Legal informatics

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Legal informatics is an area within information science. Erdelez and O’Hare (1997) define legal informatics as follows:

The American Library Association defines informatics as “the study of the structure and properties of information, as well as the application of technology to the organization, storage, retrieval, and dissemination of information.” Legal informatics therefore, pertains to the application of informatics within the context of the legal environment and as such involves law-related organizations (e.g., law offices, courts, and law schools) and users of information and information technologies within these organizations.

Delivery of legal services[edit]

Advances in technology and legal informatics have led to new models for the delivery of legal services. Legal services have traditionally been a "bespoke" product created by a professional attorney on an individual basis for each client.[1] However, to work more efficiently, parts of these services will move sequentially from (1) bespoke to (2) standardized, (3) systematized, (4) packaged, and (5) commoditized.[1] Moving from one stage to the next will require embracing different technologies and knowledge systems.[1]

Cloud computing and legal services[edit]

The widespread introduction of cloud computing provides several benefits in delivering legal services. Legal service providers can use the Software as a Service model to earn a profit by charging customers a per-use or subscription fee. This model has several benefits over traditional bespoke services.

  • Software as a Service is much more scalable. Traditional bespoke models require an attorney to spend more of a limited resource (their time) on each additional client. Using Software as a Service, a legal service provider can put in effort once to develop the product and then use a much less limited resource (cloud computing power) to provide service to each additional customer.
  • Software as a Service can be used to complement traditional bespoke services by handling routine tasks, leaving an attorney free to concentrate on bespoke work.
  • Software as a Service can be delivered more conveniently because it does not require the legal service provider to be available at the same time as the customer.

Software as a Service also complicates the attorney-client relationship in a way that may have implications for attorney-client privilege. The traditional delivery model makes it easy to create delineations of when attorney-client privilege attaches and when it does not. But in more complex models of legal service delivery other actors or automated processes may moderate the relationship between a client and their attorney making it difficult to tell which communications should be legally privileged.[2]

Latent markets[edit]

Because the traditional model for delivery services demanded all legal work to be done in a bespoke manner the supply of legal services is generally inelastic. Households that are ineligible for legal aid but are not able to easily afford bespoke legal services are effectively underserved by the traditional model. A report by the American Bar Association Standing Committee on the Delivery of Legal Services found that “among moderate-income households, 39% used the legal system to attempt resolution of their legal problems, 23% attempted resolution without legal help, and 26% took no action.”[3] New organizations seek to access this underserved latent market by using technology to reduce prices and make services more available.

Online legal services[edit]

The spread of the Internet and development of legal technology and informatics are extending legal services to individuals and small-medium companies.

See also Document automation#In Legal Services

In the U.S.[edit]

In 1995, FindLaw started its online legal information service. At Findlaw, users can search lawyers, discuss legal topics in open forum, and purchase legal forms. In 1999, LegalMatch started its online legal matching service. At LegalMatch, users answers questions online, LegalMatch identify the service required and notifies relevant lawyers, and users receives responses from the lawyers and can decide who to hire. In 2001, LegalZoom started its online legal documentation service. At LegalZoom, users can create legal documents for personal and business use by answering a questionnaire online and purchase the completed document. In 2008, Rocket Lawyer started its online legal service. At Rocket Lawyer, users can receive legal documentation service and the On Call service to consult lawyers for personal and business needs at monthly or annual subscription fee. In 2012, Shake started its mobile legal documentation service. With Shake, users can create simple legal agreements via a mobile app.

In Japan[edit]

In 2005, Taichiro Motoe, an attorney at law qualified in Japan, founded Authense Group, Inc.[4] and started its online legal service, Bengoshi.com.[5] At Bengoshi.com, users can search lawyers, ask legal questions and receive answers from lawyers in open forum, request estimate for attorney fees, and consult lawyers for personal and business needs.

Regulatory barriers to delivery of legal services[edit]

Currently available legal technologies and processes cannot be implemented due to various regulations on the practice of law put into place by state bar associations and state statutes. There is controversy over whether these regulations remain in place due to economic wagon-circling by attorneys or out of genuine concern for potential harms to customers. Regulations which pose obstacles to widespread adoption of new legal technologies and processes include unauthorized practice of law statutes, ethical rules restricting alternative business structures for law firms, and professional rules which make practicing law in multiple jurisdictions difficult.

