TLS0070 Introduction to Legal Technology

Lecture 5 Applications I: Information retrieval, knowledge management, e-discovery University of Turku Law School 2015-02-10 Anna Ronkainen @ronkaine anna.ronkainen@onomatics.com

First a little digression (guess why...)

Google Flu Trends -  predicting the timing and strength of

influenza epidemics based on the relative frequency of certain keywords in searches

-  values for the model in black (dotted lines 95% confidence intervals for predicted values), actual CDC influenza figures in red

But...

Performance after the initial period

Lessons worth learning (also for legal applications) -  transparency and replicability -  use big data for understanding the unknown -  study the algorithm -  it’s not just about the size of the data (from Lazer et al 2014)

Applications (general)

Application lectures overview Applications I (this week): -  information retrieval -  e-discovery (e-disclosure) -  knowledge management Applications II (next week, 1st half): -  case management -  online dispute resolution -  access to justice solutions Applications III (next week, 2nd half): -  decision support -  prediction -  automation -  self-service

Legal tech applications not covered here -  general-purpose applications (like Office®/

office software) -  legislative drafting applications -  docket management (and other applications

for use within the judiciary) -  courtroom visualization (etc.) software -  ... and probably a ton of other things I don’t

even know existed

Information retrieval

Information retrieval (IR) -  the granddaddy of legal tech applications -  the only form of legal tech available in all

(industrial) countries at least in some form - making different types of static legal content

available for human consumption -  statute law (+ commentaries) -  case law -  doctrine: journal articles and books

Information retrieval users -  types of users: -  lawyers in general -  subgroups of lawyers (e.g. IP lawyers) -  legal/admin support staff (e.g. tax

administrators, paralegals, informaticians) -  other non-law professionals -  ordinary citizens

-  different users have different needs in terms of -  type and quantity of content required -  terminology used -  user interface in general

First-generation information retrieval -  take whatever text you have (on paper) and

put it into a database -  full-text search (exact match or wildcards) -  structured search (in whatever fields are

available) -  Boolean search with AND, OR, NOT -  some metadata enhancements like keywords

(typically same as on paper)

Present-day Boolean search example: TMview

Further developments -  hypertext (links) -  better search capabilities with language

technology (try searching for “back” as a noun)

-  relevancy ranking -  recommendations for further reading - morebetter metadata

An example: WestlawNext -  natural-language and Boolean search -  relevancy ranking of sources of law, using

(among others) a network of links between cases

-  (commercial break, text version: http://info.legalsolutions.thomsonreuters.com/pdf/wln2/L-355700_v2.pdf)

On the horizon -  natural-language query interfaces and

advanced text understanding (think Watson/Siri)

- merging relevancy ranking with predictive legal analytics (like a certain trademark platform)

-  even more polarization between biggest markets (esp. US) and others (e.g. Finland, let alone developing countries)

Knowledge management

Knowledge management -  taking (and improving upon!) the knowledge

(explicit and tacit!) of an organization and putting it into optimal use

-  by no means just tech: creating and developing processes within the organization is equally important

-  can take different forms: -  internal: e.g. making work product (memos,

contracts etc.) electronically searchable -  external: creating digital legal content for use

by law firm customers

Knowledge management advantages -  higher efficiency -> better service -  higher quality (better dissemination of

expertise) -  makes life easier for lawyers (increased

productivity, reduced stress) -  keeps knowledge in the firm even if individuals

leave -  helps with the training of new lawyers -  necessary for good risk management (after Kay 2003)

One knowledge management example: contract management -  the default solution that’s still used by many

(most?) companies: paper + binders -  low overhead; manageable with low volumes -  doesn’t scale (cope with large volumes) well,

e.g. finding information becomes difficult -  particularly kludgy when documents needed

externally (due diligence, anyone?) -  error-prone and fragile -  still need to manage templates somewhere

(lack of central storage leads to inconsistencies)

Low-tech electronic contract management -  establish a central organization-wide repository for

signed contracts and official templates -  doesn’t need proprietary software, any LAN or

cloud based (private) file sharing solution works -  electronically searchable, at least if word processing

documents and scans are kept together -  works well (enough) if there are good processes

(e.g. regarding file naming and organization of files) and they are (always!) consistently adhered to

-  ...which this solution obviously cannot enforce -  no built-in workflow management

Dedicated contract lifecycle management (CLM) solutions -  hundreds of providers, including two from Finland (that I

know of: M-Files and Sopima) -  functionalities of varying sophistication for different stages

in the contract lifecycle: -  contract and clause template libraries -  platform and history for internal review -  platform and history for negotiations and external

review -  electronic signing / import of scanned definitive paper

originals -  archiving, retrieval etc. -  workflow management, managing access privileges etc.

