Legal technology

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Legal technology, also known as Legal Tech, [1] [2] refers to the use of technology and software to provide legal services and support the legal industry. Legal Tech companies are often startups founded with the purpose of disrupting the traditionally conservative legal market. [3]

Contents

Different approaches and technologies have been used for legal tasks. Traditional software architecture and web technologies have been used for tasks like providing access to case law. [4] Machine learning approaches have been used to help find documents for due diligence or discovery. [5] : 1329  Work on making contracts more easy to use involve aspects of user experience design. [6] : 69 

Definitions

Legal technology traditionally referred to the application of technology and software to help individual lawyers, law firms, medium and large scale businesses with practice management, document automation, document storage, billing, accounting and electronic discovery. [2] [7] : 83  Since 2011, Legal Tech has evolved to be associated more with technology startups disrupting the practice of law by giving people access to online software that reduces or in some cases eliminates the need to consult a lawyer, or by connecting people with lawyers more efficiently through online marketplaces and lawyer-matching websites. [1] In the 2010s tech companies specializing in helping consumers bring claims against traders made legal technology a mass phenomenon. Spearheads of consumer legal tech are Flightright and Fairplane, both specialize in enforcing air passenger rights under the EU's Flight Compensation Regulation. These service providers use claims management automation to process vast quantities of claims cheaply and on a no win no fee basis. [8]

History

From the 1970s through to the 1990s there were several academic attempts to formalize legal reasoning, a knowledge representation task. [5] : 1327  The International Conference of Artificial Intelligence and Law (ICAIL) has been held since 1987 [5] : 1327  The first commercially available legal AI system was an expert system released in 1988 by the University of Oxford to tell users if a new piece of legislation, the latent damage act applied to them. [9] : 132  Since 2000, there have been more attempts to make legal tasks easier using machine learning approaches rather than knowledge representation. [5] : 1328  In the mid 2000s so-called predictive coding became possible for use in the discovery process of litigation. These predictive coding tools helped lawyers predict which documents were relevant or irrelevant for the litigation, after having been trained on a subset of documents. [5] : 1329 

In 1975 in the US, the Federal Judicial Center started the COURTRAN project for the electronic recording of court records. This was initially used for criminal cases, but later was adapted for managing civil cases. COURTRAN was replaced by the Integrated Case Management System in the mid 1980s. [10] The Legal Information Institute was set up in 1992, at Cornell University with the aim of making law more accessible, [11] and began providing access to US supreme court decisions. [12] Development of the PACER to nationwide access to court records, began in 1990 and by the mid 1990s, 180 federal courts were offering fee based access to court records via dial-up internet access. [13] : 860  The E-Government Act of 2002 limited the fees to only the extent necessary. [13] : 863  The Open Courts Act of 2020 set out a plan to make PACER free to use by 2025. [14]

Applications

Case law databases

Use of tools to aid with legal research is very common within the legal field. Commercial companies such as Practical Law Company, LexisNexis, and Reuters offer services where a lawyer can pay to search case law.[ citation needed ] In the early 1990s the Cornell Legal Information Institute (ILL) started to provide free of charge full text access to US Supreme Court judgements. A database of Canadian Supreme Court decisions was hosted under the name LexUM. In Australia the AustLII (Australasian Legal Information Institute) was founded in 1995. It was the first free case law database to achieve national coverage and now comprises over 200 databases with case law from virtually all courts and tribunals. The British and Irish Legal Information Institute (BAILII) was established in 1999. These initiatives demonstrated the strong demand for free public access to case law to aid legal research and the Free Access to Law Movement was formally established in 2002. [15] In the US the Caselaw Access Project, run by Harvard Law School, had by 2018 scanned in excess of 40 million legal documents relating to reported US state and federal cases. US case law is made accessible free of charge and via an application programming interface (API). [16]

Document automation

Legal technology companies such as LegalZoom and Rocket Lawyer provide consumers and small businesses with document automation services. Document drafting is rules-based legal work and drafts of legal documents, such as contracts and the documents required for company formation, can be reliably generated through an interactive website. [17] LegalZoom and Rocket Lawyer can assemble the full range of legal documents required in the United States to be filed in court for official record or court proceedings. [18] Document automation service assemble legal documents out of templates with fill-in-blanks. The legal document is interactively assembled via a question and answer program, where the user is responding to queries. Law firms have access to a range of document automation services on a subscription basis. Lawyers can automate their own templates or pay to access prefabricated templates. [19] Since the 1970s more than 65 legal document automation services have been commercially available to lawyers. Well established document automation services for lawyers include ContractExpress and HotDocs. [20]

