CHANGING LANDSCAPE OF LEGAL PROFESSION HOW TO LEGAL TECH, BIG DATA ARE SHAPING THE FUTURE OF LAWYERS

ABSTRACT

Preserving human discretion while using automated insights in this article, we are going to talk about “Changing Landscape of the Legal Profession, How Legal Tech, Big Data are Shaping the Future of Lawyers”. We will discuss how the legal profession is evolving over time, how big data and legal technology are being integrated, and how these developments are automating repetitive tasks, improving the capacity for legal research, and freeing up resources to concentrate on more strategic and client-centric work by generating insights through data analysis, how ultimately transforming the role of lawyers. First, we will go over what big data and legal technology are, how they will change the practice of law, and their respective meanings. Along with how these technologies will impact the function of the lawyer. Analysing, interpreting, and applying insights from big data sets is the essence of data literacy. Collaboration with tech teams and IT sectors experts optimising new technologies.

In addition, we will examine the main issues that are becoming more and more pertinent in our ever-changing transition to a greater and greater use of technology, including issues like ethical implications and considerations like cost, accessibility, training, and education.

KEYWORDS

Legal Technology, Big Data, Legal profession, Lawyer, Data Literacy, AI, IT sectors, Ethical Implications.

INTRODUCTION

The use of software and technology to assist the legal sector and offer legal services is referred to as legal technology, or “Legal Tech[1]“. Traditionally conservative legal markets are the target of disruption for many entrepreneurs, including legal IT businesses.[2] For legal duties, several methodologies and technology have been employed. For objectives like granting access to case law, conventional software architecture and web technologies have been utilised. Finding papers for due diligence or discovery has been made easier with the use of machine learning techniques. Work using elements of user experience design is done to make contracts easier to use.

The term “legal technology” originally described the use of hardware and software to support practice management, document automation, document storage, billing, accounting, and electronic discovery for solo practitioners, law firms, medium-sized corporations, and big businesses. Since 2011, the term “legal tech” has changed to more accurately describe how tech startups are upending the legal profession by providing people with access to online tools that lessen or sometimes completely do away with the need to consult an attorney, or by facilitating more effective connections between clients and attorneys through online marketplaces and lawyer-matching websites[3].

Technology used to provide legal services and assist the legal sector is known as legal technology. Rather than traditional gear, like as computers, printers, and scanners, which are not exclusive to the legal sector, it usually refers to software.

Most of this technology is often created to facilitate more effective legal practice for lawyers and law firms. Litigation technology, practice management programs, and other legal software systems are a few examples.

Big data is the term used to describe data sets that are too big or complicated for conventional data-processing application software to handle. While data with more features or columns and more complexity may result in a higher false discovery rate, data with numerous entries (rows) give better statistical power[4]. The best interpretation is that it is a vast body of information that cannot be understood when utilised sparingly, even if it is occasionally used unstructured data that constantly overwhelm enterprises loosely owing to a lack of official definition.[5]

The phrase “big data” refers to the massive, difficult-to-manage amounts of organised and unstructured data that constantly overwhelm enterprises. However, what counts is how businesses use the data, not just what kind or volume of data they have. Big data analysis may provide insights that strengthen judgements and inspire confidence when making calculated business decisions.

BACKGROUND

The way the legal profession manages and uses information has changed significantly as a result of developments in legal technology and the emergence of big data. This development may be divided into many phases, each of which denotes a major change in the ways that legal professionals get, evaluate, and use information.

Early legal database history, from the 1970s to the 1990s, saw a revolution in legal research with the advent of digital resources such as Westlaw and Lexis. Legal researchers could now access extensive databases of legislation and case law through computers for the first time, which significantly increased the effectiveness and breadth of their study. Nevertheless, these early systems’ capabilities were constrained, mainly concentrating on keyword searches with minimal data analytics capacity.

The e-discovery revolution occurred in the late 1990s and early 2000s as a result of the widespread use of digital communications. The amount of electronic evidence increased dramatically during this time period, requiring the creation of specialised e-discovery tools that could manage big datasets. The need to swiftly adjust to the difficulties of organising and evaluating massive amounts of digital data forced legal practitioners to make a big change in the way evidence was gathered and examined in court cases.