Exhibit A: Sopima

Exhibit B: M-Files https://www.youtube.com/watch?v=0b0xSVHOFIg

Electronic signing -  real electronic signing not widespread

(outside Estonia, anyway), to a great deal due to a lack of standards internationally (and esp. for identifying legal persons)

-  pseudo-electronic signing (images manually written signatures stored electronically) now quite widespread, dedicated solutions and support in CLM systems also available

-  the latter raises some obvious questions about probative value

Heck, even Apple does it:

In summary: Levels of contract management adoption

(via Juntunen 2013)

Another knowledge management example: Fondia’s Virtual Lawyer

Fondia’s Virtual Lawyer -  a collection of ~1700 short documents made

by Fondia staff describing the legal aspects of particular situations

-  for external use (self-help by Fondia clients etc.), AFAIK also used internally in an enhanced version

-  not for total novices -  available at virtuallawyer.fi for free,

registration required, document template library additionally available for a fee

Electronic discovery (disclosure)

Discovery in electronically stored information (e-discovery) -  emerged out of nowhere a dozen years ago -  now a multi-billion-dollar industry (mostly US),

hundreds of providers -  roots in more general-purpose language tech

(outside the AI & law community) -  Enron corpus, Sedona Conference, TREC, DESI -  storage requirements for e-mail etc. introduced

(US) by amendments to Federal Rules of Civil Procedure in 2006

...and now* it’s already this much widespread (in the US, anyway):

*: actually this book is from 2009

Zubulake v. UBS Warburg -  employment law case in District Court for

Southern NY, heard 2003–2005 -  led to four groundbreaking rulings which set

the basic standards for e-discovery (before 2006 FRCP revisions), widely referred to as Zubulake I, III, IV, V

Zubulake I and III -  what data is considered accessible ESI

-  yes: online data/hard disks, optical disks, offline magnetic tapes -  no: backup tapes, damaged/deleted/... data

-  no -> yes if considerable evidentiary value can be demonstrated, for which a 7-factor test was introduced: -  The extent to which the request is specifically tailored to discover

relevant information; -  The availability of such information from other sources; -  The total cost of production, compared to the amount in

controversy; -  The total cost of production, compared to the resources available to

each party; -  The relative ability of each party to control costs and its incentive to

do so; -  The importance of the issues at stake in the litigation; and -  The relative benefits to the parties of obtaining the information.

Zubulake IV -  some backups no longer available -  relevant emails (created after the start of the

proceedings) had been deleted -  defendant had a duty to preserve evidence

(since relevant for ongoing/future litigation) -  plaintiff got access to the information -  however, plaintiff couldn’t show adverse

interference (at this stage) and was ordered to pay the costs

Zubulake V -  upon the plaintiff’s motion, the court

concluded that the defendant (and defence counsel) had failed to safeguard and produce evidence in an adequate manner

-  defendant sanctioned and ordered to pay plaintiff’s costs for producing evidence (witness re-examination etc.) necessary due to plaintiff’s late (or non-)production of relevant evidence

Outcome -  active interference (intentional destruction

or hiding of evidence) ruled by the judge -  jury found in favour of the plaintiff,

compensatory and punitive damages -  reimbursement of even more costs to the

plaintiff (generally a lot more unusual in US)

E-discovery workflow -  establish an ESI retention policy, stick to it when

creating and storing data -  identify relevant ESI, create authentic snapshot and

collect it for further processing -  process and filter ESI (e.g. removal of duplicates) -  review and analyze ESI for privileged information -  produce ESI after filtering out irrelevant, duplicated

or privileged materials -  possibly clawback if too much produced in error -  present at trial (if it ever goes that far)

First-generation e-discovery -  based on lists of specific search terms (or

phrases) proposed by the plaintiff and approved or modified by the judge

-  a bit sketchy, not even real consensus about whether keywords cover all inflections?

-  no longer considered acceptable by many of the most influential US judges for this field

Predictive coding -  based on coding a (very) small subset of the

relevant document mass as responsive or not (should/n’t be released)

-  then using that as the teaching set for a machine learning algorithm

-  performance comparable to (or better than) human reviewers at a fraction of the cost

E-discovery output -  native (original) formats (e.g.: .docx) -  usually better for the plaintiff: electronically

searchable -  native file formats for proprietary software not

necessarily openable without that software -  “petrified” formats (tiff, pdf) -  often better for the defendant: almost the same

as handing out the data on paper -  general-purpose tools enough for viewing -  easier to redact

What’s the status with e-discovery -  very widespread in the US (because it’s the

law!) -  gaining popularity in the rest of Anglophonia

(because common law; tech readily available for English)

-  some providers also support major European and Asian languages (mostly for international companies operating in the US)

-  rest of the world: is there even a word for this? (then again: discovery in the common-law sense doesn’t exist in most civil-law countries (incl. Finland) in general)

No concrete examples -  (because, frankly, I understand neither the field

nor the legal issue well enough) -  but e-discovery in itself is an interesting

example of legal tech for many reasons -  first real big data application for law -  came out of nowhere in the early 2000s -  now a multi-billion-dollar industry (US) -  many startups, some notable exits (e.g.

Cataphora’s e-discovery ops to EY) -  also continuously new funding rounds (even

$100M+) to more and more companies

Questions?