development, touted the claim that AI could target world hunger.
Meanwhile, Dana Rao, Adobe’s Chief Trust Officer, penned a proposal that Congress establish a federal anti-impersonation right to address the economic harms generative-AI causes when it impersonates the style or likeness of an author or artist. The proposed law would be called the Federal Anti-Impersonation Right Act, or “FAIR Act,” for short. The proposal would provide for the recovery of statutory damages by artists who are unable to prove actual economic damages.
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.
Artificial intelligence (“AI”) is generating more than content; it is generating lawsuits. Here is a brief chronology of what I believe are the most significant lawsuits that have been filed so far.
Artificial intelligence (“AI”) is generating more than content; it is generating lawsuits. Here is a brief chronology of what I believe are the most significant lawsuits that have been filed so far.
Most of these allege copyright infringement, but some make additional or other kinds of claims, such as trademark, privacy or publicity right violations, defamation, unfair competition, and breach of contract, among others. So far, the suits primarily target the developers and purveyors of generative AI chatbots and similar technology. They focus more on what I call “input” than on “output” copyright infringement. That is to say, they allege that copyright infringement is involved in the way particular AI tools are trained.
Thomson Reuters Enterprise Centre GmbH et al. v. ROSS Intelligence (May, 2020)
Thomson Reuters alleges that ROSS Intelligence copied its Westlaw database without permission and used it to train a competing AI-driven legal research platform. In defense, ROSS has asserted that it only copied ideas and facts from the Westlaw database of legal research materials. (Facts and ideas are not protected by copyright.) ROSS also argues that its use of content in the Westlaw database is fair use.
One difference between this case and subsequent generative-AI copyright infringement cases is that the defendant in this case is alleged to have induced a third party with a Westlaw license to obtain allegedly proprietary content for the defendant after the defendant had been denied a license of its own. Other cases involve generative AI technologies that operate by scraping publicly available content.
The parties filed cross-motions for summary judgment. While those motions were pending, the U.S. Supreme Court issued its decision in Andy Warhol Found. for the Visual Arts, Inc. v. Goldsmith, 598 U.S. ___, 143 S. Ct. 1258 (2023). The parties have now filed supplemental briefs asserting competing arguments about whether and how the Court’s treatment of transformative use in that case should be interpreted and applied in this case. A decision on the motions is expected soon.
The court has now issued a fair use decision in Thomson Reuters v. ROSS Intelligence.
This is a class action lawsuit against GitHub, Microsoft, and OpenAI that was filed in November, 2022. It involves GitHub’s CoPilot, an AI-powered tool that suggests lines of programming code based on what a programmer has written. The complaint alleges that Copilot copies code from publicly available software repositories without complying with the terms of applicable open-source licenses. The complaint also alleges removal of copyright management information in violation of 17 U.S.C. § 1202, unfair competition, and other tort claims.
Andersen et al. v. Stability AI et al. (January 13, 2023)
Artists Sarah Andersen, Kelly McKernan, and Karla Ortiz filed this class action lawsuit against generative-AI companies Stability AI, Midjourney, and DeviantArt on January 13, 2023. The lawsuit alleges that the defendants infringed their copyrights by using their artwork without permission to train AI-powered image generators to create allegedly infringing derivative works. The lawsuit also alleges violations of 17 U.S.C. § 1202 and publicity rights, breach of contract, and unfair competition.
Getty Images has filed two lawsuits against Stability AI, one in the United Kingdom and one in the United States, each alleging both input and output copyright infringement. Getty Images owns the rights to millions of images. It is in the business of licensing rights to use copies of the images to others. The lawsuit also accuses Stability AI of falsifying, removing or altering copyright management information, trademark infringement, trademark dilution, unfair competition, and deceptive trade practices.
Stability AI has moved to dismiss the complaint filed in the U.S. for lack of jurisdiction.