Unauthorized practice of law[edit]

Layperson organizations seeking to provide legal services must be careful to avoid committing unauthorized practice of law or face exposure to litigation from consumers and regulators. The definition of what constitutes unauthorized practice of law is nebulous and has been criticized as a potentially unconstitutional restriction on free speech.[6]

Alternative business structures[edit]

In the United States a complete bar to nonlawyer ownership has been adopted by the American Bar Association as paragraph (d) of Rule 5.4 of the Model Rules of Professional Conduct and has been codified in one form or another in all U.S. jurisdictions,[7][8] except the District of Columbia.[9] Because of these rules, law firms face additional difficulties in raising equity capital to finance development of their own legal technologies and additional regulatory requirements compared to layperson organizations. Outside of the United States there are several countries which have allowed nonlawyer ownership of law firms ranging from limitations on percentage ownership combined with a “fit to own” test[10] (as in the United Kingdom) to allowing passive equity investment in law firms[10] (as in Australia).

Multijurisdictional practice[edit]

Rule 5.5 of the Model Rules of Professional Conduct requires that attorneys who maintain a "systematic and continuous practice" in a jurisdiction be admitted to practice in that jurisdiction.[11] For law firms that wish to provide legal services over online delivery platforms, this phrase is unclear as to what types of activities within a state require licensing in that state.[12] This difficulty is especially acute for virtual law firms.

Access to justice through technology[edit]

Lawyers, designers, and computers scientists have considered ways to use technology to improve non-lawyers' access to legal resources and information.

IIT's Institute of Design and the Chicago-Kent College of Law collaborated on a multi-year redesign of self-represented litigants' court experience. Their 2002 report documented their investigation of current assistance systems, creation of a new design protocol, and plan for a new system design.[13] The report also puts forward a number of concept designs, reimagining how the court system may work and people may access it. Some of their proposals include:

  • "CourtNet", a network inside the court building, to link together judicial staff and the public;
  • "Interactive Translator", a software tool that can be used in interviewing and court exchanges, able to translate verbal and text communications into different languages;
  • "Archetypes", a diagnosis platform that models users' legal problems, classifies them, and offers referral services;
  • "Pursuit Evaluator", an online tool to allow potential litigants evaluate whether pursuing a case would be worth their time, money, and effort
  • "Complaint Formulator", an electronic interface to let litigants extract data from their problem situation and assemble it into various legal documents;
  • "Informer", software that uses sample cases to help litigants model their own forms and teaches them how to file correctly; and
  • "Case Tracker", an interactive searchable archive of a litigant's case history, that provides a clear timeline and reference to past actions.

The Berkman Center at Harvard Law School has been working with Massachusetts housing court judge Dina Fein to design access to civil justice in the state for pro se litigants, low-income people, litigants who aren't proficient in English, and people with disabilities.[14]

Richard Zorza, an attorney and founder of the Self-Represented Litigation Network, maintains a blog profiling new initiatives and studies about the use of technology to promote access to justice.[15]

Law and policy[edit]

Law and policy issues in legal informatics stem from the use of informational technologies in the implementation of law, such as the use of subpoenas for information found in email, search queries, and social networks. Policy approaches to legal informatics issues vary throughout the world; for example, European countries tend to require destruction or anonymization of data so that it cannot be used for discovery.[16]

Digital rights management and copyright law[edit]

Copyright holders make use of Digital rights management (DRM) technology to limit the use and distribution of digital content. In the United States, the Anti-circumvention provision of the Digital Millennium Copyright Act criminalizes attempts to circumvent DRM. The DMCA criminalizes circumvention of DRM, even in cases where the circumvention was merely to facilitate non-infringing uses of the content. Along with the anti-circumvention provision, DRM can override substantive rights, such as Fair Use.[17]

Legal informatics in legal practice[edit]

