LEXPERT MAGAZINE
|
SEPTEMBER 2017 55
| ARTIFICIAL INTELLIGENCE |
worrying about overfitting? First, Darwin
likely approached his mathematical calcu-
lation predisposed to marriage. So too the
leaders of an acquiring company, generally
speaking, want to acquire the target, or a
target, and therefore, want the due dili-
gence to pan out. And secondly, as Chris-
tian and Griffiths write, "Every decision is
a kind of prediction … and every predic-
tion, crucially, involves thinking about two
distinct things: what you know and what
you don't. … A good theory, of course, will
do both. But the fact that every prediction
must in effect pull double duty creates a
certain unavoidable tension."
20
at tension sounds very much like the
M&A context, in which corporate lead-
ers are asking, 'Knowing what we know
based on due diligence, if we marry, will it
be a happy, qua prosperous, corporate mar-
riage? Will the pros outweigh the cons in
the future?' Aer all, cons revealed in due
diligence, namely defects, could be rem-
edied by new corporate leadership. And
pros can be eclipsed. Judgment still needs
to be exercised. Since computers are highly
susceptible to overfitting, human lawyers
would do well to take advantage of AI,
then reduce and curate the data into for-
ward-looking strategic advice.
"No two deals are alike and each merger
or acquisition depends on a multitude of
factors. Some of these factors will include
obvious elements such as company balance
sheets, employee compensation, share al-
location as well as specific factors related
to the IP, or assets in question. e entire
process is extremely detailed, laborious and
can run from months to years depending
on the size and complexity of a deal."
21
Let us return to Garry Kasparov as we
draw our conclusion: "Whilst machines
are taking over more parts of our lives,
and people say this is killing many jobs,
we have to realise this has been happening
for thousands of years. Machines replaced
farm animals, then manual labour, and
now they're taking over jobs from people
with college degrees and twitter accounts
— and everyone is making a big noise. Re-
placing manual labour allowed humanity
to concentrate on developing our minds,
and now, perhaps by taking over more me-
nial aspects of our cognition, machines will
help us to look for greater creativity, curios-
ity and happiness."
22
End Notes
1
Frederic Friedel, http://en.chessbase.com/post/kasparov-on-
the-future-of-artificial-intelligence
2
Julie Sobowale, http://www.abajournal.com/magazine/
article/how_artificial_intelligence_is_transforming_the_le-
gal_profession, p. 1.
3
Adolph, Gerald and Simon Gillies and Joerg Krings, "Strategic
Due Diligence: A Foundation for M&A Success" at https://www.
strategy-business.com/article/enews092806?gko=21dd3,
para. 1.
4
Outsell Company Analysis, "Advancing the Business of Data
& Information", April 27, 2017 AI Legal Tech conference paper.
5
https://www.legalrobot.com/
6
Pierre Mitchell, http://spendmatters.com/2017/01/10/
artificial-intelligence-contract-management-part-4-natural-
language-processing-machine-learning/
7
Ibid.
8
Ibid.
9
http://hls.harvard.edu/academics/curriculum/catalog/de-
fault.aspx?o=71516
10
http://www.rossintelligence.com/
11
Alston Ghafourifar https://venturebeat.com/2017/04/12/
will-ai-powered-robot-lawyers-still-use-cheesy-billboard-ads/
12
Zach Abramowitz, http://abovethelaw.com/2014/09/why-
diligence-sucks-why-you-suck-at-it-and-why-robots-want-your-
job/
13
For more on the voluminous contracts that need changing
with Brexit, see: https://www.ft.com/content/f1435a8e-372b-
11e7-bce4-9023f8c0fd2e.
14
Sobowale, Note 2, p. 1.
15
Sobowale, Note 2, p. 2.
16
Sobowale, Note 2, p. 2.
17
Christian, Brian and Tom Griffiths. Algorithms to Live By: The
Computer Science of Human Decisions (New York: Penguin,
2017), p. 150
18
Christian and Griffiths, Note 16, p. 151.
19
Christian and Griffiths, Note 16, p. 151.
20
Christian and Griffiths, Note 16, p. 152.
21
http://mergertechnology.com/security/artificial-intelligence-
merger-acquisition-due-diligence-3662.
22
Vikas Shah, at https://thoughteconomics.com/garry-kasp-
arov-interview/, para. 17.
Judith McKay, Chief Client and Innovation Officer at McCarthy Tétrault LLP, says,
"We are using AI tools to enhance our current M&A process at different levels in our work
flow, including due diligence. AI allows us to more quickly and efficiently gather data on a
target and perform advanced analysis. In the due diligence context, AI is increasing our
ability to quickly and accurately put together and verify disclosure schedules and identify
risks across a large data set."
David Kruse, partner at Blake, Cassels & Graydon LLP says that, as the academ-
ics suggest, "The sweet spot is large deals involving contract-intensive targets. Cost-
effectiveness will be optimized using AI when there are a large number of contracts to be
reviewed for standard considerations, such as term, assignability and change-of-control
consents. For example, due diligence on a target business with a large portfolio of leased
real estate would present an opportunity to achieve cost-effectiveness."
McKay continues, "One good example where AI is particularly useful is if a client is con-
sidering structuring an internal reorganization. We can very quickly look at all of their con-
tracts with third parties and determine which ones may be affected by the transaction."
New innovations around AI seem to be coming up all the time, and these Canadian in-
novators in the field do not sound afraid of the future (as others arguably do, see article).
According to Natalie Munroe, Head, Osler Works — Transactional, within Osler, Hoskin
& Harcourt LLP, "We have a team at OWT who are in the market every day looking at new
ways of deploying smart technology. That is our job: to be creative and curious in scan-
ning the landscape for new ways of doing things. We are working collaboratively and inten-
sively with our preferred vendors in order to customize new solutions for clients."
That said, law firms are very security-conscious. Kruse says: "We are eager to find inno-
vative and efficient solutions but cannot do so at the expense of quality or data security.
Data security is one area that is a particular challenge. The start-ups developing AI tools
have not always focused on security enough in their early stages to allow large law firms
and clients to be comfortable."
Munroe nods to the new lawyer and to new tech: "The creative use of technology is the
new stock in trade for a lawyer. Technology pre-packaged without smart users and en-
gaged clients is not a sustainable model and not the way we work at Osler. The weakness
in these sophisticated technologies is that they are not the 'plug and play' automated
solution some expect them to be. Knowledge of the software and how to apply it is key.
… The software augments the legal expertise, but at this stage, it cannot replace the
legal judgment that must be applied to complex issues."
Adds McKay, "The tools are fairly new and still being refined for use in the due diligence
context. We are engaged in constant dialogue to help shape these tools for our purposes.
It is an exciting time to work with them, but it is still early stages and they are not without
growing pains."
On the plus side for Canadian lawyers, as Kruse points out, "many of these tools are
being developed in the Toronto/Waterloo tech hubs. It is an added benefit to use innova-
tive tools developed locally. This allows us to speak directly with the innovators to help
shape the product to suit the needs of our clients." This includes the Thomson Reuters
Labs in Communitech, which works closely with the University of Waterloo (Thomson
Reuters publishes Lexpert).
Are AI tools actually
being used in Canadian
M&A due diligence?
