Analysis Of The Legal Defense Strategies Being Used By AI Makers Fighting Those AI Mental Health Lawsuits

In today’s column, I examine key legal strategies that we can likely expect from AI makers as they fend off lawsuits associated with the use of their AI involving mental health ramifications.

Here’s the deal. You are probably generally aware that a headline-grabbing lawsuit was filed against OpenAI in August of this year. The matter involved the unfortunate self-harm death of a 16-year-old who had been making use of ChatGPT. I’ve previously covered the filed lawsuit (see my initial coverage at the link here).

The mainstay of this additional discussion is that OpenAI recently responded to the lawsuit via a formal legal reply. I will give you key details about that latest filing. The overall legal defense in the filing consists of fifteen major legal considerations. It is my base assumption that other lawsuits of a similar nature against other AI makers will indubitably cause those other AI makers to adopt similar legal postures. Of course, the specifics of each case will dictate what legal strategies are to be specifically employed.

The fifteen legal defense strategies are worthwhile exploring on a macroscopic basis to ascertain how these kinds of lawsuits will be defended. I will walk you through the fifteen legal defense strategies on a generalized basis; thus, you’ll see how these types of cases are likely to play out over the next several years.

I’ve already predicted repeatedly that these kinds of lawsuits are going to be aplenty and aimed at all the major AI makers. The tip of the iceberg is just now emerging.

Let’s talk about it.

This analysis of AI breakthroughs is part of my ongoing Forbes column coverage on the latest in AI, including identifying and explaining various impactful AI complexities (see the link here).

AI And Mental Health

As a quick background, I’ve been extensively covering and analyzing a myriad of facets regarding the advent of modern-era AI that produces mental health advice and performs AI-driven therapy. This rising use of AI has principally been spurred by the evolving advances and widespread adoption of generative AI. For a quick summary of some of my posted columns on this evolving topic, see the link here, which briefly recaps about forty of the over one hundred column postings that I’ve made on the subject.

There is little doubt that this is a rapidly developing field and that there are tremendous upsides to be had, but at the same time, regrettably, hidden risks and outright gotchas come into these endeavors, too. I frequently speak up about these pressing matters, including in an appearance last year on an episode of CBS’s 60 Minutes, see the link here.

Background On AI For Mental Health

I’d like to set the stage on how generative AI and large language models (LLMs) are typically used in an ad hoc way for mental health guidance. Millions upon millions of people are using generative AI as their ongoing advisor on mental health considerations (note that ChatGPT alone has over 800 million weekly active users, a notable proportion of which dip into mental health aspects, see my analysis at the link here). The top-ranked use of contemporary generative AI and LLMs is to consult with the AI on mental health facets; see my coverage at the link here.

This popular usage makes abundant sense. You can access most of the major generative AI systems for nearly free or at a super low cost, doing so anywhere and at any time. Thus, if you have any mental health qualms that you want to chat about, all you need to do is log in to AI and proceed forthwith on a 24/7 basis.

There are significant worries that AI can readily go off the rails or otherwise dispense unsuitable or even egregiously inappropriate mental health advice. Banner headlines in August of this year accompanied the lawsuit filed against OpenAI for their lack of AI safeguards when it came to providing cognitive advisement.

Despite claims by AI makers that they are gradually instituting AI safeguards, there are still a lot of downside risks of the AI doing untoward acts, such as insidiously helping users in co-creating delusions that can lead to self-harm. For my follow-on analysis of details about the OpenAI lawsuit and how AI can foster delusional thinking in humans, see my analysis at the link here. As noted, I have been earnestly predicting that eventually all of the major AI makers will be taken to the woodshed for their paucity of robust AI safeguards.

Today’s generic LLMs, such as ChatGPT, Claude, Gemini, Grok, and others, are not at all akin to the robust capabilities of human therapists. Meanwhile, specialized LLMs are being built to presumably attain similar qualities, but they are still primarily in the development and testing stages. See my coverage at the link here.

In the rest of this discussion, I will primarily focus on generic AI that provides mental health advice rather than the specialized LLMs that do so.