Within the practice issues conceptual area, progress continues to be made on both litigation and transaction focused technologies. In particular, technology including predictive coding has the potential to effect substantial efficiency gains in law practice. Though predictive coding has largely been applied in the litigation space, it is beginning to make inroads in transaction practice, where it is being used to improve document review in mergers and acquisitions.[18] Other advances, including XML coding in transaction contracts, and increasingly advanced document preparation systems demonstrate the importance of legal informatics in the transactional law space.[19]

Artificial intelligence and legal issues[edit]

Artificial intelligence is, more and more, allowing machines to become more autonomous. Machines are able to deliver services and execute actions that are primarily performed by humans, being increasingly capable of sensing its environment and taking actions. This poses ethical and legal questions as to what will be the future of the computer age and how that will impact our lives. Free will and empathy are concepts that are being discussed as to whether they can be exhibited by a machine. Several questions are raised as to who will ultimately bear the responsibility of a machine's actions and who will be accountable. This has important consequences in the Law, mainly in criminal law Criminal law and its objectives regarding enforcement by punishments: retribution, deterrence, incapacitation, rehabilitation and restoration. Artificial intelligence is already employed in online dispute resolution platforms that use optimization algorithms and blind-bidding, and may be employed extensively in the future.[20]

Legal ontology[edit]

Artificial intelligence is frequently employed in modeling the legal ontology. An ontology attempts to create “an explicit, formal, and general specification of a conceptualization of properties of and relations between objects in a given domain.” [21] Applied to the law one theory suggested by Ronald Dworkin is to create a legal theory based on three stages:

  1. identification of rules, standards, and precedent decisions;
  2. identification of the underlying principles and values;
  3. re-formulation of the set of rules performing the identified principles of the second stage.

One possible ontology within this structure is a case based reasoning system. Examples of Artificial intelligence cases based reasoning models include HYPO [22] and CATO.[23] Both models identify legal factors in a particular area of law, trade secret law.[24] CATO can also manipulate and generalize these factors to make legal arguments.[24] This aspect allows CATO to be used in legal instruction to train students.[24]

Case-based legal prediction[edit]

Drawing from work on legal ontologies, case-based reasoning predictive models have been created using Artificial Intelligence. The CATO model was adapted into a predictive model. CATO predicted but was outperformed by a machine learning algorithm using a naive bayes approach. IBP is another case based reasoning model in trade secret law.[25] IBP improved the CATO predictive framework and predicted 91.8% of trade secret cases.[26] The IBP model also used an early version of the SMILE legal information retrieval algorithm.[27]

Quantitative legal prediction[edit]

Both academic and proprietary quantitative legal prediction models currently exist. One of the earliest examples of a working quantitative legal prediction model occurred in the from the Supreme Court forecasting project. The Supreme Court forecasting model attempted to predict the results of all the cases on the 2002 Term of the Supreme Court. The model predicted 75% of cases correctly compared to experts who only predicted 59.1% of cases.[28] Another example of an academic quantitative legal prediction models is a 2012 model that predicted the result of Federal Securities Class Action Lawsuits.[29] Also there are legal technology startups that are attempting to create proprietary models to predict case outcomes. One example is Lex Machina [30] a company that provides Intellectual Property data and analytics.

Legal informatics and criminal law[edit]

Can legal informatics help change the way we think about the law as a system of power and control? In 1995, Peter W. Martin’s paper for the NCAIR Sponsored Program on the Future of Legal Information Technology, entitled “Digital Law: Some Speculations on the Future of Legal Information Technology,” wondered how innovations in technology were shaping—and would shape—legal information flow, storage, and organization.[31] In other words, Martin was wondering how technology would change the fundamental nature and practice of the legal field in the United States. Martin wrote that “There is a powerful (but infrequently noticed) linkage between ways societies think about law and the technology they use in operation and distribution of it (law that is).”[32]

Martin was writing shortly after launching the Legal Information Institute at Cornell, the first law server on the internet. LEXIS had pioneered putting digital legal content on computers twenty-four years prior, and digital content now accounted for more than 50% of the legal information market.[32] Martin asked readers to suspend their disbelief as he proposed relatively rapid shifts in the ratio of paper-based legal information to digital legal information; the power wielded by the information-seeking public vs. high-priced gatekeepers of legal information; and a shift away from the private sector as a means to basic legal data and towards more higher-level skill sets.[32]

