AI in Law

AI in Law

Intro

In most countries around the world, AI is entering the law field and the laws that are written as very clear in most countries – they are there in black and white, and there’s no room for interpretation. But as human beings, there is a constant need to ensure that things are correct, things are right, and things are as they should be.

This leads to a need for court rooms and judges, trials by jury, and a decision on guilt or innocence being made as an interpretation of the written laws weighed up against the actions of an individual.

Entering AI in Law

Common Use

Machine learning and NLP have enabled a number of AI tools to be developed to help legal departments reduce costs, develop data-driven strategies, assess risk, and become more productive. Below, we identify some of the AI tools that are available to legal departments.

Natural language processing (NLP) is another application of AI in which the AI epochs automatically process and interpret words based on the context actual context. For example, rather than iterating over each character or word in isolation, NLP processes the word based on the other words used in the same phrase or sentence in which the word appears and the topic or application in which the word is used. Comparable to law and fiduciary duty that requires attorneys to analyze terms in a contract, identify facts of a case or find case law.

AI In Law in CA

The reader knows people who, after conviction of a crime, then years later, the statute changes. For example, before California’s Proposition 64, the possession and use of marijuana were illegal in the state. In 2016, it became legal.

This simply meant that for those with prior convictions in relation to marijuana, they could have them struck from the record – an important move, as convictions of that nature, could impact the opportunity to get a job.

The city of San Francisco had been digitizing its files since 1975. It seems to. Some people think the judge will flip a switch and all he cases are overturned, fortunately, that’s not how digitization works.

What San Francisco (and many other cities) had stored was effectively a photograph of paper documents, viewable on a computer, but completely unreadable by a computer. To have a conviction removed, an individual must fill in the paperwork to begin the process, and that paperwork may not be simple at all.

San Francisco estimated that 10,000 people could apply to this process, but by 2018 only 23 people had identified themselves. The city took a lot of time manually going through the documents and found 1230 eligible people. There had to be a better way.

With the advancement of optical character recognition (OCR), automation, and artificial intelligence, a program was devised that could process the digitized records and attempt to understand what they said. If a record included mention of a violent crime, the program discarded it as the individual would be ineligible. A human was notified when a file had any issues. But overall, the software ran itself and produced a result.

The Results

Within minutes, it was able to identify another 8000 people who were eligible to have their convictions cleared.

The judge signed them with one action, and the criminal records of thousands of people were suddenly revised, opening new horizons for each one. And saving the city (and those individuals) a massive amount of work and resources.

How does it work?

OCR has been around for quite a long time, without AI, it is mostly useless for tasks of this nature. Macine Learning has the ability to learn and understand. That gives the opportunity for thousands of documents to be processed by a tireless machine that doesn’t make mistakes in the same way that a human might. The AI industry is prone to calling these algorithms “robots”, as the dictionary definition of a robot includes “…that are able to replicate certain human movements and functions automatically” – by reading and understanding, they are replicating what a human could do.

The artificial intelligence portion of such software allows true understanding and learning. You could use a keyword search to determine if “violent crime” featured on any record, but the context is important. The program did not discard the records with, “never been in violent crime”. The program did discard records with, “until now”. That AI understood the nuances.

A programmer was notified, in the California example. The programmer found the bug, debugged code and allowed the algorithm to be corrected. True machine learning would future judgments based on what was learned from how the human reacted. That is only one instance of AI in law.

The future of AI and Law

AI systems are analyzing records and finding convictions and flag them for removal.

Finding a jury that is truly impartial is always difficult, whereas a machine will be impartial by default. Software developers have created programs to help reach verdicts. More importantly, would the public trust such a machine?

It seems as if it is science fiction, but it is much closer to reality than you might think.

For many law practices, the ability to process large amounts of paperwork quickly would be truly beneficial. Summary of cases is much easier and quicker. it takes a few minutes. In fact, there are many services available today that will digitize and process business paperwork using software robots. Large companies that send paper bills to thousands of people (for example, credit card companies) already make use of this technology to process incoming payments – but that’s the tip of the iceberg.

Would a trained law practitioner have a better understanding of a case than a computer? Is there even a possibility that law practices could be replace by AI?

Have you ever received a ticket in the mail? An automated system does that. The vehicle was avoiding an accident from happening. Could machine learning help to prevent false positives like this? And if so, would it reduce the need for legal representation in such cases?

The legal system has come a long way in the last decade, and the move towards digital devices is unstoppable. The questions are, how far are you willing to trust them within a law practice? Would you have confidence in a courtroom under the jurisdiction of a robot judge? As technology is improving, it may only be a matter of time before this science fiction becomes science fact.

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