Template based document automation works best for contracts that use boilerplate clause, model contracts or standard clauses. The integration of predictive analytics allows for predictive contracting, where the drafter is provided with statistical information about the likelihood that a nonstandard clause will be subject to litigation or adverse judicial interpretation. Contract analytics services provided by LexPredict and Bloomberg L.P. use natural language processing (NLP) tools to find unique clauses in contracts [21] by identifying statistical patterns within language syntax. [22]

There have been attempts to improve the design of contracts, which have traditionally been seen as documents by lawyers for lawyers. Suggested improvements to the design of contracts have considered how contracts could convey more information visually, more directly address business needs, and improve relationships between the parties of a contract. [6] : 69  Scholars have suggested the use of so-called self-executing contracts, where the terms of the contract are automatically updated by a computer using predefined rules. A further step would be the generation of a machine-readable representation of the contract that could be used in other automated processes such as contract lifecycle management. [6] : 74 

Cyberjustice

The judiciary have expressed interest in the potential for electronics filing to reduce costs and increase efficiency [23] : 18  and online alternative dispute resolution as a means to reduce costs to claimants increasing access to justice. [24] [23] : 19  Technological approaches are being used to provide guidance for sentencing and pretrial detention in some courts, including machine-learning based solutions which have been criticized for potential racial bias issues. [25] : 10  [26] Litigation outcome prediction tools have been introduced to the market by the big three legal research providers LexisNexis, Westlaw, and Bloomberg Law. The Lex Machina estimates a judges' likelihood of granting or denying a motion. [27] Litigation outcome prediction tools have been criticized for potentially harming access to justice, as would-be litigants with claims that are judged too novel or less viable may be denied legal representation. [28]

Approaches

Artificial intelligence, machine learning and natural language processing are being applied to machine learning tasks particularly those related to search, such as due diligence and discovery in litigation cases. [7] : 133 

Knowledge graphs are being applied to assist in the creation, management, and analysis of smart contracts.

Rule-based expert system have been used for the purposes knowledge representation and querying legal knowledge, one such example being TurboTax. [5] : 1317  These approaches are studied in Legal informatics.

Industry context

The legal industry is widely seen to be conservative and traditional, with Law Technology Today noting that "in 50 years, the customer experience at most law firms has barely changed". [3] Reasons for this include the fact law firms face weaker cost-cutting incentives than other professions (since they pass disbursements directly to their client) and are seen to be risk averse (as a minor technological error could have significant financial consequences for a client). [3]

However, the growth of the hiring by businesses of in-house counsel and their increasing sophistication, together with the development of email, has led to clients placing increasing cost and time pressure on their lawyers. [3] In addition, there are increasing incentives for lawyers to become technologically competent, with the American Bar Association voting in August 2012 to amend the Model Rules of Professional Conduct to require lawyers to keep abreast of "the benefits and risks associated with relevant technology", [29] [30] and in late 2019, the Federation of Law Societies of Canada adopted a similar amendment to the Model Code of Professional Conduct. [31] The saturation of the market is leading many lawyers to look for cutting-edge ways to compete. [1] The exponential growth in the volume of documents (mostly email) that must be reviewed for litigation cases has greatly accelerated the adoption of technology used in eDiscovery, with elements of machine language and artificial intelligence being incorporated and cloud-based services being adopted by law firms. [32]

Stanford Law School has started CodeX, the Center for Legal Informatics, an interdisciplinary research center, which also incubates companies started by law students and computer scientists. Some companies that have come out of the program include Lex Machina and Legal.io. [2] [33]

Legal tech investment hit a record in 2019 at $1.2 billion. [34]

Societal issues

Many critics have voiced concerns about the risk of bias in the decisions made by models trained using machine learning approaches such as sentencing decisions, arguing that a model could learn the bias in existing decisions. [5] : 1335  Others have voiced concerns about the explainable of the decisions made by machine learning models arguing that such models can be a black box. There are concerns about the possibility that models could be viewed as objective and infalliable when they are not. [5] : 1336 

There is interest in the use of legal technology to increase access to justice. Programs have attempted to use legal technology to improve access to justice by improving processes, automating access to legal information and advice, and improving user interaction. [35]

Key areas

Traditional areas of Legal Tech include:

More recent areas of growth in Legal Tech focus on:

Related Research Articles

<span class="mw-page-title-main">Paralegal</span> Paraprofessional who assists qualified lawyers in their legal work

A paralegal, also known as a legal assistant, or paralegal specialist is a legal professional who performs tasks that require knowledge of legal concepts but not the full expertise of a lawyer with a license to practice law. The market for paralegals is broad, including consultancies, companies that have legal departments or that perform legislative and regulatory compliance activities in areas such as environment, labor, intellectual property, zoning, and tax. Legal offices and public bodies also have many paralegals in support activities using other titles outside of the standard titles used in the profession. There is a diverse array of work experiences attainable within the paralegal field, ranging between internship, entry-level, associate, junior, mid-senior, and senior level positions.

