Ontario Bar Association's TechXpo 2016

1. Big Data/Analytics for Small Firms
Omar Ha-Redeye
Nov. 8, 2016

2. The Big Data “Problem”
 Artificial Intelligence directly connected to big
data
 especially for predictive analytics
 Doesn’t mean that big data is useless for
lawyers
 it’s just not as robust as we would like for it to
be (yet)

3.  we have a scarcity of data in the legal
industry
 Smaller population -> less cases
 Less litigious society -> less lawsuits
 Less trials -> less written decisions
 See The Big Data Problem for AI in Law, Sept. 11, 2016:
http://www.slaw.ca/2016/09/11/the-big-data-problem-
for-ai-in-law/

4. Current Limitations in Legal
Data Analytics
 a rush to use Big Data can result in
‘overlooking a number of important
quantitative issues
 bias in data sample
 measurement error
 questions of statistical significance

5. Why is this a Problem?
 Data visualization can be an extremely
helpful tool to understand and
comprehend large amounts of data
 Concern of falsely visualizing patterns which don’t
actually exist
 without proper consideration Big Data can
be reduced to ‘quite useless or worse’
 Erroneous and misleading conclusions
 False cognitive biases that accepts small sample
sizes as a representation of the whole

6. The Proper Way to Deal with
Big Data in Law
 Solution: use a ‘confidence interval to gauge the
margin of error for any data sample and
subsequent value
 If Big Legal Data is used quantitatively, cannot be
done without use of inferential statistics
 Similar to legal argument without case law or rules of
precedent
 lacks meaningful point of reference, authority
 Even then, results should not be accepted without
further enquiry
 Robert J. Parnell,When Big Legal Data Isn’t Big Enough – Limitations in Legal Data Analytics, Sept. 26,
2016: https://settlementanalytics.com/2016/09/when-big-legal-data-isnt-big-enough-limitations-in-legal-
data-analytics/

7. How Do we Level Up?
 In civil litigation, where much of the research in AI is
being developed, the majority of the useful data is held
privately
 Information exists in silos and is not shared
 Governed by confidentiality agreements
 Protected as proprietary
 Not properly maintained or aggregated
 Either the information is shared, or 3rd party vendors
will aggregate with anonymization

8. Until Then, What is Big Data
Good For?
 Doing what we do now, just doing it better
 More efficiently
 More thoroughly
 More effectively
 Allows small and solo practices to research or prepare on
the same scale as larger firms
 Predictive analytics are still elusive
 Unlikely to feature in practice prominently any time soon

9. Contact
 omar@fleetstreetlaw.com
 @omarharedeye
 https://ca.linkedin.com/in/torontolawyer