Cookie Policy Effectiveness and Ethics – the Case for Deploying Advanced Legal Technology - eDiscovery, Digital Forensics, Cybersecurity - LDM Global

Data is more than the documents in a filing cabinet, emails on a laptop, information on a hard drive, or even messages on a cell phone. Every keystroke on a keyboard or tap of a smartphone adds to the mountain of virtual data.

The moment an individual or corporation becomes the subject of a legal matter, sifting through the mountains of data produced in everyday life becomes a task for experienced legal professionals using the latest tools and technology. Most professionals are unable to process the amount of information by hand. Instead, advanced analytics and artificial intelligence (AI), becomes essential tools for more effective and defensible discovery.

Electronically stored information, or ESI, includes information stored on devices like computers, tablets, cell phones, and laptops. ESI may be stored in shared filing systems, email servers, on social media platforms like Facebook, Twitter, or Instagram.

Searching through a mass of information by conducting a basic keyword search is both time-consuming and inefficient. Machine learning enables investigators to search through vast amounts of information early in a case or investigation without losing critical time or sacrificing thoroughness during the discovery period.

While some professionals might have doubts about the use of advanced legal technology to sort through electronic information, the American Bar Association reports that nearly two-thirds of lawyers have engaged in the use of technology to analyze information.

Why Machine Learning is becoming an Essential Tool for Lawyers

Time spent sorting through information adds to the workload of the legal team. The least efficient use of that time consumes the most in terms of personnel costs. Machine learning technology aids electronic discovery in the reduction of work hours spent pouring over large volumes of information, especially in the early stages of discovery.

In situations where there is no previous case information to fall back on, casting a wide net consumes massive amounts of time. Electronic discovery tools can streamline the process from the start. At the beginning of a case, the collection of data is a daunting undertaking. Given the amount of data produced by a single person today, manually sorting through that information is time-consuming.

More Than a Simple Word Search

Manual data searches are the dinosaur of investigations now that technology exists to sift through masses of information in a matter of seconds. Rather than reading through one file at a time, machine learning tools enable a search that expands beyond the confines of a manual keyword search. Artificial intelligence technology can look for patterns in phrasing and search for context and meaning outside the scope of the keywords. What this means for litigation support is an expanded search parameter that picks up on information that would have been otherwise missed in a more traditional review.

Clustering Data

Unlike searches based solely on keywords, machine learning tools can sort information by forming conceptual clusters. For example, a search through hundreds of documents that are based on keywords alone will return results of instances of just those keywords. These tools will search for information related to a specific subject. Instead of just searching for information about jazz, for instance, machine learning tools can find all references to music in general and even differentiate between different uses of the same word.

Narrowing Down Results

Almost as important as the need to find relevant data during an investigation is the need to eliminate irrelevant information. Artificial intelligence helps to cut out the information that is not relevant to a case so that by the time litigation support personnel begins their review only the most relevant information is considered.

Once the most relevant data is culled from the rest, advanced tools can assist human reviewers by prioritizing and cataloging the information presented. These tools can search out anomalies in the information as well. Emails sent during unusual hours, messages including a pressured tone, or communications between certain individuals discussing seemingly innocent topics can be grouped together for ease of more detailed review, for example.

Sensitive Information

Advances in machine learning have also provided tools that can help sort through sensitive or privileged information before it meets the eyes of human reviewers. Technology that is equipped with the ability to analyze using Natural Language Processing (NLP) analyzes both content and metadata.

The advanced use of NLP enables the software to distinguish between privileged information and everyday matters. In other words, NLP-enabled artificial intelligence technology can determine whether a document or an email is discussing a shopping list or sensitive trade secrets.

How Artificial Intelligence Affects Discovery Deadlines

In many US states, once a defendant is brought before a judge and read the charges against them, the countdown begins. In states where open discovery laws determine the information required to be available to defense teams, a deadline looms for the prosecution to provide that information.

Open discovery laws require prosecutors to provide all of the information not protected by privilege to the defense in a timely manner. This includes all of the information that is known or should be known. In this example, machine learning technology becomes a necessary part of the process of investigation.

Relying on litigation support team members to review, analyze, and organize information in a tight span of time is both inefficient and risky. Time is just part of the equation. Using AI and RPA tools transforms the process into a more thorough search. Crucial information is less likely to be missed due to human error or time constraints.

Making the Case for Technology

Despite the clear advantages using AI presents, there are still those reluctant to embrace the ever-changing face of eDiscovery tools. For many, the old process of manually checking files is the only way to ensure nothing is missed. For others, the cost of upgrading to the latest technology is too high.

Technology evolves constantly across all industries. In some cases, the use of yesterday’s technology might be slower than necessary, but it still gets the job done. In the context of litigation support, however, the use of less efficient and effective processes creates an unnecessary burden. Making the most of time is essential to a thorough investigation.

Return on Investment

No doubt the cost of upgrading to the latest legal technology is a legitimate concern. On the other hand, lagging behind the technology curve can be more expensive in the long run as the use of machine learning tools can improve the efficiency and effectiveness of litigation support teams.

In the end, it is a question of return on investment. Plugging away at manual searches a word at a time eats up precious work hours. Advanced analytic tools improve the compilation of information, and no price can be placed on the importance of information missed by human effort.

Old Dogs, New Tricks

Another cause for reluctance stems from the lack of desire to learn new things. Technology can be overwhelming to many people. It is a legitimate concern for time-pressed attorneys. The good news is that there are service providers such as LDM Global whose function is to train their clients in the use of the most advanced AI technology. These experts provide hands-on training that can demonstrate the effectiveness of the technological tools.

Ethical Reasons

In 2012, the American Bar Association modified its rules of professional conduct to include the need for attorneys to stay current on the changes of law and the practice of law. This includes, “staying abreast of the benefits and risks associated with relevant technology.”

What this means for practicing attorneys is that lawyers must stay on top of the latest tools that will benefit the practice of law. In other words, there is more to this professional conduct guideline where it relates to technology than just staying apprised of the data security risks. There is also an obligation to remain current on the best practices as well. It becomes a question of ethics to perform the job to the highest caliber possible. As ESI increases, so will the demand to leverage the latest tools to analyze the information contained therein.

Into the Future

It rests upon legal professionals to continue to adapt to the evolving digital world to provide the best services to clients. As attorneys, investigators, and litigation support team members, this means staying on top of the very latest advances in artificial intelligence tools. It is a matter of commitment to excellence as well as an ethical duty to provide the very best service with the newest tools in their arsenal.

Conor Looney is also an advisor to the Electronic Discovery Reference Model’s (EDRM) Global Advisory Council.
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