Confidentiality involves a set of rules or a promise usually executed through confidentiality agreements that limits the access to or places restrictions on distribution of certain types of information.

In law, a settlement is a resolution between disputing parties about a legal case, reached either before or after court action begins. A collective settlement is a settlement of multiple similar legal cases. The term also has other meanings in the context of law. Structured settlements provide for future periodic payments, instead of a one time cash payment.

A contingent fee is any fee for services provided where the fee is payable only if there is a favourable result. Although such a fee may be used in many fields, it is particularly well associated with legal practice.

Legal informatics is an area within information science.

The Electronic Filing System is the Singapore Judiciary's electronic platform for filing and service of documents within the litigation process. In addition, it provides the registries of the Supreme Court and the Subordinate Courts with an electronic registry and workflow system; and an electronic case file. Recent enhancements have added a module which facilitates the conduct of hearing using documents that have been electronically filed.

Electronic discovery refers to discovery in legal proceedings such as litigation, government investigations, or Freedom of Information Act requests, where the information sought is in electronic format. Electronic discovery is subject to rules of civil procedure and agreed-upon processes, often involving review for privilege and relevance before data are turned over to the requesting party.

Attorney misconduct is unethical or illegal conduct by an attorney. Attorney misconduct may include: conflict of interest, overbilling, false or misleading statements, knowingly pursuing frivolous and meritless lawsuits, concealing evidence, abandoning a client, failing to disclose all relevant facts, arguing a position while neglecting to disclose prior law which might counter the argument, or having sex with a client.

In Australia, legal professional privilege is a rule of law protecting communications between legal practitioners and their clients from disclosure under compulsion of court or statute. While the rule of legal professional privilege in Australia largely mirrors that of other Commonwealth jurisdictions, there are a number of notable qualifications and modifications to the privilege specific to Australia and its states, and contentious issues about the direction of the privilege.

In England and Wales, the principle of legal professional privilege has long been recognised by the common law. It is seen as a fundamental principle of justice, and grants a protection from disclosing evidence. It is a right that attaches to the client and so may only be waived by the client.

The terms legal case management (LCM), legal management system (LMS), matter management or legal project management refer to a subset of law practice management and cover a range of approaches and technologies used by law firms and courts to leverage knowledge and methodologies for managing the life cycle of a case or matter more effectively. Generally, the terms refer to the sophisticated information management and workflow practices that are tailored to meet the legal field's specific needs and requirements.

Pro se legal representation comes from Latin pro se, meaning "for oneself" or "on behalf of themselves" which, in modern law, means to argue on one's own behalf in a legal proceeding, as a defendant or plaintiff in civil cases, or a defendant in criminal cases, rather than have representation from counsel or an attorney.

Legal aid in the United States is the provision of assistance to people who are unable to afford legal representation and access to the court system in the United States. In the US, legal aid provisions are different for criminal law and civil law. Criminal legal aid with legal representation is guaranteed to defendants under criminal prosecution who cannot afford to hire an attorney. Civil legal aid is not guaranteed under federal law, but is provided by a variety of public interest law firms and community legal clinics for free or at reduced cost. Other forms of civil legal aid are available through federally-funded legal services, pro bono lawyers, and private volunteers.

A legal expert system is a domain-specific expert system that uses artificial intelligence to emulate the decision-making abilities of a human expert in the field of law. Legal expert systems employ a rule base or knowledge base and an inference engine to accumulate, reference and produce expert knowledge on specific subjects within the legal domain.

Computational Law is the branch of legal informatics concerned with the automation of legal reasoning. What distinguishes Computational Law systems from other instances of legal technology is their autonomy, i.e. the ability to answer legal questions without additional input from human legal experts.

Catalyst Repository Systems is a privately held company based in Denver, Colorado, USA, which develops, hosts and supports cloud-based software for the management of electronic legal discovery. Founded in 2000, the company’s main product is Insight Discovery. Catalyst has offices and data centers throughout the United States and an office and data center in Tokyo, Japan.