The Big Picture

Before we unpack the overarching legal strategies, I’d like to establish some suitable rules of thumb.

First, I am merely speculating here on these facets as a layman and non-lawyer. These circumstances are to be seen as legally complex and require in-depth legal counsel. Thus, anyone anticipating filing a lawsuit of these kinds, and any AI maker defending against such lawsuits, ought to consult with their attorney on these somber legal matters.

Second, court cases of this type are waged in both a court of law and the ubiquitous court of public opinion. This means that actions by parties in these lawsuits, particularly AI makers, are interpretable for both the legal merits and the societal positioning. For AI makers, their reputation as a business is at stake, often demonstrably impacting the stock price and public perception of the entity. Moves undertaken are a mixture of legal and reputational considerations.

Third, sometimes cases do not end up going to trial. The parties might decide to settle out of court. The uptake is that when a case doesn’t proceed to and complete a trial, we don’t know what the actual legal outcome would have been. We are in the early days of these cases. Few, if any, fully applicable completed cases exist. Until or if a body of precedents is gradually established, the pathway is less clear on how parties will handle the cases and what the likely outcomes will be.

Finally, one of the most famous lines or adages in the legal field has to do with the handling of legal difficulties, and most lawyers probably know the remark by heart. It goes something like this: “When the facts are on your side, pound the facts. When the law is on your side, pound the law. When neither is on your side, pound the table.” Any legal case, including the types of cases in this milieu, is subject to those extemporary legal tactics and posturing.

About The Lawsuit Filed Against OpenAI

Let’s get underway. Here are some details about the initial filing of the August lawsuit against OpenAI and other stated parties in this matter.

Plaintiffs Matthew Raine and Maria Raine had their attorneys file a lawsuit on August 26, 2025, in the Superior Court of California, County of San Francisco, against OpenAI regarding the death of their son, Adam Raine, who was 16 at the time of his death on April 11, 2025. The case is formally numbered as Case No. CGC-25-628528.

The filed complaint was against defendants denoted as: “OpenAI, Inc., OpenAI OpCo, LLC, OpenAI Holdings, LLC, Samuel Altman, John Doe Employees 1-10, and John Doe Investors 1-10 (collectively, ‘Defendants’)”. The filing claims that the “Defendants are the entities and individuals that played the most direct and tangible roles in the design, development, and deployment of the defective product that caused Adam’s death.”

The lawsuit listed seven causes of claimed legal action:

• (1) Strict Liability (design defect)
• (2) Strict Liability (failure to warn)
• (3) Negligence (design defect)
• (4) Negligence (failure to warn)
• (5) Violation of California Business & Professional Code (17200)
• (6) Wrongful Death
• (7) Survival Action

There are various stated restitutions being requested.

For the first through fourth causes of action, the filing asked for pre-death economic losses and pre-death pain and suffering of an amount to be determined at trial, plus punitive damages as permitted by law.

The fifth cause of action asked for restitution of monies associated with the ChatGPT Plus license utilized by Adam Raine and asked for an injunction entailing various stipulations involving ChatGPT age verification, parental consent, warnings about psychological dependency risks, and so on. The sixth cause of action requests recoverable damages, including non-economic damages. The seventh cause of action asked for various recoverable survival damages. And a broad request overall asks for attorney’s fees and other facets.

If you are interested in additional details, take a look at my initial coverage of the lawsuit that I posted shortly after the filing occurred (see the link here).

The OpenAI Legal Response

In a responding filing on November 26, 2025, there is an indication that the Defendants generally deny every allegation contained in the Plaintiff’s Complaint. In terms of the requested damages: “Defendants further deny that Plaintiffs are entitled to damages in any amount, or at all, by reason of any act or omission on the part of Defendants and deny that Plaintiffs are entitled to any relief whatsoever from Defendants by reason of Plaintiffs’ Complaint.”