Jack Flora and others filed a class action lawsuit against Prisma Labs for invasion of privacy. The complaint alleges, among other things, that the defendant’s 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, in violation of Illinois’s data privacy laws.
This is a publicity rights case. NeoCortext’s Reface app allows users to paste images of their own faces over those of celebrities in photographs and videos. Kyland Young, a former cast member of the Big Brother reality television show, has sued NeoCortext for allegedly violating his publicity rights. The complaint alleges that NeoCortext has “commercially exploit[ed] his and thousands of other actors, musicians, athletes, celebrities, and other well-known individuals’ names, voices, photographs, or likenesses to sell paid subscriptions to its smartphone application, Reface, without their permission.”
NeoCortext has asserted a First Amendment defense, among others.
Walters v. Open AI (June 5, 2023)
Walters v. OpenAI, LLC, No. 2023-cv-03122 (N.D. Ga. July 14, 2023) (Complaint originally filed in Gwinnett County, Georgia Superior Court on June 5, 2023; subsequently removed to federal court)
This is a defamation action against OpenAI, the company responsible for ChatGPT. The lawsuit was brought by Mark Walters. He alleges that ChatGPT provided false and defamatory misinformation about him to journalist Fred Riehl in connection with a federal civil rights lawsuit against Washington Attorney General Bob Ferguson and members of his staff. ChatGPT allegedly stated that the lawsuit was one for fraud and embezzlement on the part of Mr. Walters. The complaint alleges that Mr. Walters was “neither a plaintiff nor a defendant in the lawsuit,” and “every statement of fact” pertaining to him in the summary of the federal lawsuit that ChatGPT prepared is false. A New York court recently addressed the questions of sanctions for attorneys who submit briefs containing citations to non-existent “precedents” that were entirely made up by ChatGPT. This is the first case to address tort liability for ChatGPT’s notorious creation of “hallucinatory facts.”
In July, 2023, Jeffery Battle filed a complaint against Microsoft in Maryland alleging that he, too, has been defamed as a result of AI-generated “hallucinatory facts.”
This lawsuit has been brought by underage individuals against OpenAI and Microsoft. The complaint alleges the defendants’ generative-AI products ChatGPT, Dall-E and Vall-E collect private and personally identifiable information from children without their knowledge or informed consent. The complaint sets out claims for alleged violations of the Electronic Communications Privacy Act; the Computer Fraud and Abuse Act; California’s Invasion of Privacy Act and unfair competition law; Illinois’s Biometric Information Privacy Act, Consumer Fraud and Deceptive Business Practices Act, and Consumer Fraud and Deceptive Business Practices Act; New York General Business Law § 349 (deceptive trade practices); and negligence, invasion of privacy, conversion, unjust enrichment, and breach of duty to warn.
Another copyright infringement lawsuit against OpenAI relating to its ChatGPT tool. In this one, authors allege that ChatGPT is trained on the text of books they and other proposed class members authored, and facilitates output copyright infringement. The complaint sets forth claims of copyright infringement, DMCA violations, and unfair competition.
Sarah Silverman (comedian/actress/writer) and others allege that OpenAI, by using copyright-protected works without permission to train ChatGPT, committed direct and vicarious copyright infringement, violated section 17 U.S.C. 1202(b), and their rights under unfair competition, negligence, and unjust enrichment law.
This is a lawsuit against Google and its owner Alphabet, Inc. for allegedly scraping and harvesting private and personal user information, copyright-protected works, and emails, without notice or consent. The complaint alleges claims for invasion of privacy, unfair competition, negligence, copyright infringement, and other causes of action.
On the Regulatory Front
The U.S. Copyright Office is examining the problems associated with registering copyrights in works that rely, in whole or in part, on artificial intelligence. The U.S. Federal Trade Commission (FTC) has suggested that generative-AI implicates “competition concerns.”. Lawmakers in the United States and the European Union are considering legislation to regulate AI in various ways.
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.
