AI Legal Series

Legal AI Series [Chapter One]: The Guide to AI and the Legal Revolution

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The past two centuries have seen some of the most dramatic technological leaps in the history of humankind. Steam engines that connect continents. Personalized vehicles. The typewriter. Metal birds that can fly. Not to mention tiny boxes that can send and receive messages across the globe in less time than a blink.

Legal professionals have played a critical role in shaping the future of each of these new leaps, molding the path of invention through patents, contracts, legislation, and dispute resolution. However, we’d be lying if we said that the legal industry, itself, wasn’t also shaped by these advances.

One of the most dramatic, has been the introduction of artificial intelligence to the business world.

From e-discovery, to contract analytics, all the way up to predicting case outcomes, AI legal software is revolutionizing the industry, offering practical applications to common, everyday obstacles. And, as this technology continues to evolve, artificial intelligence shows every promise of being able to solve even the most complex legal problems of the future.


Artificial intelligence (or, “AI”) refers to software that is designed to mimic the learning and problem-solving behaviors of the human brain.

Technology gurus call this type of computing “machine learning.” By harnessing the power of complex algorithms, computers can make deductions, sort information, and find solutions faster and more efficiently than humans can on their own.

For attorneys, legal AI specifically relates to software designed to expedite routine processes and solve everyday problems that commonly arise during the practice of law, effectively tackling some of the main offenders of high costs and tight timelines that often plague firms. Here’s how.


Not so long ago, artificial intelligence was something most people delegated to the realm of science fiction. These days, it’s a different story.

Today, there isn’t a single industry that has not been impacted by the introduction of AI—including the legal arena, where AI platforms are being developed to offer niche solutions that specifically target the needs of legal professionals.

For example, take the document review giant, Relativity, and its eDiscovery platform, RelativityOne, a software designed to help process large quantities of data, and quickly identify key solutions that attorneys can act upon. Or, OpenText, a startup whose AI technology focuses on the acquisition, management, and analysis of data, using machine-assisted decision making to help optimize business performance.

Veritone is another such company to join this revolution, entering the fray as the first of its kind to harness the functioning power of hundreds of AI engines  into one, centralized operating system for artificial intelligence called aiWARE.  As a result of aiWARE’s open and extensible technology stack, many bespoke AI-enabled solutions for a wide range of industries (including legal and compliance industries) are built on top of aiWARE.  One such legal and compliance software application powered by aiWARE is: Veritone Illuminate.

Here are a few ways that Veritone and other companies are using AI in the legal sector to revolutionize the practice of law.

Legal Document Review

In layman’s terms, “document review” refers to the laborious process of sifting through massive evidence dumps during the discovery phase of a lawsuit.

Manually combing through this material is a slog. A time-consuming, multi-tiered quagmire that’s fraught with workforce shortages, exorbitant costs, human error, and ever-shifting directives from an indecisive legal team.

However, document review is also vital to case cultivation, producing necessary insights that help shape the direction of future arguments—not to mention the evidence to back them up.

Luckily, contract attorneys no longer have to tackle this slog alone. With the introduction of AI, legal software can be programmed to meet the specific needs and search parameters of any case.

eDiscovery and ESI

Nestled under the umbrella of document review, is the rapidly expanding category of e-discovery.

E-discovery (or, “electronic discovery”) is the area of document review that deals specifically with the processing, review, and organization of electronically stored information (ESI), such emails, photos, audio files, personal videos, website content, social media, and more.

New, machine learning AI addresses the problems associated with ESI-centered document review, helping law firms rapidly filter through large quantities of media data, and providing early case insights that are vital to narrowing the scope of a case.

Unstructured Data

In the digital world, not all data is created equal. When it comes to ESI, content falls into two categories: structured and unstructured.

Structured data exists within the confines of an already established database (for example, Excel). This material is fairly simple to search and categorize, since it already has a built-in support system.

Unstructured data, on the other hand, lacks an internal skeletal structure, making it more difficult to organize. Unfortunately for attorneys, however, it also happens to make up the bulk of most eDiscovery projects (think: emails, text messages, office memos, videos, photos, etc.).

Luckily, AI programs like Veritone Illuminate now allow attorneys to give structure to the chaos of unstructured data, outfitting them with the right tools to tackle the growing onslaught unstructured media evidence in the modern era.

Technology Assisted Review

One tool that AI brings to eDiscovery, is Technology Assisted Review (also known as “TAR”). In TAR, a human coder uses test documents to “teach” AI software how to recognize and label documents.

Unfortunately, early TAR models were too sensitive to the varying subconscious perceptions of their human coders, whose differing opinions would inevitably end up impacting the direction of the TAR’s self-learning algorithms, producing frustrating results.

With improved designs and more sophisticated calculations, modern TAR software is better equipped to handle the minute differences in human perspective, resulting in a more accurate review experience, overall.

Transcribe and Translate

Another way AI is revolutionizing the legal industry is through its ability to both transcribe and translate audio, video, and text documents, without the need of a specialized workforce.

In the past, it was a challenge to find individuals who had the necessary skill sets for these tasks—especially for foreign language projects, primarily because it wasn’t just about finding someone with the right language proficiency. Indeed, when hiring outside help, law firms are also required to hire translators who are licensed, ABA attorneys in good standing.

Needless to say, the list of Finnish language experts who are also ABA accredited attorneys is a short one.

With AI’s ability to transcribe and translate, firms no longer have to stress about finding a team of lawyers who meet a review’s niche requirements. Instead, they only need to find a few qualified individuals to oversee the process.