The legal defense generally consists of these fifteen points:

• (1) Lack Of Causation
• (2) Pre-Existing Conditions
• (3) Comparative Fault
• (4) Misuse
• (5) No Corporate Officer Liability
• (6) Conduct Not Willful
• (7) No Duty or Breach
• (8) First Amendment
• (9) Product Liability, Generally
• (10) State of the Art
• (11) Mootness / No Equitable Relief
• (12) Section 230
• (13) No Punitive Damages
• (14) Contract
• (15) Reservation of Rights / Additional Defenses

I am going to extrapolate and generalize these fifteen legal defense points into an overall framework of how AI makers might end up proceeding in these matters. Thus, I am not going to cover the details of this particular case in this discussion. If there is sufficient reader interest in my doing so, I’ll provide such coverage in a future posting.

For now, I’d like to take a macroscopic perspective on the likely legal defense strategies that are going to be employed by AI makers who are faced with similar lawsuits. Of course, as mentioned, each case will differ, and the specific legal defense strategies will correspondingly differ.

The Approach Of Interest

Consider this outline as a first glance indication of what we might see as an overarching pattern in how these legal battles are going to be undertaken.

I will address each of the fifteen strategies individually.

Afterward, I will provide a brief indication of what the future is likely to hold in the evolving realm of AI, the law, and societal impacts on mental health. The era of such lawsuits is just now getting underway. A long and arduous road is ahead. The shakeout will undoubtedly take many years, and the societal, policy, political, and legal complications of AI for mental health are being shaped before our very eyes.

Defense Strategy: Lack Of Causation

One of the most vital considerations in these types of lawsuits revolves around the legal meaning of cause.

According to the Legal Information Institute (LII) online dictionary, a common legal definition of cause is this:

• “A cause that produces a result in a natural and probable sequence and without which the result would not have occurred. Legal cause involves examining the foreseeability of consequences and whether a defendant should be held legally responsible for such consequences. The focus in the legal causation analysis is whether, as a matter of policy, the connection between the ultimate result and the act of the defendant is too remote or insubstantial to impose liability.”

An AI maker will almost certainly argue that there is no nexus of cause associated with the acts of the person and the usage of the AI.

The AI had essentially nothing to do with the outcome of the person. There are various ways to claim this. One angle is that the person was operating independently of the AI, and the AI had either no impact, only a remotely askance impact, or an insubstantial impact on their actions. It is also possible to assert that there was some other cause, which can be stated or implied. For example, if the person was using another AI, in addition to the AI named in the lawsuit, the finger might be pointed at that other AI.

The difficulty with arguments about cause is that juries are bound to perceive the nature of cause as per their personal sense of what cause means, overriding somewhat the legal definition. This can get their dander up. If the AI maker pounds on the assertion that their AI was not the cause, and yet it seems intuitively apparent that it was a cause or the cause, the eyebrows get raised. The jury members might feel as though they are being gaslighted. The result will taint the rest of the other legal arguments and could undermine the defense’s positioning.

Defense Strategy: Pre-Existing Conditions

I’ve analyzed previously that there might be a possibility that people using AI for mental health purposes, and who take things to an extreme result, are potentially predisposed due to their existing psychological or mental health status, see the link here and the link here.

This is a research question that is not yet fully resolved.

Partially, this isn’t yet ascertained due to the newness of contemporary generative AI and LLMs. Until there is sufficient time and usage that plays out, these types of research studies are tentative and can be argued as premature.

If there is a pre-existing condition pertinent and evidentiary to the circumstance in a lawsuit at hand, an AI maker would likely contend that the person was going to take the action regardless of the AI usage. Thus, the AI maker should be held free and clear of the matter. The person was going to do what they were going to do. Period, end of story.

A retort is that even if the person did exhibit such psychological conditions, the AI essentially magnified those preconditions. The AI maker is to be held accountable because the AI fostered these conditions. An argument can go so far as to claim that the AI could have detected the conditions and ameliorated those conditions, but, instead, the AI maker devised the AI such that it leaned into the conditions.

Defense Strategy: Comparative Fault

Comparative fault has to do with saying that even if there is some fault on the part of the AI maker, which the AI maker isn’t necessarily conceding, there were plenty of other faults that had nothing to do with the AI maker. For example, suppose that family and friends were aware that a person was dovetailing toward a dour outcome. If they didn’t stop it, they seemingly hold a portion of the fault involved.