Martin suggested “fuller” bodies of data, pointing to a case in which the court thoroughly discussed a restaurant’s trademark decor without ever showing a picture of the decor.[32] Martin also highlights the Penalty Statistics Database in use in sentencing in New South Wales, and comparing it to the Federal Sentencing Guidelines of the United States.[32] The South Wales model, launched in 1990, allows judges access not only to both more traditional legal data, including statutory provisions and appellate decisions but also to the availability of alternate facilities (such as drug rehabilitation programs).[32] The “Penalty Statistics Database” furthermore gives judges access to a pre-analyzed data pool of sentencing decisions made by other sentencing officers in New South Wales, as well as full offense and offender information.[32] In this suggestion, too, Martin emphasizes the Penalty Statistics Database’s use of graphical display to make the information it is transmitting to judges easier to access and utilize.

Treating legal informatics as a field as a serious tool for changing the way people interact with the law may pave the way for radical innovations in areas of law that are seen as inherently static, top-down, and bureaucratic.

Legal informatics in the corporate legal departments[edit]

Today's corporate legal departments are entities which can be as large as the biggest law firms. As such, the usage of different legal informatics technologies is important for their success. Legal departments use among other: various technology aids to manage their document databases, and more advanced assets such as patent portfolios. Some legal departments are also experimenting with the automation of certain types of tasks performed by in-house attorneys in their day-to-day practice. These tasks include: preparation of documents, editing and customization of these documents and the management of signatures.

Legal informatics and corporate governance[edit]

The prevailing corporate governance paradigm, especially when public companies are concerned, is largely based on the notion of the relative efficiency of separating ownership and control in managing business corporations.[33] However, technological change can affect the equilibrium of optimal governance structure for individual firms. For instance, by lowering the cost of both disseminating information to shareholders and gathering data about their preferences, developments in communication technology can potentially make it preferable for some firms to organize the management of the firm in a manner more similar to, for example, direct democracy, with features such as two-way communication between the company’s senior management and its investors. The study of such questions thus applies legal informatics to analyzing the relationship between technology and corporate governance structures.

Legal information retrieval[edit]

See also[edit]

Sources[edit]

  • Erdelez, S, and S & O’Hare (1997). "Legal informatics: application of information technology in law", Annual Review of Information Science and Technology, 32: 367-402.

References[edit]

