I Know the Answer But I Don’t Know Why: Practicing Law in the Age of Machine Intelligence

Evolve Law – Bridging the Technology Gap in LawBenjamin SnipesMarch 14, 2017

DRAFT

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Marco Polo, Google and Bayesian Statistics

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What is Machine Intelligence? It Primarily Uses These Technologies for Legal Purposes

• Machine Learning, that uses feedback mechanisms and statistics in order to improve recall and precision in response to questions• Natural Language Parsing, allows

machines to interpret human grammer• Natural Language Understanding,

allows machines to interpret and relate language based on semantics

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How Can Machine Intelligence be Use in Law to Improve Accuracy and Efficiency?

• In a legal context, Machine Intelligence uses various computing techniques in order to:• Suggest a likely further explanation or

question for the question being asked• Provide information likely to help a

lawyer, librarian or paralegal make a decision

• Provide the most likely answer

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Two Key Limits:

• Lawyers must be able to understand and explain answers in order to support a legal opinion

• Extent the logic and empathy of legal answers are fully quantifiable

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Model Rules of Professional ConductMPRC Rule 1.1 Comments Thoroughness and Preparation [5]  Competent handling of a particular matter includes inquiry into and analysis of the factual and legal elements of the problem, and use of methods and procedures meeting the standards of competent practitioners. … [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… From <http://www.americanbar.org/groups/professional_responsibility/publications/model_rules_of_professional_conduct/rule_1_1_competence/comment_on_rule_1_1.html>

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Machine Intelligence Invokes Algorithms

Company profile and key figures

Before Machine Intelligence

After Machine Intelligence

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GUILTY

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Statistical Sampling and Machine Intelligence in Document Review

• Starting in 2004, rather than requiring lawyers to review each and every document possibly produced by a defendant, in order to constrain discovery costs, courts began to accept the statistical results of document review

• Humans must still interpret the results

1 See, Zubukake v. UBS Warburg, 229 F.R.D. 422 (S.D.N.Y. 2004) (i.e. “Zubulake V”)

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Statistical Sampling and Machine Intelligence in Document Review – Key Question

• Will the conclusion of a machine as to whether a given set of documents are legally relevant ever be accepted?

• How far down this path will we go where we trust the algorithms to reach legal conclusions?

• How will this precedent apply to all other areas of law?

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Conclusions• Law firms and legal departments will be

pressured to use Machine Learning technologies to drive insight and efficiency

• However, to what extent lawyers may be able to use these technologies will depends whether they are an acceptable standard of practice

• In the meantime, vendors of these technologies must deploy them in a way lawyers can understand and audit them or else these tools will be relegated to finding aids