Legal Informatics – Cambridge University Press (2021)

We are very pleased to announce pre-orders for “Legal Informatics” (Cambridge University Press – (Coming in early 2021) are now available on Amazon / Cambridge. Our book is designed to be an introduction to the academic discipline underlying the economic and technological transformation of the legal industry. Legal Informatics features contributions from more than two dozen academic and industry experts, chapters cover the history and principles of legal informatics and background technical concepts – including natural language processing and distributed ledger technology. The volume also presents real-world case studies that offer important insights into document review, due diligence, compliance, case prediction, billing, negotiation and settlement, contracting, patent management, legal research, and online dispute resolution. It is hardbound book ~600 pages in length.

#LegalInformatics #LegalTech #LegalInnovation #MachineLearning #NetworkScience #NLP #LegalScience

Complex Societies and the Growth of the Law – Published Today in Scientific Reports (Nature Research)

Access the Full Article via Scientific Reports (Nature Research). This article is part of a special compilation for Scientific Reports devoted to Social Physics.

ABSTRACT: While many informal factors influence how people interact, modern societies rely upon law as a primary mechanism to formally control human behaviour. How legal rules impact societal development depends on the interplay between two types of actors: the people who create the rules and the people to which the rules potentially apply. We hypothesise that an increasingly diverse and interconnected society might create increasingly diverse and interconnected rules, and assert that legal networks provide a useful lens through which to observe the interaction between law and society. To evaluate these propositions, we present a novel and generalizable model of statutory materials as multidimensional, time-evolving document networks. Applying this model to the federal legislation of the United States and Germany, we find impressive expansion in the size and complexity of laws over the past two and a half decades. We investigate the sources of this development using methods from network science and natural language processing. To allow for cross-country comparisons over time, based on the explicit cross-references between legal rules, we algorithmically reorganise the legislative materials of the United States and Germany into cluster families that reflect legal topics. This reorganisation reveals that the main driver behind the growth of the law in both jurisdictions is the expansion of the welfare state, backed by an expansion of the tax state. Hence, our findings highlight the power of document network analysis for understanding the evolution of law and its relationship with society.

It has been a real pleasure to work with my transatlantic colleagues Corinna Coupette (Max Planck Institute for Informatics), Janis Beckedorf (Heidelberg University) and Dirk Hartung (Bucerius Law School). We have other projects also in the works — so stay tuned!

Back to Future in Legal Artificial Intelligence — Expert Systems, Data Science and the Need for Peer Reviewed Technical Scholarship

In the broader field of Artificial Intelligence (A.I.) there is a major divide between Data Driven A.I. and Rules Based A.I.  Of course, it is possible to combine these approaches but let’s keep it separate and easy for now.  Rules Based AI in the form of expert systems peaked in the late 1980’s and culminated in the last AI Winter.  Absent a few commercial examples such as TurboTax, the world moved on and Data Driven A.I. took hold.

But here in #LegalTech #LawTech #LegalAI #LegalAcademy – it seems more and more like we have gone ‘Back to the A.I. Future’ (and brought an IF-THEN back in the Delorean).  As even in 2020, we see individuals and companies touting themselves for taking us Back to the A.I. Future.

There is nothing wrong with Expert Systems or Rules Based AI per se.  In law, the first expert system was created by Richard Susskind and Phillip Capper in the 1980’s.  Richard discussed this back at ReInventLaw NYC in 2014.    There are a some use cases where Legal Expert Systems (Rules Based AI) are appropriate.  For example, it makes the most sense in the A2J context.  Indeed, offerings such as A2J Author and Docassemble are good examples. However, for many (most) problems (particularly those with a decent level of complexity) such rule based methods alone are really not appropriate.  

Data Science — mostly leveraging methods from Machine Learning (including Deep Learning) as well as Natural Language Processing (NLP) and other computational allied methods (Network Science, etc.) are the modern coin of the realm (both in the commercial and academic spheres).

