This "blue sky idea" paper outlines the opportunities and challenges in data mining and machine learning involving making a computational attorney -- an intelligent software agent capable of helping human lawyers with a wide range of complex high-level legal tasks such as drafting legal briefs for the prosecution or defense in court. In particular, we discuss what a ChatGPT-like Large Legal Language Model (L$^3$M) can and cannot do today, which will inspire researchers with promising short-term and long-term research objectives.

There has been legal documentation through technological systems, but it goes beyond exploring technology for transmitting and storing legal proceedings to creating a robot lawyer. Pondering what a robot lawyer does? A robot lawyer can advocate like a trained, and experienced lawyer would do. A robot lawyer can "fight corporations, beat bureaucracy, and sue anyone at the press of a button", says Joshua Browder, DoNotPay founder. DoNotPay is a manufacturing company aimed at making legal information and self-help services available to everyone through the use of technology.

A legal services company says it's willing to pay $1 million to fuck around and find out. On Sunday, DoNotPay CEO Joshua Browder made a wild proposition to any lawyer slated to argue an upcoming case in front of the U.S. Supreme Court. Let DoNotPay's AI lawyer, which is built on OpenAI's viral GPT-3 API, argue the case before the court, Browder said, in exchange for $1 million. All the human lawyer would need to do is wear AirPods and repeat to the court what DoNotPay's robot lawyer argues. "DoNotPay will pay any lawyer or person $1,000,000 with an upcoming case in front of the United States Supreme Court to wear AirPods and let our robot lawyer argue the case by repeating exactly what it says," Browder wrote on Twitter on Sunday night.

AI and the law is a vital upcoming profitable opportunity for lawyers, law firms, and law students. The gauntlet had been thrown. You see, I was the invited keynote speaker at a major legal industry conference and my heralded topic was squarely in my wheelhouse, namely Artificial Intelligence (AI) and the law (typically coined as AI & Law). Rather than being entirely heralded, maybe the more apt phrasing is to say that the topic was met with a mixture of excitement by some and outright eyebrow-raising skepticism by others. The assembled collection of several hundred law firm partners and associates murmured and questioned subtly whether anything about AI and the law especially needed to be known by them. AI was generally perceived as a pie-in-the-sky topic. On top of that contention, AI when combined with the law was equally or even further at the outreaches of what daily hard-working nose-to-the-grind lawyers would seem to be thinking about. I'm pleased to say that my remarks were well-taken and the response was quite positive, including that this was the first time many of them had ever heard a no-nonsense compelling and comprehensive case made for why lawyers ought to know about AI and the law. The discussion got those top-notch legal-minded gears going and the attendees had plenty to ruminate on. Let's see if the same can be said for those of you that might be interested or at least intrigued by the AI & Law topic. First, a vital facet to know is that AI & Law consists of two intertwined conceptions. I want to emphatically make clear-cut that these are both bona fide and rapidly expanding ways in which AI and the law are being combined. Many attorneys are only familiar with one or the other of the two perspectives, or oftentimes not familiar with either of the two. Depending upon your lawyering preferences, it is perfectly fine to concentrate on one of the two and not particularly focus on the other. By and large, lawyers that seem less inclined toward having an interest in technology are bound to keep their eye on the law as applied to AI, wherein you don't necessarily need to get your hands into the tech per se. Those lawyers that seem to relish the high-tech infusion into the legal realm are more apt to gravitate toward the realm of AI as applied to the law. You are welcome to embrace both aspects and do so with your head held high. I'll first herein do some meaty unpacking on the law as applied to AI. When referring to the law as applied to AI, you should immediately be thinking about the emerging litany of new laws seeking to govern the advent of AI systems. Laws are springing up like wildfire. International laws are coming forth about AI & Law, federal laws too, state laws also, and local laws aplenty, see my ongoing coverage at the link here and the link here, just to name a few.

If you're in trouble, would you rather call your lawyer or his AI sidekick? The right answer is not as obvious as one might think. Law is all-encompassing, especially in the business world. Whether we realize it or not, business takes place in the shadow of the law. Law is still, however, one of those fields primarily conducted by humans.

AI robot lawyers are here--and they aren't going away. When you hear the phrase "robot lawyer," what comes to mind? My brain conjures up an image of C-3PO in a three-piece suit, shuffling around a courtroom, while throwing out cross-examination quips such as: "Don't call me a mindless philosopher, you overweight glob of prosecuting witness grease!" Artificial intelligence (AI) is, in fact, becoming a mainstay component of the legal profession. In some circumstances, this analytics-crunching technology is using algorithms and machine learning to do work that was previously done by entry-level lawyers.

AI robot lawyers are here--and they aren't going away. When you hear the phrase "robot lawyer," what comes to mind? My brain conjures up an image of C-3PO in a three-piece suit, shuffling around a courtroom, while throwing out cross-examination quips such as: "Don't call me a mindless philosopher, you overweight glob of prosecuting witness grease!" Artificial intelligence (AI) is, in fact, becoming a mainstay component of the legal profession. In some circumstances, this analytics-crunching technology is using algorithms and machine learning to do work that was previously done by entry-level lawyers.

In May 1997, in a high-profile chess match held under tournament conditions, the reigning world champion, Garry Kasparov, took on Deep Blue, an IBM-developed computer, and lost. It was the first time that an artificial intelligence (AI) had defeated a world champion. The result received much coverage at the time and represented a triumph of late 20th century technology. The question of whether the practice of law exhibits an equivalent level of tactical dexterity to that of a chess match is not one to be answered here, and certainly not by a practising lawyer. But advances in AI, across many facets of life since the turn of the century, are undeniable.

Let's expand this question asked by Alan Turing in the 50s. The countless disaster scenarios, in which artificial intelligence (AI) takes over the world and destroys humanity, are already made-up and still being told in Hollywood. AI has not yet taken control of humanity, but it has indeed taken control of many aspects of our lives even if we do not perceive it as such. We accept AI as a part of our lives. The simplest example is our smartphones!

This article is the second part (click here for part one) in our series about the role of AI in customer support. The explores how digitization, digital self-service, and distributed digital advisors are disrupting a series of industries and creating a series of business opportunities to realize transformative value propositions, business models, services, and new revenue streams. The second-part delves further into the impact of AIOps and machine automation on a range of different careers and considers how we can prepare further for the occupational changes of the future. Many of the critical building blocks of computing -- microchip density, processing speed, storage capacity, energy efficiency, download speed, etc. -- have been improving at exponential rates over the last decade According to the authors of The Second Machine Age, Erik Brynjolfsson and Andrew McAfee: "We've also recently seen great progress in natural language processing, machine learning (the ability of a computer to automatically refine its methods and improve its results as it gets more data), computer vision, simultaneous localization and mapping, and many of the other fundamental challenges of the discipline." Administration tasks have evolved to largely self-service over the last few decades with technology removing the need for typing pools, copyists, and mailroom clerks.