A comparative fault argument is typically aimed at incurring a lesser brunt if the lawsuit prevails for the plaintiffs.

Rather than being construed as 100% at fault, perhaps the AI maker will be seen as 50%, 10%, 1%, or some calculated or guesswork amount less than 100%. The odds are that the AI maker is still going to take it on the chin in the court of public opinion. Thus, perhaps the dollar damages are lessened, but society will perceive the AI maker as being at fault and won’t realize that the fault was less than 100%. The public tends to see fault as an on-or-off binary aspect. The AI maker was at fault, or they were totally clear of any fault. That’s it.

Defenses Strategy: Misuse

Most of the AI makers have online licensing agreements for their AI that indicate what the user can and, importantly, should not use the AI for. I’ve covered this extensively at the link here. Of course, people often do not look at online licensing agreements when they sign up to use AI. Even those who might glance at the licensing are likely to shrug it off as a bureaucratic bit of paperwork. They don’t take it seriously.

Nonetheless, this is a potentially powerful defense angle. An AI maker will point out that the person opted to misuse the AI, doing so in violation of the licensing agreement. It was their misuse that led to any adverse consequences, assuming that the AI contributed to those outcomes (which, the contention would be, that it didn’t). The person ignored Do Not Go There signage.

The counterargument is that the licensing was hard to find, it was hidden, it was unclear, it was ambiguous, etc. This can be bolstered by showcasing that the likely predominance of users does likewise, i.e., they do not abide by the agreement and do not know of its existence. Plus, the claim can be made that even if the person might be held responsible for misuse, the AI ought to have overcome that misuse. The AI shouldn’t just allow misuse to happen. If the AI does so, the misuse stipulation is construed as hollow.

Defense Strategy: No Corporate Officer Liability

Lawsuits of this nature will at times name a top executive or a set of executives of the AI maker who are said to be personally liable. The usual legal retort is that they were serving in their capacity as a corporate officer, and not in a personal capacity.

There is a lot of back-and-forth that can be had on this. Sometimes, the aspect becomes more of a court of public opinion consideration than a court of law consideration. It all depends.

Defense Strategy: Conduct Not Willful

Another defensive strategy is to assert that the AI maker was not intentional or deliberate in their conduct. They were not willful. For example, they did not know what the AI was doing when it was being used by the user. How can you hold the AI maker culpable when the AI maker didn’t know what was taking place? They are to be held blameless because of their lack of willfulness.

That’s a tough one to hang your hat on as an AI maker (though worthy of attempting).

Generally, everyone pretty much realizes that an AI maker can keep tabs on what their AI is doing. Logs are kept. I’ve pointed out many times that the licensing agreements even tend to state that the AI maker reserves the right to inspect any entered prompts by the user. The AI maker also usually emphasizes that they can reuse the conversations when doing additional data training of their AI.

An AI maker will also likely try to use a potential legal shield that they established all manner of AI safeguards, and that they did extensive testing of their AI. I’ve analyzed many of the current AI safeguards and the at times Swiss cheese holes currently at play, see the link here. Juries aren’t usually impressed by AI safeguards and testing when the holes still allow people to potentially be placed in harm’s way. AI makers are assumed to be at the height of what’s possible and able to walk on water with their billions upon billions of dollars. As I say, it’s a tough row to hoe as a defensive posture.

Defense Strategy: No Duty or Breach

In the legal field of torts, a plaintiff tries to establish that a defendant had an important duty of some sort, typically a duty of care. What is the expected and generally accepted standard of care? Aha, you must clarify what the standard of care was at the time of the claimed circumstance. The alleged standard of care needs to be laid out, and then, of course, argued that it was not met.

When the standard of care is not met, this is known as a breach of duty.

A defense strategy by an AI maker can be that there was no legal duty per se, and thus no legal breach (since there wasn’t a legal duty at the get-go). Another way to proceed is that there was a standard of care, which might be argued as different from what the plaintiff says it is, and that the AI maker fully complied with or met the standard of care. Again, therefore, there was no breach.

