The Future of Legal
Technology
Kent Radford
Why It Matters
ABA Model Rule 1.1 Competence
A lawyer shall provide competent representation to a client.
Competent representation requires the legal knowledge, skill,
thoroughness and preparation reasonably necessary for the
representation.
Comment [8] To maintain the requisite knowledge and skill,
a lawyer should keep abreast of changes in the law and its
practice, including the benefits and risks associated with
relevant technology, engage in continuing study and
education and comply with all continuing legal education
requirements to which the lawyer is subject.
Why It Matters, cont.
• “The tools lawyers use to conduct research, review documents,
assemble documents, communicate with clients and invoice and
accept payment are inefficient.”
• “We do everything online, there’s no reason to think law will be the
exception.”
-- Forbes 8/12/2014
The Future
• Finding law
• Learning law
• Finding legal advice
• Making law
• Drafting legal documents
• Deciding/resolving disputes
• Predicting legal outcomes
• Compliance and enforcement
• Finding evidence
• Deepening the rule of law
Drafting Legal Documents
LegalZoom
• Founded in 2001 in California with a major office in Austin
• Provides forms for people to fill out
• Offers a subscription model for people seeking legal advice
• Over 1,000,000 users in 2011
• Received $266M in funding (7/24/11-1/7/2014)
Drafting Legal Documents
LegalZoom, cont.
Sample Texas Directive To Physicians and Family
or Surrogates of Jane Doe
“In fact, several lawyers … said they love LegalZoom because they get
paid for untangling all the mistakes people make using online DIY
legal forms.” National Review 8/1/2014
Predicting Legal Outcomes
Lex Machina
• Spinoff from Stanford’s Intellectual Property Litigation
Clearinghouse
• Analytics applied to IP–“money ball”
• $50,000 per year
• What it does
• How many times a patent has been asserted and how many
findings of infringement
• Which judge will hear your case
• Which lawyers do the best against non-practicing plaintiffs
• Which defendants are likely to sue other defendants
Predicting Legal Outcomes
Lex Machina, cont.
• $4.8 million Series A funding round led by Boston-based Cue Ball
Capital
• How they do it
• Gathered millions of pages of public available information from
2000 forward for a massive database
• Used machine learning and natural language search; took
specific legal terms and turned them into natural language
algorithms that classify documents into 10 categories in their
system (this is the secret sauce)
• Limitations
Finding Evidence
Technology + Services
Speed
• 1/3 Second Search
• 1/10 Second Document Navigation
• Lawyer Focused Design
• Got Data? 3.5 TB, 20,000,000 Unique Documents, 100,000,000
pages
• Translate from any language to English (Unicode compliant)
Processing
• Uncompress containers
• Search indexes
• Remove system files
• DB + file repository
• Extract text, metadata
• Ingest report
• OCR
• Time zone correction
• What affects speed?
• Duplicate detection
• Unusual filetypes
• Image everything upfront
• Preprocessed data
• Families + threads
Formats
Ingestion
Production
• Natives are always best
• EDRM + PDF
• 2nd best: DAT + OPT
• Concordance
• Do not preprocess
• SEC
• #1 source of problems is
bad load files
• Summation
• Natives only
• Exports to review
Roadmap
• Searchable logs and advanced statistics
• Self upload and ingest
• Multi-pass review, review stages
• Inconsistent tagging flags
• Browse
• Suggested tags (internal, across databases, with primary law)
• Spoliation detection
• Alerts using suggested tags against real-time data in place