Technologies that may be able to automate typical legal tasks, such as performing case searches or creating standard contracts, have been around for some time but are not have not yet been fully integrated into practice. However, over the last decade or so, pressure has increased on lawyers and law firms to reduce fees and this has led to a more favorable attitude towards legal technologies in an attempt to increase efficiency across the profession. Second, the pressure to improve access to justice by reducing financial and structural barriers affecting disadvantaged groups has led to the development of several legal technologies that are online or otherwise accessible. Third, as the capabilities of computers grow to include higher-level processes, the possibilities for their integration into the legal field also grow. While previous legal technologies mostly threatened to replace office work, AI could threaten to replace lawyers themselves. To gain a complete understanding of this topic, it is necessary to explore the current state of artificial intelligence in the legal profession, how it impacts the demand for lawyer jobs, and how the profession's regulatory structures relate to the trajectory of legal technology. to plagiarism. Get a tailor-made essay on "Why Violent Video Games Shouldn't Be Banned"? Get an Original Essay The term “artificial intelligence” describes how computers can perform tasks that are generally thought to require some level of human intelligence. These tasks can range from reporting outliers in a dataset to transcribing an audio tape and everything in between. Basically, computers work according to a defined set of rules. Any task performed by computers must be able to be articulated as a set of basic rules to follow. Deductive rules are those established in a step-by-step process that is followed by the computer until the task is completed. An example of this applied to automated legal work is the use of automated document assembly, such as creating a template for a will or other standard legal document. In seconds, a document assembly application can extract relevant information about a customer and use it to create a personalized document. Similarly, a computer might provide a list of cases from a particular court that cite a particular statute. In addition to such tasks whose processes can be modeled explicitly, some other tasks can be performed with the use of data-driven rules. The relationship between a set of input variables and the resulting outputs can be estimated by a process called “supervised machine learning,” so called because the estimation is limited by the training data set. For example, a team of researchers managed to develop a model to predict the behavior of the Supreme Court, based only on data from past decisions. They were able to achieve a prediction accuracy of 70.2% at the case outcome level and a prediction accuracy of 71.9% at the justice vote level. Although these predictions cannot be expressed based on a combination of deductive rules as in the previous examples, with enough input data it is possible to recognize a relatively consistent pattern. Similarly, automated document review software has been developed that has proven effective in determining the relevance of documents based on input from a “setinitial” of documents designated as relevant or not. In addition to potentially being able to replace or improve the efficiency of routine legal tasks, predictive algorithms such as these have possible applications to the legal field as a whole. For example, the results of an algorithm of race-neutral sentence predictions could be compared to actual sentences to determine the influence of human biases in such processes. Overall, the success of data-driven algorithms is significant primarily because it highlights the routineness of some activities that would otherwise be considered more sophisticated and complex.complex. The adoption of technology in the legal workplace will be influenced by the market as well as the quality and capabilities of available technologies. Historically, the demand for technology in law firms has been low for several reasons to billable hours economically encouraged inefficiency, while the typical partnership structure stipulated that funds for new technologies would come directly from the partners' pockets, unlike a traditional corporate structure where the money would come from shareholders. Regarding the first point, in recent years there has been a notable shift in the supply of lawyers relative to the demand for forensic work. This leads to increasing pressure to improve efficiency and reduce costs for customers. Additionally, an increase in the share of legal work performed by a company's internal legal department compared to that performed by external law firms allows these technologies to be purchased with company funds, which is more favorable. In addition to the growing demand for legal technologies, the capabilities of those technologies are also expanding rapidly. The theory of disruptive innovation explains how this will also contribute to the growing prevalence of legal technology. When the only legal tasks that could be automated were clerical and other low-level services, law firms were willing to purchase such software to improve efficiency and better serve their clients. However, developers have since been able to expand their technologies to handle more complex tasks, and companies are now virtually forced to adopt them as customer pressures grow. This phenomenon, in addition to the growing market interest, will lead to a rapid adoption of technology in the legal sector. As the use of technology in the legal profession increases, the impact of artificial intelligence on the demand for lawyer jobs in some areas has been reduced. or will be relatively significant, while in others it is unlikely to pose a significant threat. The distinction between tasks that can be easily automated and those that cannot be easily automated lies in the extent to which their underlying structures can be defined. For example, while document drafting can be successfully automated as discussed above, more complex legal writing that characterizes the state of the law or its application to particular factual circumstances presents a much more challenging situation. The conceptual creativity and flexibility required by this type of writing cannot be defined by either deductive or data-driven rules. Another example is the distinction between document review during the discovery phase and document review during due diligence. While the former can be automated with the use of explicit rules, the latter requires critical judgments that a computer cannot make. An experienced lawyer can notice, for example, any unexpected information or violation of appropriate rules that a computer would not be able to recognize without beingexplicitly prepared to look for such things. Some advanced applications of AI to the legal profession have found ways to extend its reach despite these limitations. For example, IBM's Debater System can analyze documents and other materials first annotated by humans. While this is clearly less efficient than purely automated processes as it requires time on the part of an associate, it alleviates some of the major issues with automated lawyering; any obvious contradictions or relevant subtleties can be highlighted before the materials are analyzed by the software. Another way AI can be used to perform tasks for which a lawyer is qualified is through online systems to resolve minor disputes ranging from parking violations to e-commerce complaints. These technologies help lawyers in negotiations by analyzing the overlap between the two parties' stated preferences and can typically reach a mutual solution without the involvement of a lawyer. While such systems may therefore be able to replace lawyers and even judges, they will likely have minimal impact on the overall labor demand for lawyers since it would probably not be feasible, either economically or otherwise, to hire a lawyer and start a cause. In this way, the complete automation of legal services does not involve any cost for the work of lawyers. In fact, a study that ranked legal tasks by automation's impact on employment found that only about 4% of lawyers' time was spent on tasks most threatened by AI. In summary, although even moderately complex legal tasks have been successfully automated, the legal profession is unlikely to find itself obsolete within a decade as some headlines predict. As new technologies continue to develop and make their way into legal practice, a need emerges for a better way to protect the integrity of the legal system while ensuring consumer protection and access to quality services for all members of the legal system. population. As far as consumer protection is concerned, computers offer the advantage of eliminating human error and standardizing services in some, but certainly not all, cases. For example, online services cannot effectively analyze highly complex scenarios, but instead of returning an error message they often return completed products in order to hold the customer accountable. While consumer protection concerns are not necessarily more severe with automated legal services, they deserve at least as much attention as legal services provided by human lawyers. Current professionalism guidelines limit the provision of legal services to those who are trained and licensed to practice law, and the stated reason for this is to "protect the public from the consequences of receiving legal services from unqualified persons". These rules are then implemented through disciplinary sanctions imposed by the forensic commissions. However, these guidelines present several weaknesses regarding the regulation of new technologies in the legal field. They fail to specifically outline which tasks require the expertise of a licensed professional, making them useless in governing which tasks can be left to automated providers. Furthermore, while computers may not be competent enough to perform some tasks normally handled by lawyers, they may be competent enough to assist.