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Introduction to Legal Technology, lecture 5 (2015)


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Slides for lecture 5 of the course Introduction to Legal Technology at the University of Turku Law School, presented Feb 10 2015.

This lecture is the first of three lectures on specific legal technology applications: information retrieval, knowledge management, and e-discovery.

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Introduction to Legal Technology, lecture 5 (2015)

  1. 1. 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
  2. 2. First a little digression (guess why...)
  3. 3. 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
  4. 4. But...
  5. 5. Performance after the initial period
  6. 6. 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)
  7. 7. Applications (general)
  8. 8. 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
  9. 9. 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
  10. 10. Information retrieval
  11. 11. 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
  12. 12. 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
  13. 13. 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)
  14. 14. Present-day Boolean search example: TMview
  15. 15. 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
  16. 16. 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:
  17. 17. 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)
  18. 18. Knowledge management
  19. 19. 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
  20. 20. 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)
  21. 21. 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)
  22. 22. 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
  23. 23. 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.
  24. 24. Exhibit A: Sopima
  25. 25. Exhibit B: M-Files
  26. 26. 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
  27. 27. Heck, even Apple does it:
  28. 28. In summary: Levels of contract management adoption (via Juntunen 2013)
  29. 29. Another knowledge management example: Fondia’s Virtual Lawyer
  30. 30. 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 for free, registration required, document template library additionally available for a fee
  31. 31. Electronic discovery (disclosure)
  32. 32. 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
  33. 33. ...and now* it’s already this much widespread (in the US, anyway): *: actually this book is from 2009
  34. 34. 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
  35. 35. 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.
  36. 36. 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
  37. 37. 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
  38. 38. 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)
  39. 39. 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)
  40. 40. 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
  41. 41. 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
  42. 42. 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
  43. 43. 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)
  44. 44. 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
  45. 45. Questions?