Courting Change: AI’s Evolving Role in Legal Documentation

Summary: Artificial intelligence is transforming the way many industries do business – including the legal sector. The positive impact of AI on document processes and workflows is hard to deny, but it’s important to remain aware of this technology’s limitations. Explore the benefits, potential drawbacks, and important considerations associated with incorporating AI tools into legal documentation.

Virtually every industry has been touched by AI in some way, from chatbots to operations optimization, data analysis, and content generation. (This blog post is 100% written by humans, though.) And with the global artificial intelligence market expected to reach a value of US$407 billion by 2027, it’s no wonder companies of all kinds are hungry for their slice of the AI pie.

The legal sector is no exception. Despite what might appear to be conflicting interests like privacy and hallucinations, AI has affected and continues to transform law practices. The opportunity for positive impact is tremendous – especially where documents are concerned.

There is now an abundance of secure and reliable AI tools for automating document generation, redaction, analysis, and more. There’s still a lot of room for improvement in the AI space, but successful implementation is possible. Ultimately, the path forward involves finding the tools that fit specific workflows best, staying up to date on new advancements, and being knowledgeable about both the possibilities and drawbacks of this technology.

Let’s dive deeper into the good, the bad, and the grey area of AI’s role in legal documentation.

It’s not just about having access to innovative tools but knowing how to use them. Here are some benefits of incorporating AI into legal document workflows.

Nobody’s perfect. Manual processes tend to be error-prone, which could mean serious consequences for both professionals and clients. Mistakes in legal documents can lead to lawsuits, disputes, inaccurate legal research, and more. Automating document generation, redaction, extraction, and analysis workflows helps eliminate human-caused errors and minimize the associated risks.

AI enables legal professionals to spend less time and administrative resources on repetitive document-related tasks. For example, redaction of sensitive information is essential for maintaining confidentiality, but can be extremely time-consuming if there’s a large volume of documents. Tools like Apryse WebViewer can save on costs by providing automatic redaction features that are fast, accurate, secure, and permanent.

Saving time and money can also help law offices improve services and increase client satisfaction. Automation promotes timely document turnaround and processing, which is especially useful for delivering critical documentation when deadlines are looming. Using AI to lower the cost of document processing also means firms have the option of passing on the savings and lowering fees in certain cases, which makes legal services accessible to a wider range of people.

In a nutshell, incorporating AI tools into document processing workflows enables law offices to do more with the resources they already have. And that includes growing a practice. Automation frees up time and resources, so firms can devote those resources to higher value work and helping a larger number of clients.

Learn more about document automation and SDKs (Software Development Kits) for the legal sector.

As with any nascent technology, AI still has bugs to work out and hurdles to overcome. Here’s a look at some of the downsides.

To err is human, but it can also happen with AI. Hallucinations are nonsensical or incorrect outputs provided by an AI in response to a request. Sometimes AI models perceive patterns where none exist and produce a response based on this nonexistent pattern. In human terms, it’s like coming up with a conspiracy theory or recognizing faces in inanimate objects. This can be problematic for several reasons, but particularly in an industry where accuracy and verifiable precedents are paramount.

Blindly trusting generative AI can be disastrous for legal professionals. In the now infamous case of Mata v. Avianca, lawyer Steven Schwartz used ChatGPT to prepare a filing that cited several other cases to establish precedent. Just one problem: six of those cases didn’t actually exist. The error was discovered when the court couldn’t find documentation on the cited cases. The issue deepened when Schwartz revealed he’d asked the AI tool to confirm the cases were real. ChatGPT insisted they were.

This case shows that though generative AI can be used to save time when preparing legal documents, it’s critical to be aware of a tool’s limitations, especially if it’s new. And it always pays to triple-check your sources.

Justice may be blind, but AI sees all. And that can be a problem when it comes to bias. AI models are trained using vast amounts of human-generated data. In addition, humans choose the data AI models train on. So, any bias in the data can translate to the AI model and influence how it generates responses.

This can have an immense impact in the criminal justice system when it comes to profiling based on race, gender, and other factors. For example, an analysis by ProPublica found a significant racial disparity in a computer algorithm designed to predict how likely a defendant is to reoffend in the future. The system was nearly twice as likely to label Black defendants as future criminals compared to white offenders, regardless of past criminal history or the type of crime committed.

There are several steps developers can take to reduce AI bias, but it’s a complex problem. Until it’s completely solved, it’s important to remain vigilant about potential bias in AI-generated documents.

AI can do many things, but when it comes to predicting the future outcomes of this technology, some aspects remain unclear.

Is AI coming for our jobs? 36% of people around the world think so, according to an Ipsos survey. When it comes to the legal sector, there might be a bit of justifiable concern. Of course, AI isn’t going to replace lawyers anytime soon. (Case in point: the hallucination example above.) However, a study by Goldman Sachs showed that an estimated 44% of tasks in the legal profession could conceivably be automated, second only to administrative at 46%.

It is true that many legal document-related tasks can be automated, which could eventually reduce the need for administrative support. But as the Schwartz saga proves, AI still needs a significant amount of human oversight. In the interim, it’s far more likely that AI tools will be used to improve efficiency and scale up services rather than put people out of a job.

AI’s uncanny ability to provide exactly what you’re looking for comes from an astonishingly vast quantity of data. However, the sources of data used to train AI models have long been subject to questions and scrutiny. Just how much of an individual’s personal data has been fed into this technology? How is it stored? Who can access it? And how is it being protected? These questions are the subject of ongoing ethical debates in the legal sector and beyond as data protection laws struggle to move at the speed of technological innovation.

These are valid concerns, but AI can also be used to help preserve data privacy and stay in compliance with laws like GDPR (General Data Protection Regulation). Tools like automated document redaction can quickly and permanently remove a client’s personal information and metadata from a large volume of documents.

Want to know more about redaction? Check out our Ultimate Redaction Guide.

As we’ve seen, AI has the potential to make a significant impact on the legal sector. If you’d like to try out some of the features discussed in this blog post, including redaction tools, feel free to explore the demo. To see our redaction tools in action, check out our Egress case study. If you have questions about automation capabilities, get in touch with our team.