As the image above highlights, the broader A.I. world faces challenges associated with overhyped AI and faux expertise. #LegalAI also faces the problem of individuals and companies passing themselves off as “cutting edge AI experts” or “offering cutting edge AI products” without an academic record or codebase to their name. 

In the academy,  we judge scholars on academic papers published in appropriate outlets.  In order for someone to be genuinely considered an {A.I. and Law Scholar, Computational Law Expert, NLP and Law Researcher} that scholar should publish papers in technically oriented Peer Reviewed journals (*not* Law Reviews or trade publications alone).  In the Engineering or Computer Science side of the equation, it is possible to substitute a codebase (such as a major Python package or contribution) for peer reviewed papers.  In order for this field to be taken seriously within the broader academy (particularly by technical inclined faculty), we need more Peer Reviewed Technical Publications and more Codebases. If we do not take ourselves seriously – how can we expect others to do so.

On the commercial side, we need more objectively verifiable technology offerings that are not in line with Andriy Burkov’s picture as shown above … this is one of the reasons that we Open Sourced the core version of ContraxSuite / LexNLP.

NLLP Workshop 2020 — Legal Text Analysis Session — Video of Natural Legal Language Processing Workshop is Now on YouTube

NLLP Workshop 2020 Session 1: Legal Text Analysis — Video of Natural Legal Language Processing Workshop is Now on YouTube.  

Unfortunately, I was not available to participate as I was teaching class at the time of the workshop. However, Corinna Coupette and Dirk Hartung represented us well !  

Copy of the paper presented is available here —
SSRN LINKhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3602098
arXiv LINKhttps://arxiv.org/abs/2005.07646

2nd Workshop on Natural Legal Language Processing (NLLP) – Co-Located at the broader 2020 KDD Virtual Conference

Today is the 2nd Workshop on Natural Legal Language Processing (NLLP) which is co-located at the broader 2020 KDD Virtual Conference. Corinna Coupette is presenting our paper ‘Complex Societies and the Growth of the Law’ as a Non-Archival Paper. NLLP is a strong scientific workshop (I did one the Keynote Addresses last year and found it to be a very good group of scholars and industry experts). More information is located here.

LexPredict Launches New User Interface for ContraxSuite

Our LexPredict Team is excited to announce the new ContraxSuite User Interface – See Press Release < HERE >

ContraxSuite has a wide range of user types across our various legal service delivery customers. Relevant users include legal data scientists, power users in legal information technology, professional review teams at legal process outsourcers, contract review units in corporate legal departments, as well as associates and partners in law firms. While the existing ContraxSuite user interface will still serve as the interface for our data scientist community, the new UI is designed to serve the needs of a much broader community of users.

Eric Detterman – VP and Global Head of Products and Solution Engineering at LexPredict noted, “The new ContraxSuite User Interface delivers the bells and whistles that many users expect from a modern app or software tool, including dynamic menus, helpful dialog boxes, and an easy, intuitive design.”   

Blockchain, Cryptocurrency + Law Course – ( Professor Nelson Rosario + Professor Daniel Martin Katz )


Next semester – I am looking forward to teaching Blockchain, Cryptocurrency + Law with CK alum 
Nelson Rosario – there is real demand for this class among our students – the class was full before registration was even complete — we have 50 students taking the class and had to turn away a number of students … #LegalTech #Blockchain #LegalInnovation #Hashtag 

Revisiting Distance Measures for Dynamic Citation Networks – Published in Physica A


I was revisiting some of our old stuff for this Oslo event -early on for us on our #LegalPhysics #LegalAnalytics path – published in Physica A – “By applying our sink clustering method, we obtain a dendrogram of the network’s largest weakly connected component shown in Fig. 4. However, despite their general topical relatedness, these two clusters of cases engage substantively different sub-questions, and are thus appropriately divided into separate clusters. While not a major focus of the docket of the modern court, the early court elaborated a number of important legal concepts through the lens of these admiralty decisions. For example, the red group of cases engages questions of presidential power and the laws of war, as well as general interpretations of the Prize Acts of 1812. Meanwhile, the blue cluster engages questions surrounding tort liability, jurisdiction, and the burden of proof.”