The practice management industry entered the cloud computing era in the 2000s and 2010s. Cloud-based practice management solutions were adopted by law firms, improving their capacity to gather and handle client data, billable hours, and case specifics. This change not only increased operational effectiveness but also gave businesses better tools for analysing internal data for business intelligence, which opened up fresh perspectives on client interactions and company performance.

The legal profession has entered the era of big data analytics in the 2010s and beyond. During this time, powerful legal analytics systems like Ravel Law and Lex Machina have been developed. With the use of these technologies, lawyers are now able to use data in previously unheard-of ways, such as forecasting case outcomes and developing litigation strategy. Moreover, the use of data-driven insights has broadened to encompass domains including corporate expansion, recruitment procedures, and pricing tactics, radically transforming the way legal companies function and make choices.[6]

This development is in line with the legal profession’s general trend towards data-driven decision-making and the growing incorporation of technology into every facet of legal practice. Big data and analytics will probably play an ever-more-important role in determining legal strategy and operations as legal tech develops.

The most recent development in legal technology is the fusion of AI and machine learning. Due diligence and contract analysis are now being performed with much less time and effort thanks to the use of natural language processing. Predictive coding in e-discovery streamlines and automates document inspection, making it possible to handle massive amounts of data more effectively. Artificial intelligence (AI)-driven legal research instruments are yielding quicker and more thorough outcomes, expanding the scope and profundity of legal analysis accessible to professionals.

In legal practice, data-driven decision-making is becoming more and more important. These days, data analytics is a major tool used by attorneys for risk assessment and case planning. Big data is being used to find similarities in the actions of opposing solicitors and the rulings made by the courts, giving litigants a strategic edge. Settlement talks and trial tactics are being guided by these data-driven insights, enabling more knowledgeable and efficient legal representation.

The emergence of big data and analytics has also changed how services are provided and how clients expect to be served. More openness and data-driven insights are increasingly demands from clients. In response, attorneys are leveraging big data to deliver more realistic budget estimates and timeframes, boosting client satisfaction and project management. The advancement of data visualisation technologies has made it possible for attorneys to explain complicated legal ideas to clients in a way that is more engaging and understandable.

Nonetheless, there are difficulties and moral issues with this technological revolution. The protection of data integrity and privacy has grown in importance as legal practice becomes more digitally orientated. Growing awareness of the need to address potential biases in AI systems and big data analytics is also necessary to make sure that these technologies advance justice and equality rather than thwart them.

Within the field of law, specialisation and skill development have evolved as a result of the shifting terrain of legal technology. Since these abilities are valuable in today’s legal practice, more and more lawyers are pursuing competence in data science and analytics. Legal data scientists and analytics professionals are increasingly employed by law firms, adding fresh knowledge to established legal teams. A greater emphasis on data literacy is now the standard in legal education and professional development, reflecting this change.

In the coming years, a number of new developments are expected to significantly alter the legal profession. It is anticipated that there will be an increase in the use of Internet of Things (IoT) data in court cases, such as the use of data from smart devices as evidence. Predictive policing’s potential and the effects it may have on criminal justice practice are now being investigated. Big data is being used more and more by corporate customers to manage risk and compliance, creating new opportunities for legal services.

The way that solicitors approach their work has fundamentally altered as a result of this revolution, and it is now necessary to acquire skills in huge dataset analysis and use. It has also opened up new doors for anyone who know how to successfully blend data analytic skills with legal knowledge. The legal profession is undergoing significant change in the era of big data, and attorneys will need to be able to handle and analyse large volumes of data, which will change the legal practice environment for years to come.

HOW IT HELPS LAWYER

The IT Industry’s Impact on the Legal Profession

The IT sector has been instrumental in revolutionizing the legal profession by offering instruments, technologies, and support systems that augment the efficiency and competencies of attorneys. This revolution encompasses numerous facets of legal practice, from research and analytics to practice administration and client interactions. Modern databases and search engines, such as Westlaw and LexisNexis, have been created by the IT sector specifically for the purpose of legal research and analytics. Artificial intelligence (AI)-driven research tools that provide quicker, more thorough case law study are a supplement to these platforms. The emergence of predictive analytics technology has also revolutionized the way lawyers approach their cases by providing predictions of case outcomes and strategic preparation. [7]

Cloud-based timekeeping, billing, and case management solutions have greatly simplified practice management. Client portals have improved document sharing and communication, while workflow automation solutions have made tedious chores easier. Because of these developments, legal services are now more open and easily available, which has increased customer satisfaction while also increasing efficiency.