Cyberjustice is the incorporation of technology into the justice system, either through offering court services electronically or through the use of electronics within courtrooms or for other dispute resolution purposes. One of the most crucial goals of cyberjustice is increasing access to justice through both reducing the costs associated with administering justice as well as reducing the burden on the judges and the court system as a whole.

Lawbots are a broad class of customer-facing legal AI applications that are used to automate specific legal tasks, such as document automation and legal research. The terms robot lawyer and lawyer bot are used as synonyms to lawbot. A robot lawyer or a robo-lawyer refers to a legal AI application that can perform tasks that are typically done by paralegals or young associates at law firms. However, there is some debate on the correctness of the term. Some commentators say that legal AI is technically speaking neither a lawyer nor a robot and should not be referred to as such. Other commentators believe that the term can be misleading and note that the robot lawyer of the future won't be one all-encompassing application but a collection of specialized bots for various tasks.

PainWorth is a justice, legal and insurance services application founded by Canadian entrepreneurs Mike Zouhri, Chris Trudel and Ryan Bencic. The application is a "robot lawyer" that uses artificial intelligence to automate personal injury claims for injury victims. It is currently available in Canada and the United States.

The legal industry refers to the aggregation and integration of sectors within the economic system that provide legal goods and services. The global legal industry is fast-growing: in 2015, it was valued at USD 786 billion, USD 886 billion by 2018 and is expected to exceed USD 1 trillion by 2021. The United States and Europe dominate the legal industry, with the former accounting for more than half of the global market revenue. Meanwhile, Europe accounts for more than a quarter of revenue. Legal services in the Asia-Pacific region continues to grow, with total revenues of $103.3 billion in 2018.

