5 Common AI Legal Issues to Watch Out For

Why Law Firms Are Using AI Tools

Why are law firms using AI tools in the first place? Artificial intelligence is not a new concept, but as it expands its capabilities to handle more time-consuming legal tasks, more and more law firms are riding the wave.

For example, AI can:

• Zip through tasks like sorting documents and doing legal research way faster than humans. This means lawyers can spend less time on the boring stuff and more on the complex legal work.
• Cut down on the hours that need to be paid for, which helps keep costs down. Cheaper operations mean firms can either boost profits or pass savings onto their clients.
• Spot patterns and trends in huge piles of data—stuff that might slip past a human, which can help lawyers make better decisions based on solid data.
• Handle basic customer service tasks like answering questions, booking appointments, and providing updates around the clock.
• Handle the extra workload without needing to hire more staff.

5 Most Common Legal Issues Surrounding AI

AI systems have integrated and continue to integrate into many aspects of our lives. In the law industry, however, the use of AI has led to a complex web of legal risks and undefined rules.

Does this mean you should scrap your AI system altogether? Not exactly, but there are several key legal issues that every law firm needs to be wary of:

1. Poor Accuracy

An AI system is only as good as the data it learns from. If the data is bad, incomplete, or biased, then the AI’s outputs will probably be off the mark too. This can lead to legal headaches, especially if decisions made based on these outputs adversely affect individuals or result in discriminatory outcomes.

Imagine a law firm using AI to give clients advice about how likely they are to win in court. The AI tool works by analyzing tons of past cases, looking at what decisions judges made, and the arguments that played well.

However, let’s say the AI’s data isn’t up-to-date—it’s missing recent cases or doesn’t include information from certain areas. If the AI’s prediction ends up being way off because of this, and a client follows that advice and loses their case, they might end up losing time, money, or a crucial legal opportunity.

All that said, law firms have to be sure that the data feeding their AI is top-notch and up-to-date to avoid these pitfalls. Sadly, it’s not as easy as it sounds. They also have to make sure that the developer is using reliable training data for their AI models.

Plus, AI systems need regular check-ups to stay accurate. Legal standards shift, new data comes in, and AI systems need to adapt to these changes. Law firms should have processes in place to keep testing and updating their AI tools to make sure they stay reliable and effective under the latest legal conditions.

2. Intellectual Property Issues

When it comes to AI and intellectual property, law firms face several unique challenges. AI can create, manipulate, and interact with IP in ways that traditional legal frameworks are still trying to fully understand and regulate.

Who Owns AI-Generated Content?

One of the biggest questions is who owns the intellectual property created by AI systems. For instance, if a generative AI program drafts a contract or creates a legal document, who holds the copyright—the law firm, the AI developer, or the AI itself?

Currently, most jurisdictions require a human author for copyright protection, which complicates matters when AI is doing much of the creation.

Protecting Law Firm IP

Law firms also need to think about protecting their own intellectual property rights when they use AI tools. This includes proprietary data, legal strategies, and custom-developed software.

When using third-party AI solutions, firms must ensure that their IP rights are safeguarded in any licensing agreements. They also need to prevent unauthorized use of their AI-driven tools and content.

Infringement Risks

AI systems can process vast amounts of data from various sources, and there’s a risk they might use content that is copyrighted by others without permission.

Law firms need to implement safeguards to ensure that their AI tools do not inadvertently infringe on someone else’s IP rights. This might include using only properly licensed data or implementing checks to make sure that any third-party content is used legally.

3. Failure to Protect Personal and Confidential Data

AI technology, while incredibly useful, brings a bunch of privacy and data protection issues that can quickly turn into legal implications. Let’s also not forget that law firms have a responsibility to protect personal data.

Here’s a look at how AI can stir up privacy and legal issues:

Collecting Too Much Information

AI loves data—the more, the better for its algorithms. But collecting tons of data, especially personal stuff, can be problematic if it’s done without people’s clear consent or breaks data protection laws. Also, AI can allow a level of watching and tracking that goes way beyond traditional methods.

This can raise big red flags about how much companies know about individuals and whether people even know they’re being watched.

Data Leaks

With more AI use comes a higher risk of data breaches. AI systems can be hacker targets and might even be the weakest link in cybersecurity if they’re not built with security as a priority.