Modern systems that arrange enormous case file collections have revolutionised document administration and analysis. While version control and collaboration capabilities make it easier for several lawyers to prepare documents together, AI-powered contract analysis tools speed up risk assessment and detection. With machine learning and predictive coding speeding up document review procedures, advanced software has become essential in the field of e-discovery for processing and evaluating digital evidence.

The vital requirement for cybersecurity in legal practice has also been addressed by the IT sector. Strong security measures guard confidential client data, secure file transfers and communication are made possible by encryption tools, and data protection best practices are implemented with the aid of assistance and training. In courtrooms, technology has introduced electronic filing systems, video conferencing tools for remote depositions and hearings, and presentation software for creating compelling visual aids.

Specialized CRM software geared on client management and business development has improved client relationship management. In order to provide more effective and personalised client service, data analytics are used to find trends in the demands and preferences of the clientele.

Particularly revolutionary has been the incorporation of AI and machine learning into the legal profession. Legal research and contract reviews are now conducted using natural language processing; chatbots help with initial client intake and basic legal questions; and resource allocation and case strategy formulation are aided by predictive models.

The scope of these advancements has been further expanded by mobile technology, which offers secure mobile applications that provide access to case information while on the move. Additionally, mobile time-tracking and invoicing apps guarantee improved billing accuracy for clients.

The IT sector never stops innovating, creating fresh approaches to satisfy the changing demands of the legal profession. Due to the merging of IT and law, legal technology has emerged as a separate and quickly expanding industry that helps lawyers work more productively, make data-driven choices, and provide their clients better service.

ETHICAL IMPLICATIONS OF AI ON RESEARCH

Concerns over correct attribution in research and academic integrity have been highlighted by AI language models such as ChatGPT. These models can produce coherent and presumably unique content on a variety of themes since they have been trained on enormous volumes of text data, including scholarly literature. However, because researchers can be enticed to utilise AI-generated content without proper attribution or acknowledgment, this capacity raises ethical concerns. Unintentional plagiarism might result from this approach as the AI’s output can mimic previously published works without obvious citations. Furthermore, depending too much on content created by AI might compromise the originality and critical thinking components of research, which could affect the calibre and legitimacy of academic work.[8]

Furthermore, issues with authorship and intellectual property rights are brought up using AI in research. It gets harder to tell the difference between material created by AI and content produced by humans as AI models get more complex. The conventional concept of authorship and credit attribution in academic contexts is complicated by this blurring of boundaries. Establishing precise standards on how to properly recognise AI contributions while making sure that human researchers are appropriately credited for their intellectual work is a challenge that organisations and academics must face. For the academic community, striking a balance between the advantages of AI support for research and upholding academic integrity and real scientific growth is still a major concern.

AI in the Legal Profession: Current Use and Future Prospects

Artificial Intelligence (AI) has become a disruptive force in the legal field, changing established procedures and creating new avenues for opportunity. AI is now being used in many areas of the legal industry, including contract analysis, predictive analytics, document review, and research. Artificial intelligence (AI)-powered tools that can analyse millions of documents in seconds have revolutionised legal research, which was once a laborious process of manually searching through enormous libraries of case law and statutes. These tools give lawyers access to pertinent cases, statutes, and legal analyses at a speed and accuracy never before possible.

AI has shown to be very useful in the field of document assessment and e-discovery. These days, machine learning algorithms are significantly more rapid and accurate than human reviewers in sorting through massive amounts of emails, papers, and other digital exchanges to find pertinent information and possible evidence. This lowers expenses and saves time while simultaneously raising the standard of the discovery process as a whole. In a similar vein, artificial intelligence (AI) systems have revolutionized contract analysis by reviewing and extracting important data from intricate legal papers, highlighting possible problems and discrepancies that human reviewers would miss.

