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.

There is an increasing interest in the entwining of the field of antitrust with the field of Artificial Intelligence (AI), frequently referred to jointly as Antitrust and AI (AAI) in the research literature. This study focuses on the synergies entangling antitrust and AI, doing so to extend the literature by proffering the primary ways that these two fields intersect, consisting of: (1) the application of antitrust to AI, and (2) the application of AI to antitrust. To date, most of the existing research on this intermixing has concentrated on the former, namely the application of antitrust to AI, entailing how the marketplace will be altered by the advent of AI and the potential for adverse antitrust behaviors arising accordingly. Opting to explore more deeply the other side of this coin, this research closely examines the application of AI to antitrust and establishes an antitrust vigilance lifecycle to which AI is predicted to be substantively infused for purposes of enabling and bolstering antitrust detection, enforcement, and post-enforcement monitoring. Furthermore, a gradual and incremental injection of AI into antitrust vigilance is anticipated to occur as significant advances emerge amidst the Levels of Autonomy (LoA) for AI Legal Reasoning (AILR).

An expanding field of substantive interest for the theory of the law and the practice-of-law entails Legal Sentiment Analysis and Opinion Mining (LSAOM), consisting of two often intertwined phenomena and actions underlying legal discussions and narratives: (1) Sentiment Analysis (SA) for the detection of expressed or implied sentiment about a legal matter within the context of a legal milieu, and (2) Opinion Mining (OM) for the identification and illumination of explicit or implicit opinion accompaniments immersed within legal discourse. Efforts to undertake LSAOM have historically been performed by human hand and cognition, and only thinly aided in more recent times by the use of computer-based approaches. Advances in Artificial Intelligence (AI) involving especially Natural Language Processing (NLP) and Machine Learning (ML) are increasingly bolstering how automation can systematically perform either or both of Sentiment Analysis and Opinion Mining, all of which is being inexorably carried over into engagement within a legal context for improving LSAOM capabilities. This research paper examines the evolving infusion of AI into Legal Sentiment Analysis and Opinion Mining and proposes an alignment with the Levels of Autonomy (LoA) of AI Legal Reasoning (AILR), plus provides additional insights regarding AI LSAOM in its mechanizations and potential impact to the study of law and the practicing of law.

Legal Judgment Prediction (LJP) is a longstanding and open topic in the theory and practice-of-law. Predicting the nature and outcomes of judicial matters is abundantly warranted, keenly sought, and vigorously pursued by those within the legal industry and also by society as a whole. The tenuous act of generating judicially laden predictions has been limited in utility and exactitude, requiring further advancement. Various methods and techniques to predict legal cases and judicial actions have emerged over time, especially arising via the advent of computer-based modeling. There has been a wide range of approaches attempted, including simple calculative methods to highly sophisticated and complex statistical models. Artificial Intelligence (AI) based approaches have also been increasingly utilized. In this paper, a review of the literature encompassing Legal Judgment Prediction is undertaken, along with innovatively proposing that the advent of AI Legal Reasoning (AILR) will have a pronounced impact on how LJP is performed and its predictive accuracy. Legal Judgment Prediction is particularly examined using the Levels of Autonomy (LoA) of AI Legal Reasoning, plus, other considerations are explored including LJP probabilistic tendencies, biases handling, actor predictors, transparency, judicial reliance, legal case outcomes, and other crucial elements entailing the overarching legal judicial milieu.

Legal scholars have postulated that there have been three eras of American law to-date, consisting in chronological order of the initial Age of Discovery, the Age of Faith, and then the Age of Anxiety. An open question that has received erudite attention in legal studies is what the next era, the fourth era, might consist of, and for which various proposals exist including examples such as the Age of Consent, the Age of Information, etc. There is no consensus in the literature as yet on what the fourth era is, and nor whether the fourth era has already begun or will instead emerge in the future. This paper examines the potential era-elucidating impacts amid the advent of autonomous Artificial Intelligence Legal Reasoning (AILR), entailing whether such AILR will be an element of a fourth era or a driver of a fourth, fifth, or perhaps the sixth era of American law. Also, a set of meta-characteristics about the means of identifying a legal era changeover are introduced, along with an innovative discussion of the role entailing legal formalism versus legal realism in the emergence of the American law eras.

