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If there is one industry that AI experts are sure will be significantly transformed by innovations in artificial intelligence, it is the legal industry.

The reason for this is the obscene amount of paperwork and the drudgery related to the analysis of said paperwork. 

Perhaps the most important thing to understand about AI is that it is very capable of quickly analyzing and making predictions about big data.

Data comes in many shapes, sizes, and types, and one form of data is texts in natural languages like English. 

So, analyzing a mountain of paperwork, such as court documents, is certainly within the wheelhouse of AI systems capable of Natural Language Processing (NLP). 

In this blog, we will cover three ways that AI is going to change the legal industry, and then cover how exactly it does that. 


Analyzing and Summarizing Data

For lawyers, one of the biggest time sinks comes from having to sit down and pore over stacks upon stacks of records, documents, and other information-dense materials. Or, increasingly nowadays, whatever the digital version of paper towers are (PDF towers?). 

Anyways, so often it is the case that the lawyer is looking for particular details within the documents, rather than the whole of the documents. It is those tiny details that can make or break cases, and since most cases are time-sensitive there can be a lot of pressure to not waste one’s time reading the nonessential bits of otherwise crucial material. 

AI in law offers lawyers a highly sophisticated form of “seek and find” capability. Think of this as like CTRL+F on steroids.

Let’s suppose you are an injury lawyer working for a client looking to sue the owners of a dog park because a stray poodle bit your client’s leg when he refused to throw the dog a bone. This is a high-profile case that has been going on for months, and there have been many days in court already with truly mind-boggling amounts of writings—which, recall, are a form of data. 

Across all this data, from court stenographers’ transcriptions to police interviews, you are looking for anything that would suggest that the stray poodle got into the dog park because of the park owners’ neglect. By assigning the task of finding such evidence to AI, it will direct you to any relevant passages that assist in building your case.

Without having to do the drudgery of finding the crucial passages yourself, you can spend more time on building a compelling case for your client. 


AI in Law Can Produce Legal Writings

On the other end of the paperwork workload for lawyers is producing materials. Notes and gathered materials form the basis for producing legal writings. 

Oftentimes, legal writings are simply articulations of things that the lawyer has already gained knowledge of through research. All a lawyer would need to do is pass on notes and other relevant materials to a generative AI platform that will then make quick work of producing a legal document that hits all the important notes. 

So, for the lawyer looking to sue the dog park, being able to quickly make a lucid document that argues for the client’s case can be built from previously gathered materials. 

All that needs to be done is offering the relevant materials to the AI platform along with clear directions for the platform to create a certain kind of writing. And, of course, a review of that writing. 


AI in Law and Judges and Juries

The consideration of implementing AI judges and juries in courtroom settings is further in the future than the above two changes, but it holds strong potential.

This is not as dystopian as it may seem once you realize that the possibility is extremely low that these AI judges and juries will outright replace human judges and juries. 

Rather, these will likely function as another pair of “eyes” for the case, with the hope of providing something like objectivity in analyzing things like hard evidence. AI predicts based on available data, and the ability to predict innocence or guilt based on specific factors can provide valuable assistance to humans who have the same task.

Not every case is sensational and emotionally charged. Some are actually quite boring and rely on the analysis of hard data to make decisions. Consider insurance fraud cases, where AI in law can assist a jury by analyzing the same insurance claims that the jury reads. Are the numbers off? AI can help jurors—and judges—add to their existing base of knowledge about the case through data analysis. 

Think of it as like doctors who will perform diagnoses with AI The AI is there to assist the doctors in making a more accurate diagnosis, rather than doing the work for the doctor. 


How Will AI Perform These Tasks?

There is a field of AI that is called Natural Language Processing (NLP).

Natural language processing is concerned with teaching AI systems to understand the logic that governs natural languages like English. 

For instance, why does a sentence like “the long-limbed fourth grader climbed up the palm tree to pluck off the milk-filled coconuts” maintain grammatical correctness, whereas a sentence like “clock car nice fun fun plow treason” lacks meaning?

This is because natural languages are all rule-based, and a big part of the rules for any language is defining what words, and “types” of words (e.g., nouns, pronouns, verbs, and the like), can coexist with each other in certain orders. 

What NLP does is enable AI systems to analyze texts in natural languages and discover the rules of that language. Through training, AI gains an understanding of what words do and do not go together, what sentences and phrases make sense and which do not according to the laws of a given language. 

In the field of law, NLP will come into play when it is typing up those summaries and detecting crucial information in scores of papers. All the AI is really doing is making predictions about what kind of sentence the lawyer wants the AI to create, based on a prompt, and then creating a sentence of that kind. 

Interested in implementing AI into your law firm or business?  GO AI today.


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Guardian Owl Digital is dedicated to helping businesses everywhere learn about and implement AI 

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