Another area where AI is significantly advancing the legal profession is predictive analytics. Artificial intelligence (AI) algorithms can forecast case outcomes, assess settlement prices, and even recommend the best course of action for litigation by evaluating enormous volumes of past case data. Attorneys are now able to make better-educated choices about client advising, resource allocation, and case management because to this skill.[9]

Future predictions indicate that the use of AI in the legal field will probably pick up speed and spread to other domains. The emergence of more advanced legal chatbots and virtual assistants is one possible trend. Regular legal enquiries might be handled by these AI-powered technologies, freeing up attorneys to concentrate on more difficult work. By giving those who cannot afford traditional legal services access to fundamental legal information and advice, they may also contribute to the improvement of justice access.

The use of AI to the draughting and negotiation of contracts is another field with room for expansion. Although contracts are now analysed by AI, in the future, these systems may also be able to construct complicated legal agreements according to predetermined guidelines and even conduct informal discussions. This might cut down on the amount of time attorneys spend on repetitive draughting duties and greatly streamline the contract writing process.

AI could possibly become increasingly important in judicial decision-making in the future. Artificial intelligence (AI) has the potential to be a useful auxiliary to human judges, even if it is unlikely to do so. It can do this by evaluating case law, locating pertinent precedents, and even making recommendations for verdicts based on past evidence. This could result in more uniform and fact-based court rulings.

But there are also significant practical and ethical issues raised by the growing usage of AI in the legal field, which will require attention. Important factors to take into account will include the possibility of AI systems causing bias, the possibility of employment displacement, and the requirement for attorneys to retain their fundamental analytical and social abilities in an AI-assisted setting. Debates over the proper ratio of human judgement to AI-assisted decision-making in the legal profession are probably going to continue.

To adequately educate upcoming solicitors for this AI-enhanced legal environment, the legal school system will also need to change. It may be necessary for law schools to include additional technology and data science courses to their curricula in order to prepare graduates to use AI technologies efficiently and see both their advantages and disadvantages.

ISSUES ARISE DUE TO USE OF AI IN LEGAL PROFESSION

Artificial intelligence (AI) tools have the ability to drastically alter legal research and document review, possibly replacing positions once filled by paralegals and young attorneys. Although artificial intelligence (AI) has the potential to boost productivity, issues with accuracy and algorithmic bias remain. Liability and malpractice concerns surface in the event that AI makes mistakes or fails to recognise important data. Additionally, it might be difficult to explain AI-assisted conclusions to courts and clients.

Ethical questions are raised by the use of AI to legal prediction and decision-making systems. Concerns arise that these kinds of systems can reinforce or magnify preexisting prejudices in the judicial system, especially when it comes to things like criminal sentence. Certain AI algorithms, also known as “black box” systems, are opaque, which goes against the ideas of due process and openness. How to make sure AI systems appropriately balance difficult legal and ethical issues is another area of concern.[10]

When legal businesses use AI systems, data privacy and confidentiality become more important issues. Data protection laws and the attorney-client privilege may be broken by feeding client data into outside AI systems. The requirement to train AI on massive datasets and the obligation to secure customer information can collide. Furthermore, in order to handle new circumstances and potential conflicts of interest, the use of AI may require revisions to the ethical standards and principles of professional behaviour for attorneys.

SUSTAINABILITY OF AI IN LEGAL FIELD

AI in law must be able to reliably produce findings that are morally sound, accurate, and efficient in order to be sustainable over the long run. AI systems have the potential to improve access to justice by cutting costs and expediting judicial proceedings as they advance. This, however, depends on continued funding for AI research and development, upkeep of current legal databases, and frequent audits of algorithms to guarantee accuracy and fairness. To ensure that solicitors are capable of managing and interpreting AI-generated outputs, the legal profession will need to modify its continuing education and training programs to incorporate AI literacy.

