There’s no doubt that Big Data, Data Mining, and Machine Learning have changed every industry on the planet. Recent political campaigns were won by experts who knew how to use all data available regarding key factors. Many were surprised to learn how certain types of information could guide a political campaign down the pathway to a big win.
Data analytics has been used in the field of sports for many years. This is perhaps one of the first industries to fully embrace this concept. All professional sports organizations use volumes of data to understand past performances of rival teams. They analyze every bit of the information available to discover a competing team’s weaknesses. Then they use that information to build an arsenal of both offensive and defensive strategies.
It’s natural that the legal profession would want to gain the upper hand in this same manner. And, that is exactly what’s taken place in the last few years. Now we have teams who are experts in both technology and the law. Using the most sophisticated tools available, they decipher every morsel of legal information, including trial outcomes, court decisions, witness testimony, precedents and much more. This gives their side the competitive advantage.
However, the issues that the legal system faces differ a great deal from those of other industries. A sports team analyzes things like various plays and the results of those actions. In the legal field, every trial generates huge amounts of data. From the trial transcripts to the expert witnesses, the sheer volume of data sets the legal field apart from most other industries.
Last year, in the US alone, there were over 350,000 cases brought to court. And legal data is highly complex. It contains legal nuances that are hard to explain to most people, much less a computer program. Trial outcomes typically occur as a result of hard evidence, but sometimes they are a result of emotional juries. Since juries are made up of human beings, it’s very hard to predict with accuracy what they will do in any given situation. That’s the goal of trial science.
In the past, America has held very public trials for popular athletes accused of crimes like assault or even murder. All the evidence might point to the suspect being guilty. And yet, the jury had a previous emotional connection with the athlete because they enjoyed watching him play sports. Even with overwhelming evidence of guilt, the jury ruled that he was innocent.
How do you explain that type of irrational thinking to a computer? How will artificial intelligence deal with anomalies like this? These are just a few of the questions facing today’s data-driven attorneys. Though big data offers a world of opportunities, it also represents a substantial challenge even to the best legal researchers.
Today’s legal technology experts are continuously adding new information to their databases. Every trial and verdict is a new piece of information that the AI will use to build its intelligence platform. In fact, millions of pieces of data are added daily to the repository. These massive blocks of data require high-speed processors. Much of this is accomplished using data-parsing technology.
This process cleans raw data, refines and enhances it, and structures the data so it offers maximum insight to users. For instance, one program allows searchers to look at the decisions specific judges made in the past. This helps them build a profile of that judge’s legal philosophies. With great accuracy, these programs can predict how a judge will rule in a certain type of court case. Imagine being able to know with some degree of certainty, how a judge might rule on a specific case before the trial even begins.
The possibilities this technology provides are endless and offer a wealth of valuable information to attorneys. As the future unfolds for the legal field, experts believe that advanced technology will be used in every part of the law.
Of course, today it’s being used primarily by legal teams that want to win cases. There are often substantial financial reasons for wanting to win a big case. Today’s attorneys understand that clients are looking for the best team of lawyers. They want to work with the brightest people–winners. But, there’s more than just money on the line; a law firm is building its reputation as well. They want to build their brand to the place where their name is a byword in the legal world.
These are natural reasons for wanting to win at anything. However, many experts believe the future of legal technology holds much more than this. They believe the legal field can evolve into a much more fair, accurate and profitable industry. As a society, we can begin to get things right when it comes to verdicts in big cases. We can move past the place where known murderers are freed over a technicality. This is not a pipe dream for many in the legal field, it’s a destiny that must be achieved for our legal system to continue moving forward.
From making new laws to enforcing old ones, data mining and machine learning have the potential to show us where our society’s legal system has failed in the past. We can clearly see what has worked and what hasn’t. We can use this knowledge to move forward in a better direction. Unfair laws could be changed, and unfair verdicts could be a thing of the past.
That’s the hope of every reputable attorney. Today, we may use data mining and AI to gain a better advantage in a trial. Tomorrow, we may use them to mold our legal system into a fine-tuned instrument that delivers correct verdicts every time, and at a third of the cost.
40% of businesses will incorporate the anywhere operations model to accommodate the physical and digital experiences of both customers and employees (Techvera).
Forty-three percent of attacks are aimed at SMBs, but only 14% are prepared to defend themselves (Accenture).
The internal team was energized. With the Level 1 work off its plate, the team turned its attention to the work that fueled company growth and gave them job satisfaction.
It takes an average of 287 days for security teams to identify and contain a data breach, according to the “Cost of a Data Breach 2021” report released by IBM and Ponemon Institute.
More than 33 billion records will be stolen by cybercriminals by 2023, an increase of 175% from 2018.
The average cost of a data breach in the United States is $8.64 million, which is the highest in the world, while the most expensive sector for data breach costs is the healthcare industry, with an average of $7.13 million (IBM).
The three sectors with the biggest spending on cybersecurity are banking, manufacturing, and the central/federal government, accounting for 30% of overall spending (IDC).
The cost of cybercrime is predicted to hit $10.5 trillion by 2025, according to the latest version of the Cisco/Cybersecurity Ventures “2022 Cybersecurity Almanac.”.
We did a proof of concept that met every requirement that our customer might have. In fact, we saw a substantial improvement.
We did everything that we needed to do, financially speaking. We got our invoices out to customers, we deposited checks, all the things we needed to do to keep our business running, and our customers had no idea about the tragedy. It didn’t impact them at all.
“We believe our success is due to the strength of our team, the breadth of our services, our flexibility in responding to clients, and our focus on strategic support.”