Early Case Assessment

Early case insights are vital to legal teams, who are trying to narrow the focus of a lawsuit’s direction. However, finding these early patterns is easier said than done.

Focus is derived from evidence—the kind gleamed from document review. But document review can’t produce evidence without first having focused search parameters.

This creates a frustrating, chicken-before-the-egg conundrum, with both contract attorneys and law firms unable to work at full capacity, until the other produces the information they need. However, with AI technology on board, there no longer needs to be a conundrum.

AI’s early assessment tools can help law firms find their direction—and document reviewers, their footing—at the same time, through finding patterns, organizing data, and cross-referencing contract analytics with case outcomes. This enables each side to operate faster and more independently from the other, settling the chicken argument once and for all:

Because why have one when you can have ‘em both?

Text and PII Redaction

Protecting confidential information is one of the biggest concerns with large-scale e-discovery and evidence gathering processes. Redaction, however, can be time consuming and feel like busy work, which often increases the likelihood of error.

AI has a solution for this, as well.

Not only can AI algorithms find and redact personal identifying information (PII) from text documents, but modern legal technology also gives attorneys the power to remove this information from photos, videos, and audio files, too.

These functions provide better safeguards for client privacy, and also make it easier for judicial agencies to comply with public transparency, when needed.

Image Classification

The same machine learning abilities that help redact sensitive PII can help firms with more than just removal. New artificial intelligence software can actually classify this data, as well.

Using trace markers, algorithms can detect, find, and catalog anything from a face in a crowd to a license plate on a busy street, streamlining the organization of unstructured media exponentially.

Image classification makes it easier to identify unknown faces, track down clues, and connect patterns. It also allows legal professionals to easily rereview material whenever they want, without having to re-track down the information. Adding yet another arrow to the multifunctional quiver of AI legal software.


Considering all the ways artificial intelligence is already transforming the field of law, we don’t have to wonder what the future of legal AI looks like. Indeed, as some have already pointed out, when it comes to AI, the future is here.

Then again, if scientific discovery has taught us anything, it’s that there’s always room for a little more evolution.

Exactly what these future improvements will look like, though, is another matter. But what we do know, is that their success will likely depend on both how receptive law firms are, and how easily science can rectify the concerns and risks associated with forthcoming discoveries.

Law Firm Response

While the stereotype about old-time practitioners of law being resistant to change contains a grain of truth, even old-timers aren’t immune to the tireless march of progress.

Not so long ago, the computer was facing the same, guarded response as AI software is today. And yet, while those boxy apparatuses might have once seemed excessive to practicing professionals, no respectable attorney would try and operate without at least a desktop today (if not a laptop, too). Indeed, it seems unfathomable—even, dare we say, “negligent”? —for an attorney to freehand notes, when computers are such an established part of everyday business.

Legal professionals are bound by more than just trends, though. ABA licensed attorneys—regardless of age—each have a “duty of competence” to their clients. This ethical obligation requires attorneys to provide the best representation possible, which includes—by specific reference—the duty to stay abreast of the pros and cons of emerging new legal technologies.

With this in mind, it seems likely that AI technology is on the same story arc as its predecessor, the computer, even for the rusty curmudgeon.

Still, an important part of a product’s full immersion into society, is to acknowledge and respond to concerns and risks that arise with each new development.

Responding to Risks and Concerns of AI in Legal

Despite hyped up movie plots, I-Robot technology simply does not exist.

As beneficial as AI is, most functions are still quite basic when compared to the overall complexity of the human brain. Hence, there’s no need to fret about humankind’s future (à la Terminator) … at least not yet, anyway. However, that doesn’t mean there aren’t other risks that shouldn’t be considered.

In recent years, critics of artificial intelligence have raised serious concerns about the ethical use of such technology, the future job security of legal professionals, and even questions about liability in the face of so much machine-filtered information.

Where ethics are concerned, courts as far back as 2012 have already approved the use of AI in the legal sector. As for liability, firms are always responsible for the integrity of their own practices—regardless of what software, internet browser, or cell phone tower they’re using. That leaves the question of job security.

It’s natural for people to be concerned about employment—especially considering how fast technological advances can render a service obsolete. Still, while AI certainly makes some legal practices look laughably archaic, an obsolete service doesn’t necessarily compute to an obsolete employee.

The purpose of AI legal software is to enable legal professionals the freedom to focus their brain power on quality, high-level tasks, instead of mired in repetitive grunt work. Hence, AI’s impact on employment will mainly result in shifting job titles, rather than the elimination of them.

In the end, AI is human driven. It needs the creative, cognitive input from the human brain in order to thrive, and can never reach its full potential without it.


As AI technology continues to evolve, there are—no doubt—more unforeseen risks ahead. However, considering that AI already has a firm toehold in the industry, it’s no longer a question of whether or not this technology should be used. Instead, legal professionals would be better off using concerns as a guide, to help them do what they’ve always done in the face of past technological advances:

Shape a better future for AI, and the attorneys who use it.

Daniel Wong on Email
Daniel Wong
Marketing Director at Veritone, Inc.
Daniel Wong is currently the Marketing Director for Veritone, Inc., (NASDAQ: VERI) – a leader in enterprise artificial intelligence (AI) solutions for commercial and regulated industries such as Media & Entertainment, Energy, Government, Legal, Compliance, just to name a few. With more than 25+ years of hardware and software product management and product marketing experience in the technology sector, Daniel has been fortunate enough to part of the explosion of bleeding edge technologies such wireless networking, the Internet of Things, and now artificial intelligence.

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