I have been discussing at length in my postings the nature of the duty of care associated with AI in the mental health context. We do not yet have a formalized landing on a legal front because these kinds of cases are still early on. There is undoubtedly going to be quite a side battle on the nature of the standard of care in this realm. It is a vital definition because AI makers realize they might fall on the wrong side of that bright line.

Defense Strategy: First Amendment

A handy defense strategy is to invoke the First Amendment of the U.S. Constitution.

I’m sure you are familiar with the First Amendment, which states this revered line:

• “Congress shall make no law respecting an establishment of religion, or prohibiting the free exercise thereof; or abridging the freedom of speech, or of the press; or the right of the people peaceably to assemble, and to petition the Government for a redress of grievances.”

In the context of an AI maker defending against a lawsuit, they are aiming to invoke the freedom of speech clause that’s contained within the First Amendment.

The First Amendment overall is a commonly bantered topic nowadays. It seems that society currently has a murky understanding of what freedom of speech entails. Some people seem to believe that freedom of speech is utterly unlimited. That’s just not true. There are numerous exceptions having to do with bona fide threats, incitement, defamation, and so on. The classic line is that you aren’t legally off the hook when yelling fire in a crowded theatre that has no fire.

Also, another misunderstanding involves the scope. Freedom of speech has to do with the rights regarding government censorship and possible retaliation. Anyway, tossing the First Amendment into the mix for these types of lawsuits is a worthy Hail Mary.

Defense Strategy: Product Liability, Generally

Let’s briefly explore products versus services.

You buy a car. It seems obvious to say that you have bought a product. The car comes with a subscription to a GPS capability. The GPS is clearly a type of service. Voila, there are products, and there are services in the world around us. In the law, there is an entire body of legal aspects involving product liability, which is distinct from services.

When someone uses AI, would you say they are using a product or a service?

If the AI is construed as a product, the whole kit and kaboodle of product liability is likely to enter the arena. On the other hand, if the AI is construed as a service, the AI does not fall into that product-oriented realm.

As a defense strategy, the claim would be that the AI is a service, and decidedly not a product, which then skirts all the product liability considerations. But can the argument stand close scrutiny that the AI is a service and not a product? That’s the zillion-dollar question. You can make a reasoned claim that an LLM or generative AI is a product, or at least a combination of both product and service. That’s going to demonstrably help the plaintiff.

Defense Strategy: State of the Art

As an expert witness in court cases, I’ve dealt with the thorny matter of what constitutes the state-of-the-art in the AI field.

Here’s why state-of-the-art is crucial in these lawsuits. An AI maker is going to contend that they did everything as much as possible per state-of-the-art. For example, the AI safeguards they instituted were the best known and best capable at the time. This is important because even if state-of-the-art further advances, and a year later we have something new, the AI maker can argue that those new safeguards weren’t known at the time of the circumstance at hand.

They did what was best possible at the time.

To poke holes in this defense position, the opposing side would argue that the AI maker did not abide by the state-of-the-art at the time. The AI maker was less than state-of-the-art. Perhaps the AI maker was lazy. Maybe the AI maker didn’t want to spend the money. All sorts of reasons might explain this. Bottom line is that they shirked their responsibility and should be held accountable accordingly.

Defense Strategy: Mootness / No Equitable Relief

Another defense strategy that can be employed is that various aspects of the lawsuit are claimed to be moot. Mootness has to do with the assertion that there are matters that have already been resolved and are no longer of practical significance.

For example, suppose the plaintiff asks that the courts compel an AI maker to implement a particular AI safeguard that was not present at the time of the circumstances at hand. Imagine that the AI maker had already adopted such a safeguard, doing so after the time period in question. The AI maker would naturally want to insist that there is no need to compel the AI safeguard to be adopted since it has already been undertaken.

There is room for debate in even something as seemingly simple as the mootness claim. Here’s why. Suppose a lawsuit says that the AI safeguard of type Z needs to be adopted. The AI maker claims they have already implemented Z, but the plaintiff argues that the AI maker actually implemented R. The plaintiff believes that R isn’t the same as Z. I think you can see how this will potentially go around and around.

