Text IQ Blog

This blog post is part one of “Innovative Legal Leaders” - an ongoing series spotlighting top legal minds from various industries (F500, non-profits, F100 law firms).

“Machines should be able to sift through the noise, help us overcome our biases…not [provide] shallow predictions,” says David Ferrucci (Machine Learning vs Machine Understanding, 2020).  Ferrucci—the IBM Watson team founder made famous for besting the Jeopardy! champions in 2011—goes on to point out that another serious limitation to traditional machine learning (ML) approaches is that they provide their right or wrong results without explanation.

Regulations surrounding healthcare data privacy are constantly changing. Due to the invention of new technology, the emergence of the COVID-19 pandemic, and other privacy complications, it’s more important than ever that companies handling protected health information (PHI) do their due diligence and ensure they comply with ever-changing regulations.

Are you aware of the dangers lurking in your documents? A missed privileged document could spell the end of your chances at trial, and failing to redact all the necessary personal information in your files could lead to heavy fines or a lawsuit. Hidden deep in your documents could be evidence that your colleagues are committing fraud!

Artificial intelligence (AI) is transforming nearly every industry. As AI becomes more widespread, you may be wondering how to gauge its effectiveness. AI is often used for pattern recognition, information retrieval, and classification. There are two metrics that are key for evaluating the performance of AI in this context: precision and recall.

Industries across the economy are adopting artificial intelligence, and for general counsel (GC) this means staying ahead of the curve or risk getting left behind. We’ve seen explosive growth in the AI market, both in investment and technological progress.  While this brings a host of challenges—from data privacy compliance to optimizing integration—AI systems pull their weight for organizations that are sitting on otherwise unmanageable volumes of data.

What if you, as the Chief Legal Counsel (CLC) of a multinational enterprise, inadvertently produced 420 privileged documents during a high-stakes litigation? 

It is no secret that the healthcare industry as a whole is facing greater and greater scrutiny each year, and the industry is growing more litigious. Pharmaceutical companies in particular face patent litigation, antitrust litigation, class actions, multidistrict litigation, and False Claim Act litigation. 

The Federal Rules of Evidence were adopted by the Supreme Court on Nov. 20, 1972 and became effective on July 1, 1973. Since then there have been many changes and modifications to make privilege what it is today.

Document review, as it relates litigation and legal proceedings, is the process where each party to the proceeding reviews, sorts, and analyzes all documents, data, and electronic information in their possession to determine which materials may be relevant to the proceeding and what may be withheld from production. This process is the cornerstone of most discovery and ediscovery actions.

We're taking you back to basics with an in-depth look at the privilege review process, including how to conduct a privilege review and how to reduce your discovery expenses.  

Text IQ is excited to launch our new ebook, “A Guide for Antitrust Counsel: Transforming Second Request Compliance With AI,” we explain how to comply with regulator requests while saving countless hours and dollars, and significantly reducing risk (download now).

Nothing will cause a group of young associate attorneys to groan quite like a privilege log. For most, privilege logs are deemed a necessary evil during litigation prep. However, our list of best practices will help you optimize your privilege log preparations and make your next privilege log experience painless.

I was in Portland last month at PREX 2019 to host a panel titled: “Tech Spotlight: The Case for AI in a Privacy-Conscious World.” One topic that came up in the discussion was the impact that AI adoption will have on the law firm business model. My musings and coverage are below.

Though Artificial Intelligence (AI) is already altering the way lawyers think, the way they conduct business, and the way they manage their clients, the legal profession still largely relies on paralegals, legal assistants, and interns to manually research and process information.

Rule 23 of the Federal Rules of Civil Procedure and its state analogues, which govern class action lawsuits in the United States, may be the most important laws in modern litigation.  In an era when most civil suits settle, class actions dominate the settlement landscape. Given the trend towards higher settlement values, recent Supreme Court opinions that have been interpreted as anti-class-plaintiff are turning out to challenge class action defendants. In this article, we examine these recent rulings, trends, and challenges in class action litigation settlements.

At Text IQ, we developed our solution because we found many stages in the privilege review process where current methods were inefficient and inherently risky. These stages represent choke points that our technology—AI for Sensitive Information—can overcome.

Text IQ has applied artificial intelligence to privilege review, a process that is historically risky, inefficient, and costly. The diagram below demonstrates the literal transmutation of privilege review with Text IQ.

Short for Regular Expression, Regex is a sequence of text programming that is used to generate and recognize patterns to identify, define, and manage text. 

Hiring outside reviewers, or contract attorneys, to perform document review is a well-known practice in the legal field. Document review requires a lot of work - often thousands of attorney hours, and contract attorneys can be a cost-effective solution. However, negative outcomes, attorney experiences, and even legislation show that relying solely on manual review may not be the best option for document review. 

Part Two of a Three-Part Series where we examine the evolving challenges of second requests, and the promise of AI to help. Our last post addressed the logistical challenges for antitrust counsel facing a second request review. This post will explore competing demands of growing scrutiny and growing risk.

Part I of a series where we examine what you’re up against, and follow up with the promise of AI to help. 

Amid the high-stakes and often high-stress negotiations that accompany corporate mergers and acquisitions, a government-mandated “Second Request” poses another formidable hurdle for a company and its antitrust counsel to clear.

Part 1 of a series about the role of AI in a world that’s leaving TAR behind.

Jocelyn Hunter, Vice President and Deputy General Counsel

Jocelyn Hunter knows a thing or two about more saving and more doing. After twenty years at Home Depot, Hunter now serves as the Vice President and Deputy General Counsel for the company, where she works on employment litigation, international work, legal issues relating to the company’s

Meet Aaron Crews, Head of eDiscovery at Walmart. In his tenure at the behemoth and beyond, he’s seen the evolution of eDiscovery operations as both in-house and outside counsel. Crews understands firsthand the gravity of building strategies for a massive litigation profile that are repeatable, defensible, transparent, and cost-efficient. At Text IQ, we’re building solutions