References

  1. 1 2 3 Rubin, Basha (6 December 2014). "Legal Tech Startups Have A Short History And A Bright Future". TechCrunch. Retrieved 1 May 2015.
  2. 1 2 3 Hibnick, Eva (7 September 2014). "What is Legal Tech?". The Law Insider. Retrieved 1 May 2015.
  3. 1 2 3 4 Goodman, Bob (16 December 2014). "Four Areas of Legal Ripe for Disruption by Smart Startups". Law Technology Today. Retrieved 1 May 2015.
  4. ↑ "AustLII - User Tools: Sino Free Text Search Engine". www.austlii.edu.au. Retrieved 2021-09-26.
  5. 1 2 3 4 5 6 7 8 Surden, Harry (1 June 2019). "Artificial Intelligence and Law: An Overview". Georgia State University Law Review. 35 (4). SSRN   3411869.
  6. 1 2 3 Marcelo Corrales; Mark Fenwick; Helena Haapio, eds. (2019). Legal tech, smart contracts and Blockchain. Singapore. ISBN   978-981-13-6086-2. OCLC   1084757003.{{cite book}}: CS1 maint: location missing publisher (link)
  7. 1 2 Susanne Chishti, ed. (2020). The legaltech book: the legal technology handbook for investors, entrepreneurs and FinTech visionaries. Chichester, West Sussex, United Kingdom. ISBN   978-1-119-70806-3. OCLC   1154093755.{{cite book}}: CS1 maint: location missing publisher (link)
  8. ↑ Christine Riefa; Severine Saintier (2020). Vulnerable Consumers and the Law: Consumer Protection and Access to Justice. Taylor & Francis. p. 229. ISBN   978-1-000-20970-9.
  9. ↑ Susskind, Daniel; Susskind, Richard (June 2018). "The Future of the Professions". Proceedings of the American Philosophical Society. 162 (2): 125–138. JSTOR   45211625. ProQuest   2157781264.
  10. ↑ Owen, Forrester J (1995). "History of the Federal Judiciary's Automation Program, The L. Ralph Mecham & Federal Courts Administration: A Decade of Innovation and Progress". American University Law Review .
  11. ↑ "LII:Overview" . Retrieved 2010-03-04.
  12. ↑ St. Amant, Kirk (2007). Handbook of Research on Open Source Software: Technological, Economic, and Social Perspectives. IGI Global. p. 375. ISBN   978-1-59140-999-1.
  13. 1 2 Martin, Peter W. (2008). "Online Access to Court Records - From Documents to Data, Particulars to Patterns". Villanova Law Review. 53: 855.
  14. ↑ Lee, Timothy B. (2020-12-10). "US House passes bill to tear down judiciary's paywall". Ars Technica. Retrieved 2021-09-26.
  15. ↑ Pierre F. Tiako, ed. (2009). Software Applications: Concepts, Methodologies, Tools, and Applications. IGI Global. p. 2805. ISBN   978-1-60566-061-5.
  16. ↑ Dwight Steward; Roberto Cavazos (2019). Big Data Analytics in U.S. Courts. Springer International Publishing. p. 77. ISBN   978-3-030-31780-5.
  17. ↑ David Freeman Engstrom (2023). Legal Tech and the Future of Civil Justice. Cambridge University Press. p. 35. ISBN   978-1-009-25535-6.
  18. ↑ David Freeman Engstrom (2023). Legal Tech and the Future of Civil Justice. Cambridge University Press. p. 38. ISBN   978-1-009-25535-6.
  19. ↑ Michael Legg; Felicity Bell (2020). Artificial Intelligence and the Legal Profession. Bloomsbury Publishing. p. 179. ISBN   978-1-5099-3183-5.
  20. ↑ Daniel Martin Katz; Michael J. Bommarito; Ron Dolin, eds. (2021). Legal Informatics. Cambridge University Press. p. 76. ISBN   978-1-107-14272-5.
  21. ↑ Michael Legg; Felicity Bell (2020). Artificial Intelligence and the Legal Profession. Bloomsbury Publishing. p. 180. ISBN   978-1-5099-3183-5.
  22. ↑ Daniel Martin Katz; Michael J. Bommarito; Ron Dolin, eds. (2021). Legal Informatics. Cambridge University Press. p. 89. ISBN   978-1-107-14272-5.
  23. 1 2 Neuberger, David (2016). "British Irish Commercial Bar Association Law Forum: Technology and the Law. Closing Keynote Address" (PDF). Supreme Court (UK).
  24. ↑ Online Dispute Resolution Advisory Group. ONLINE DISPUTE RESOLUTION FOR LOW VALUE CIVIL CLAIMS. Civil Justice Council.
  25. ↑ Kehl, Danielle Leah; Kessler, Samuel Ari (2017). "Algorithms in the Criminal Justice System: Assessing the Use of Risk Assessments in Sentencing". Harvard University. S2CID   217366408.
  26. ↑ Thomas, C.; Nunez, A. (2022). "Automating Judicial Discretion: How Algorithmic Risk Assessments in Pretrial Adjudications Violate Equal Protection Rights on the Basis of Race". Law & Inequality . 40 (2): 371–407. doi: 10.24926/25730037.649 .
  27. ↑ David Freeman Engstrom (2023). Legal Tech and the Future of Civil Justice. Cambridge University Press. p. 162. ISBN   978-1-009-25535-6.
  28. ↑ David Freeman Engstrom (2023). Legal Tech and the Future of Civil Justice. Cambridge University Press. p. 167. ISBN   978-1-009-25535-6.
  29. ↑ "Client-Lawyer Relationship, Rule 1.1 Competence - Comment". American Bar Association. Retrieved 1 May 2015.
  30. ↑ Ambrogi, Robert. "The Cloud Has Landed: 10 Legal Tech Innovations and What They Mean". Wisconsin Lawyer. Retrieved 1 May 2015.
  31. ↑ "Interactive Model Code of Professional Conduct".
  32. ↑ James N Dertouzos, Nicholas M Pace and Robert H Anderson, The Legal And Economic Implications Of Electronic Discovery (Rand Institute for Civil Justice, 2008) 3; Pavan Mediratta, "Using Legal Data Analytics To Gain A Competitive Advantage", LAW.COM (Webpage, 2017) <https://www.law.com/native/?mvi=80e16694159446d0ae29f6c93e95806c&slreturn=20200028224509>.
  33. ↑ Stanford Law School (2016-11-27). "CodeX - Programs and Centers - Stanford Law School". Law.stanford.edu. Archived from the original on 2015-07-18. Retrieved 2016-12-10.
  34. ↑ "At $1.2 Billion, 2019 Is A Record Year for Legal Tech Investments -- And It's Only September". LawSites. 2019-09-16. Retrieved 2021-01-10.
  35. ↑ "Technology, Access to Justice and the Rule of Law" (PDF). The Law Society.
  36. ↑ "Legal Schema and beyond - Legislate". www.legislate.tech. Retrieved 2022-02-03.
  37. ↑ Hobbs, Stephen (14 December 2015). "Simplifying idea | Colorado Springs Gazette, News". Gazette.com. Retrieved 2016-12-10.
  38. ↑ Ho, Catherine. "FileRight Aims to Help with Immigration". Archived from the original on 2017-01-25. Retrieved 2016-10-18.
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