10 (More) Potential Defense Strategies in Artificial Intelligence Litigation
Artificial Intelligence Team Lead
Contact NickArtificial intelligence (AI) presents both unprecedented opportunities and unprecedented challenges. As AI continues to gain mainstream acceptance, more companies are finding ways to use generative and predictive AI tools in ways that set them apart from their competition. AI efficiently streamlines the automation of various tasks in drafting contracts, motions, pleadings, and other legal documents. At the same time, however, these innovative uses present risks for litigation, and as AI grows in popularity, the volume of AI-related litigation is also growing.
We have previously covered potential defense strategies in artificial intelligence litigation. In that article, titled 10 Defense Strategies in AI Litigation, we discussed some examples of potential commercial and governmental claims. We outlined some examples of potential defense strategies for each type of litigation. Based on legal research, the defenses we discussed for commercial litigation include the following:
- Relying on contractual protections
- Reasonable efforts to ensure accuracy or protect privacy
- Assumption of risk
- Improper use of the AI tool or platform
- Insufficient evidence of a “defect”
- Insufficient basis for liability
The defenses we discussed for governmental litigation include:
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Good-faith efforts to comply (or reliance on the advice of counsel)
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Insufficient basis for civil liability or criminal culpability
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Working with the government to chart a path forward
These all remain viable options, and these can all prove to be key defense strategies in many types of AI-related litigation. However, as we said at the time, these are far from the only defenses that companies can assert when facing litigation—whether litigation with a customer or client, litigation with a vendor or competitor, or litigation with the government. With this in mind, we thought we would follow up by discussing other defenses targeted companies may have available.
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Due to the breadth of potential types of AI-related litigation, it is difficult to pen a comprehensive list of potential defense strategies. For example, litigation involving allegations of copyright or patent infringement will involve claims and defenses very different from those involving allegations of employment discrimination or violations of consumers’ or patients’ privacy. With this in mind, for this list, law firms focus on artificial intelligence litigation defense strategies that apply across the board—fully recognizing, once again, that these are far from the only available defenses.
Despite AI’s unique and constantly evolving nature, many (if not most) of the fundamentals of litigation will be the same regardless of the substantive issues involved. Thus, for example, while AI-related lawsuits involving IP-related and privacy-related claims are very different, companies targeted in both types of lawsuits can rely on many of the same general defense strategies. Some examples of these strategies from the legal industry include:
1. Asserting Counterclaims
Companies targeted in AI-related lawsuits can assert counterclaims in many (but not all) cases. For example, if the plaintiff is a client or customer alleging that its use of the defendant’s AI platform led to commercial losses or civil liability, the defendant may be able to assert a counterclaim for intellectual property infringement or breach of contract. Or, if a competitor is alleging infringement, the defendant may be able to assert a counterclaim alleging that the competitor’s AI platform is infringing.
These are very specific examples of legal issues, and there are numerous possible permutations of AI-related litigation, as noted above. However, the general principle applies broadly: When targeted in AI-related litigation, companies can (and should) assess the viability of using counterclaims to turn the tables on the plaintiff.
2. Asserting Cross Claims and Interpleading Additional Defendants
Along with filing counterclaims, companies targeted in AI-related litigation may be able to defend themselves by asserting cross-claims and interpleading additional (or alternate) defendants. This strategy is particularly likely applicable in litigation involving claims against AI licensees. While the terms of the AI license in question will be critical, licensees may be able to use cross-claims or interpleaders to bring their licensors into the litigation—and potentially extract themselves in the process.
3. Leveraging the Discovery Process
Discovery is a key phase in large-scale civil or commercial litigation. While discovery is often viewed as advantageous to the plaintiff, defendants in the legal profession can (and should) leverage the discovery process to their advantage.