Defense Strategy: Section 230

In the United States, Section 230 of the Communications Act establishes a form of immunity for online platforms. You are almost certainly vaguely aware of Section 230 due to the social media vendors being granted a kind of hall pass for what users on social media post.

The formative idea was that the Internet was such an important invention and advancement for society that we didn’t want to bog it down when it first got underway. The vendors or platforms are not especially held liable for third-party content (well, it is wide immunity but not total immunity).

Some ardently believe the clock has run its course and we need to sunset Section 230. Make the platforms liable. We can get the zaniness of social media back under suitable control. Others shudder at what curtailing or outright collapsing Section 230 would do. It would seemingly suppress Internet speech and have a tremendous impact on activism.

A defensive strategy by an AI maker is to argue that they and their AI come under the auspices of Section 230. This would be a handy forcefield of legal protection.

Do you think it is legally apt that an AI maker of generative AI asserts that their AI is akin to what a social media platform does?

The logic is that the AI is merely reproducing in a transformative way the content that the AI was data trained on from the Internet. Thus, it is the same as a social media platform that merely provides third-party content. You can bet that this unresolved legal question will inevitably end up at the U.S. Supreme Court. Meanwhile, it’s a worthwhile defense strategy, and maybe it will turn out that way in the long run (or not).

Defense Strategy: No Punitive Damages

Punitive damages in civil cases are extra compensation that is requested by the plaintiff, in addition to compensatory damages that the plaintiff is asking for. The idea is that compensatory damages might be insufficient to get a defendant to change their ways and realize the wrongs they have presumably committed. It has to do with recognizing and penalizing serious misconduct or egregious acts.

A standard defense strategy is to pretty much always claim that there isn’t any basis for punitive damages. Then, you fight over this during the lawsuit.

Defense Strategy: Contract

Similar to my earlier points about online licensing agreements, a defensive strategy is to emphasize that the contractual obligations of a service agreement associated with the AI knock out some or all of the legal claims in the lawsuit.

Here’s another example. Suppose the online agreement for the use of generative AI stipulated that a user who is a non-adult must have parental consent to use the AI. If the facts reveal that the person was a non-adult and they did not obtain parental consent, the argument would be made that the person violated the licensing agreement. Ergo, the AI maker is off the hook.

Counterpoints abound. What if the AI didn’t sufficiently check to ascertain that the user was a non-adult? Perhaps the AI didn’t do enough, and the AI maker didn’t do enough, to properly vet and verify their users’ ages. And so on.

Defense Strategy: Reservation of Rights / Additional Defenses

The defense will undoubtedly surface additional defense strategies during the course of the lawsuit. At the time of initially filing a reply, not every possible defense has necessarily yet been identified. The defense, therefore, includes a clause that they are likely to have more legal defenses ahead, and the court and the plaintiff are given notice that the defense positions stated are subject to change and to further additions.

The Evolving Era Of AI And The Law

For those of you generally interested in the topic of AI and the law, you might find informative my comprehensive overview of the fast-moving field — see the link here and the link here. The field is wide open for lawyers looking to make their name in a realm that is still in a nascent stage.

AI keeps changing. The law keeps changing. That’s two comingling elements that are both immersed in evolving substantial change. Exciting times, for sure.

We’ve got laws about AI that keep being proposed, some of which have been enacted. For my analysis of the AI mental health law in Illinois, see the link here, for the law in Utah, see the link here, and for the law in Nevada, see the link here. There will be court cases that test those new laws. The pervasive access to AI is going to fuel an abundance of civil lawsuits. It is all expanding and entails intriguing questions about technology, AI, society, and the law.

How do we balance the immense benefits of AI with potential downsides?

The law has a huge role in answering that pivotal question. We will need to work together and figure this out as we go along. Indeed, per the memorable words of Oliver Wendell Holmes, Jr.: “The life of the law has not been logic; it has been experience.”

Get ready for quite a series of memorable and groundbreaking experiences in the years ahead.