  1. ^ a b c Richard Susskind, From Bespoke to Commodity, LEGAL TECH. J., 2006, at 4, 4–7. [1]
  2. ^ Chris Johnson, Leveraging Technology to Deliver Legal Services, 23 HARV. J.L. & TECH.259, 279 (2009).
  3. ^ William Hornsby, Improving the Delivery of Affordable Legal Services Through the Internet, AMERICAN BAR ASS’N, June 10, 2009. [2]
  4. ^ http://www.authense.co.jp
  5. ^ http://www.bengo4.com
  6. ^ Catherine J Lanctot, Does LegalZoom have First Amendment Rights? Some Thoughts About Freedom of Speech and the Unauthorized Practice of Law, Villanova Univ. Sch. of L. Public Law & Legal Theory Working Paper No. 2011-07.
  7. ^ See Rule 5.4 of the Model Rules of Professional Conduct.
  8. ^ Krause, Jason (July 1, 2007). "Selling Law on an Open Market". ABA Journal. Retrieved October 4, 2010.  See also: American Bar Association Commission on Multidisciplinary Practices, Final Report, Appendix C, Reporter’s notes, July 2000
  9. ^ See Rule 5.4 of the District of Columbia Rules of Professional Conduct
  10. ^ a b ABA Commission on Ethics 20/20, Memorandum Re: For Comment: Issues Paper Concerning Alternative Business Structures, 17-19 (April 5, 2011)[3]
  11. ^ Model Code of Prof'l Conduct R. 5.5
  12. ^ Staphanie L. Kimbro, Regulatory Barriers to the Growth of Multijurisdictional Virtual Law Firms and Potential First Steps to Their Removal, 13 N.C.J.L. & TECH. ON. 165.
  13. ^ Charles L. Owen, Edward B. Pedwell, and Ronald W. Staudt, "Access to Justice: Meeting the Needs of Self-Represented Litigants," 2002, http://www.kentlaw.iit.edu/Documents/Institutes%20and%20Centers/CAJT/access-to-justice-meeting-the-needs.pdf
  14. ^ Berkman Center for Internet & Society at Harvard University, "Technology and Access to Justice," May 19, 2011, http://cyber.law.harvard.edu/node/6853
  15. ^ Richard Zorza, Access to Justice Blog, http://accesstojustice.net/
  16. ^ Dolin, Ron A. "Search Query Privacy: The Problem of Anonymization" Hastings Science & Technology Law Journal, 2010, p.137.
  17. ^ Restoring the Public Library Ethos: Copyright, E-Licensing, and the Future of Librarianship. William M. Cross. Law Library Journal Vol. 104:2 (2012).
  18. ^ BRIAN VICK, PRACTICE MANAGEMENT | PREDICTIVE CODING: E-DISCOVERY TECHNOLOGY IS NOT JUST FOR E-DISCOVERY ANYMORE (MAY 1, 2012) (http://www.ncbar.org/about/communications/nc-lawyer/2012-nc-lawyer-editions/may-2012/predictivecoding.aspx)
  19. ^ Darryl Mountain, XML E-Contracts: Documents that Describe Themselves, 11(3) INT’L J.L. & TECH. 274 (2003)
  20. ^ David Allen Larson, "Brother, Can You Spare A Dime?" Technology Can Reduce Dispute Resolution Costs When Times Are Tough and Improve Outcomes, 11 Nev. L.J. 523, 550 (2011)
  21. ^ A. Wyner, An Ontology in OWL for Legal Case-Based Reasoning. Artificial Intelligence and Law, 16: 361-387
  22. ^ K.D. Ashley, Reasoning with cases and hypotheticals in HYPO, Internat. J. Man-Machine Stud. 34 (6) (1991) 753-796
  23. ^ Vincent Aleven, Using Background knowledge in case-based legal reasoning: A computational model and an intelligent learning environment, Artificial Intelligences 150 (2003) 183-237.
  24. ^ a b c K.D. Ashley, Reasoning with cases and hypotheticals in HYPO, Internat. J. Man-Machine Stud. 34 (6) (1991) page 190
  25. ^ Kevin D. Ashley and Stefanie Bruninghaus, Computer Models for Legal Prediction, 46 Jurimetrics J. 309-352 (2006).
  26. ^ Kevin D. Ashley and Stefanie Bruninghaus, Computer Models for Legal Prediction, 46 Jurimetrics J. page 337 (2006).
  27. ^ Kevin D. Ashley and Stefanie Brninghaus, Computer Models for Legal Prediction, 46 Jurimetrics J. page 350
  28. ^ Theodore W. Ruger, Pauline T. Kim, Andrew D. Martin, & Kevin M. Quinn, “The Supreme Court Forecasting Project: Legal and Political Science Approaches to Predicting Supreme Court Decisionmaking” Columbia Law Review Volume 104 May 2004 (http://www.jstor.org/stable/10.2307/4099370)
  29. ^ Blakeley B. McShane, Oliver P. Watson, Tom Baker, and Sean J. Griffith “Predicting Securities Fraud Settlements and Amounts: A Hierarchical Bayesian Model of Federal Securities Class Action Lawsuits” Journal of Empirical Legal Studies Volume 9, Issue 3, 482-510 September 2012 (http://onlinelibrary.wiley.com/doi/10.1111/j.1740-1461.2012.01260.x/full)
  30. ^ https://lexmachina.com/
  31. ^ Peter W. Martin, "Digital Law: Some Speculations on the Future of Legal Information in Technology," http://www.law.cornell.edu/papers/fut95fnl.htm.
  32. ^ a b c d e f g Id.
  33. ^ See Stephen M. Bainbridge, The Case for Limited Shareholder Voting Rights, 53 UCLA L. Rev 601 (2005).