Legal argumentation is a vital cornerstone of justice, underpinning an adversarial form of law, and extensive research has attempted to augment or undertake legal argumentation via the use of computer-based automation including Artificial Intelligence (AI). AI advances in Natural Language Processing (NLP) and Machine Learning (ML) have especially furthered the capabilities of leveraging AI for aiding legal professionals, doing so in ways that are modeled here as CARE, namely Crafting, Assessing, Refining, and Engaging in legal argumentation. In addition to AI-enabled legal argumentation serving to augment human-based lawyering, an aspirational goal of this multi-disciplinary field consists of ultimately achieving autonomously effected human-equivalent legal argumentation. As such, an innovative meta-approach is proposed to apply the Levels of Autonomy (LoA) of AI Legal Reasoning (AILR) to the maturation of AI and Legal Argumentation (AILA), proffering a new means of gauging progress in this ever-evolving and rigorously sought domain.

This paper examines and extends the legal microdirectives Recent research by legal scholars suggests that the law theories in three crucial respects: might inevitably be transformed into legal microdirectives consisting of legal rules that are derived (1) By indicating that legal micro-directives are from legal standards or that are otherwise produced likely to be AIenabled and evolve over time in automatically or via the consequent derivations of scope and velocity across the autonomous levels of legal goals and then propagated via automation for AI Legal Reasoning [20] [22], everyday use as readily accessible lawful directives throughout society. This paper examines and extends (2) By exploring the tradeoffs between legal the legal micro-directives theories in three crucial standards and legal rules as the imprinters of the respects: (1) By indicating that legal micro-directives micro-directives, and are likely to be AIenabled and evolve over time in scope and velocity across the autonomous levels of AI (3) By illuminating a set of brittleness exposures Legal Reasoning, (2) By exploring the tradeoffs that can undermine legal micro-directives and between legal standards and legal rules as the proffering potential mitigating remedies to seek imprinters of the micro-directives, and (3) By greater robustness in the instantiation and illuminating a set of brittleness exposures that can promulgation of such AIenabled lawful directives.

Advances in Artificial Intelligence (AI) and Machine Learning (ML) that are being applied to legal efforts have raised controversial questions about the existent restrictions imposed on the practice-of-law. Generally, the legal field has sought to define Authorized Practices of Law (APL) versus Unauthorized Practices of Law (UPL), though the boundaries are at times amorphous and some contend capricious and self-serving, rather than being devised holistically for the benefit of society all told. A missing ingredient in these arguments is the realization that impending legal profession disruptions due to AI can be more robustly discerned by examining the matter through the lens of a framework utilizing the autonomous levels of AI Legal Reasoning (AILR). This paper explores a newly derived instrumental grid depicting the key characteristics underlying APL and UPL as they apply to the AILR autonomous levels and offers key insights for the furtherance of these crucial practice-of-law debates.

Efforts furthering the advancement of Artificial Intelligence (AI) will increasingly encompass AI Legal Reasoning (AILR) as a crucial element in the practice of law. It is argued in this research paper that the infusion of AI into existing and future legal activities and the judicial structure needs to be undertaken by mindfully observing an alignment with the core principles of justice. As such, the adoption of AI has a profound twofold possibility of either usurping the principles of justice, doing so in a Dystopian manner, and yet also capable to bolster the principles of justice, doing so in a Utopian way. By examining the principles of justice across the Levels of Autonomy (LoA) of AI Legal Reasoning, the case is made that there is an ongoing tension underlying the efforts to develop and deploy AI that can demonstrably determine the impacts and sway upon each core principle of justice and the collective set.

Legal scholars have in the last several years embarked upon an ongoing discussion and debate over a potential Legal Singularity that might someday occur, involving a variant or law-domain offshoot leveraged from the Artificial Intelligence (AI) realm amid its many decades of deliberations about an overarching and generalized technological singularity (referred to classically as The Singularity). This paper examines the postulated Legal Singularity and proffers that such AI and Law cogitations can be enriched by these three facets addressed herein: (1) dovetail additionally salient considerations of The Singularity into the Legal Singularity, (2) make use of an in-depth and innovative multidimensional parametric analysis of the Legal Singularity as posited in this paper, and (3) align and unify the Legal Singularity with the Levels of Autonomy (LoA) associated with AI Legal Reasoning (AILR) as propounded in this paper.