Legal trouble pops up when these breaches involve losing or exposing personal data, which can lead to potentially hefty fines under laws like the GDPR.

Unintentional Discrimination

AI can also show biases in processing data and lead to unfair outcomes.

Say an AI system used for hiring is trained on biased historical data—it might keep favoring certain groups over others. This isn’t just a bad look—it’s legally risky, as it could violate anti-discrimination laws. Making sure AI systems are fair and unbiased is crucial, not just technically but legally, too.

Keeping Things Clear

Privacy laws often demand clarity about how personal data is used, but AI can make this tricky. AI algorithms can be like black boxes, hard to explain even for those who create them, and complicating efforts to be transparent as required by law.

Plus, figuring out who’s responsible when AI decisions cause harm or invade privacy can be a real puzzle, making accountability a serious concern.

Navigating Global Laws

AI doesn’t stop at borders—it often handles data from different places with different privacy standards. This global operation can lead to tricky legal challenges as companies need to navigate a complex mix of privacy and data protection laws.

For example, sending personal data from the EU to less strict countries can break GDPR rules unless you’ve got the right safeguards in place.

4. Open-Source License Compliance Problems

Open-source software is great because it’s freely available, but it comes with rules on how you can use, change, and share it.

These rules are laid out in licenses, which can range from super lenient (like MIT or Apache licenses) that pretty much let you do whatever you want, to stricter ones (like GPL) that have more conditions, like requiring you to share your modifications under the same terms.

Law firms need to really understand these licenses to make sure they’re using open-source software the right way. Why? Not following these licenses can lead to lawsuits or having to make your own software code public if it includes open-source code under a strict license. This is especially risky for law firms that tweak open-source software for their own tools.

5. Tort Liability

Tort liability is about holding someone responsible for harm caused to another person. When it comes to AI, if a system makes a biased decision that ends up harming someone, this could lead to a tort claim.

AI bias happens when an algorithm unfairly favors or discriminates against certain groups because of skewed data inputs, mistakes in the programming, or other factors. This kind of bias can result in serious issues, like unfair hiring decisions, biased policing, or unequal loan approvals.

Who’s to Blame When AI Messes Up?

Figuring out who has legal liability for AI errors is tricky. If an AI system delivers poor legal advice or messes up data analysis, is it the fault of the AI’s developers, the law firm using it, or the people who supplied the data?

To reduce their legal risk, law firms often sort this out with detailed contracts that lay out who’s liable if the AI doesn’t perform as expected.

What Risks Do Law Firms Face When Using AI Systems?

When law firms integrate AI systems into their operations, they open themselves up to a new set of risks. Understanding these risks is important for law firms to manage them effectively and harness the benefits of AI without facing setbacks.

• Overdependence on AI: Relying too much on AI for decision-making can lead to issues if the AI provides flawed advice or analyses, which can potentially lead to poor outcomes for clients and legal malpractice claims.
• Data security vulnerabilities: AI systems handle a lot of sensitive data. Any weakness in the system can lead to data breaches, risking exposure of confidential client information, and violations of data protection laws like GDPR.
• Compliance challenges: Ensuring that AI systems comply with all relevant legal and regulatory frameworks is complex. Non-compliance can lead to fines, legal disputes, and damage to the firm’s credibility.
• Bias and discrimination: If AI tools are built on biased data sets or flawed algorithms, they can produce discriminatory outcomes. This can lead to legal challenges and harm the firm’s reputation and client relationships.
• Intellectual property issues: Using AI can raise questions about the ownership of the generated content and the software itself, which can potentially lead to IP disputes.
• Lack of transparency: AI’s decision-making process can be a “black box,” making it hard to explain how conclusions were reached. This lack of transparency can be problematic in legal settings where justification of methods and findings is required.
• Client trust and confidentiality: AI tools must be designed to maintain strict confidentiality of client information. Any failure in this area can erode client trust and result in legal consequences.

Use a Generative AI Tool You Can Trust

Briefpoint.ai was designed with proper training and ethical considerations in mind to reduce the risks that come with generative AI. While due diligence is still a must for our users, Briefpoint uses strict security measures to protect data privacy:

• In-Transit and At-Rest Encryption
• Automatic Backups and Redundant Servers
• Secure Development Practices
• Payment and Login Security Measures

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