How? There are several possibilities. One possibility is to gather information from the plaintiff to demonstrate fatal flaws in the plaintiff’s substantive allegations or damages calculations. Another possibility is to use the discovery process to substantiate counterclaims. While defendants must manage the discovery process in good faith, defendants can also use the burdens of discovery and their right to challenge flawed discovery requests to increase the costs of pursuing litigation for plaintiffs.
4. Protecting Sensitive Information During Discovery
While plaintiffs can obtain information relevant to their claims through the discovery process, the old adage that discovery is not a fishing expedition holds true. Plaintiffs cannot use litigation to gain access to sensitive information when they do not have claims to pursue in the first place. Additionally, while defendants must manage the discovery process in good faith, as noted above, this does not mean that defendants have to interpret plaintiffs’ discovery requests broadly or disclose sensitive information they are entitled to withhold. In many cases, protecting sensitive information during the discovery process can leave plaintiffs without the evidence they need to move forward.
5. Challenging the Plaintiff’s (or Government’s) Choice of Jurisdiction and Venue
Targeted companies can also use challenges to jurisdiction and venue to defend against commercial, civil, and criminal litigation in many cases. With technology in general—and artificial intelligence in particular—determining the appropriate jurisdiction and venue for litigation can be far from straightforward.
Additionally, plaintiffs’ legal professionals pursuing AI-related claims may file their clients’ lawsuits in a court that has issued plaintiff-friendly rulings in the past (a practice known as “forum shopping”). If this forum is improper, demonstrating that this is the case could force the plaintiff to pursue its lawsuit elsewhere. If litigating in an alternate forum presents additional uncertainty, this could set the stage for a favorable pre-trial resolution.
6. Distinguishing Between Moral and Legal Arguments (and Highlighting Deficiencies in the Law)
The law surrounding AI systems is still developing, which will remain the case for years. As a result, many plaintiffs are pursuing claims based on what they believe should be just—but without legal authority to back them up. By distinguishing between moral and legal arguments (and highlighting deficiencies in the law), targeted companies may convincingly argue that there are no applicable grounds for a judge to rule in a plaintiff’s favor.
7. Pursuing Strategic Settlement Negotiations as Warranted
While targeted companies should never assume that settling is their best option, pursuing strategic settlement negotiations will sometimes be warranted. In particular, settling artificial intelligence litigation may make sense if doing so will:
- Reduce the total cost of resolving the dispute at hand and/or,
- Avoid negative publicity and unfavorable precedent, which could presage additional lawsuits.
Several factors go into making informed decisions about settlement, and timing can also be hugely important. For example, while waiting to open settlement negotiations until after discovery can make sense when there is little for the plaintiff to find, if information uncovered during discovery will strengthen the plaintiff’s case, then waiting could prove to be a costly mistake.
8. Leveraging Pre-Trial Motions Practice
Leveraging pre-trial motions practice can be an effective defense strategy in artificial intelligence litigation as well. Filing motions to exclude evidence, dismiss claims, or potentially dismiss the plaintiff’s entire lawsuit can leave plaintiffs with little choice but to walk away or seek far less than they were hoping to seek at trial.
9. Focusing on the Plaintiff’s (or Government’s) Burden of Proof
We discussed this in our previous article, but it is worth mentioning again here. In all types of artificial intelligence litigation, the burden of proof rests with the plaintiff (or the government). If the plaintiff (or government) cannot prove its allegations—which, as discussed above, can be challenging in many cases with the current lack of AI-specific law—then the only just outcome is a verdict in favor of the defense.
Finally, while settling to avoid unfavorable precedent can be an advisable defense strategy in some cases, in others, it can be well worth litigating a case through trial. If taking a case to verdict is likely to establish a favorable precedent for future AI-related litigation, then litigating could be an effective defense strategy for the instant case and future cases.
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At Oberheiden P.C., we are at the forefront of AI-related litigation and relevant case law in the United States. If you would like to confidently speak with one of our artificial intelligence litigation attorneys, we invite you to get in touch. Please call 888-680-1745 or contact us online to schedule an appointment today.