Sustainability in the environment is another factor. Large AI models require a huge amount of energy, even if they can save paper waste and travel through digital document management and virtual court appearances. Legal tech businesses and law firms will have to weigh the advantages of AI against its carbon footprint and consider making investments in renewable energy sources to mitigate the effects on the environment. Furthermore, the speed at which technology is developing might result in regular hardware updates, which would raise concerns regarding the management of electronic waste in the legal industry.[11]

Striking the correct balance between automation and human knowledge will be essential to the long-term financial viability of AI in the legal field. Artificial intelligence (AI) has the potential to upend established legal business structures and employment markets while simultaneously increasing efficiency and possibly lowering client expenses. To properly integrate AI, law firms will need to reorganise their pricing and operational strategies. The issue of how to sustainably finance the creation and upkeep of AI legal tools, particularly those targeted at enhancing underprivileged people’ access to justice, also has to be addressed. For legal AI to be sustainable over the long run and be accepted by the legal community, it will be essential to make sure that the advantages are shared fairly across society.

CONCLUSION

A thorough summary of the ways in which big data and technology are revolutionising the legal profession can be found in the article “Changing Landscape of Legal Profession: How Legal Tech, Big Data are Shaping the Future of Lawyers”. The essay does a good job of explaining the development and possible advantages of these technologies, but it might use a more critical and impartial analysis of its ramifications.

The author properly highlights the ways in which big data analytics and legal technology are boosting productivity, strengthening research capacities, and facilitating data-driven decision-making in the legal profession. The essay may, however, go into further detail about the possible disadvantages and moral dilemmas raised by these developments.

The section on the detrimental effects of technology adoption is especially significant since it raises critical points about the possible loss of human touch in legal services, employment displacement, and over-reliance on technology, among other things. These issues merit more investigation, particularly considering their potential long-term effects on the practice of law and the administration of justice.

The last section’s brief discussion of the ethical implications of AI in research raises important issues regarding correct attribution, academic integrity, and the evolving nature of authorship in the AI era. A more thorough examination of this subject is necessary, especially considering its connection to the larger issue of how technology is affecting the legal profession.

Although the essay offers a good starting point for comprehending the technology revolution in the legal field, it may benefit from more examples, case studies, or statistical information to bolster its arguments. Furthermore, a more comprehensive analysis of viable remedies or optimal methodologies to tackle the difficulties highlighted would augment the article’s pragmatic significance.

To sum up, this study effectively illustrates how legal technology and big data can revolutionise the legal industry. It may, however, benefit from a more thorough examination of the difficulties and moral issues, as well as additional hard data and useful suggestions for solicitors navigating this shifting terrain, to offer a more thorough perspective.

REFERENCES

[1] Rubin, Basha (6 December 2014). “Legal Tech Startups Have a Short History and A Bright Future”. TechCrunch. Retrieved 1 May 2015.

[2] Goodman, Bob (16 December 2014). “Four Areas of Legal Ripe for Disruption by Smart Startups”. Law Technology Today. Retrieved 1 May 2015

[3] Rubin, Basha (6 December 2014). “Legal Tech Startups Have a Short History and A Bright Future”. TechCrunch. Retrieved 1 May 2015

[4] Breur, Tom (July 2016). “Statistical Power Analysis and the contemporary “crisis” in social sciences“. Journal of Marketing Analytics. 4 (2–3). London, England: Palgrave Macmillan:

[5] Mahdavi-Damghani, Babak (2019). Data-Driven Models & Mathematical Finance: Apposition or Opposition? (DPhil thesis). Oxford, England: University of Oxford. p. 21. SSRN 3521933

[6] The History, Evolution, & Technologies of Big Data, by TechVidvan Team, https://techvidvan.com/tutorials/big-data-history/ 22/09/2024

[7] How technology is changing the legal sector, Amy Bullows

Pages 258-264 | Published online: 13 Aug 2021

[8] Resnik, D.B., Hosseini, M. The ethics of using artificial intelligence in scientific research: new guidance needed for a new tool. AI Ethics (2024). https://doi.org/10.1007/s43681-024-00493-8

[9] Karklins, L., & Nalick, M. (2021). AI and legal ethics: A comparative analysis of AI usage in U.S. and European legal systems. Harvard Journal of Law & Technology, 34(2), 233-259.

[10] Gupta, S. (2020). Leveraging AI for the Indian legal system: Challenges and opportunities. Indian Law Review, 4(3), 281-299. https://doi.org/10.1080/24730580.2020.1783994

[11] Russell, S., & Norvig, P. (2020). Artificial Intelligence: A Modern Approach (4th ed.). Pearson.

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