In
a
previous
article
I
explored
how
Ethan
Mollick’s
insights
from
Co-Intelligence:
Living
and
Working
With
AI
about
how
the
equalization
of
skills
will
impact
legal.
In
today’s
post
I
will
examine
two
additional
Mollick
insights
that
are
equally
important
to
the
profession.
The
Role
of
Experts
Mollick
notes
in
his
book
that
AI
tools
have
the
capacity
to
create
enhanced
expertise
on
anything
and
everything
by
everyone
and
anyone.
This
dynamic
is
already
playing
out
in
legal
practice.
Want
to
be
an
expert
on
non
disclosure
agreements?
You
can
do
several
AI
prompts
and
get
much
of
what
you
need
to
know
to
get
by,
at
least
for
more
routine
questions.
Mollick
insists,
however,
that
expertise
in
most
fields
will
still
be
necessary
and
critical.
If
nothing
else,
there
needs
to
be
experts
to
determine
the
accuracy
and
completeness
of
AI
outputs,
to
catch
the
hallucinations,
to
see
when
an
output
is
simply
off
mark
or
not
relevant
to
the
situation.
To
apply
the
information
effectively.
Where
will
these
experts
come
from
when
AI
already
has
access
to
all
the
expertise
that
exists?
How
can
we
insure
a
pipeline
for
future
experts?
Mollick
believes
that
in
the
near
future,
experts
will
be
developed
in
new
and
different
ways.
AI
itself
will
play
a
role
in
developing
the
new
experts
of
the
world.
And
this
expert
development
challenge
is
particularly
acute
in
legal
practice,
where
traditional
training
methods
are
already
being
questioned.
The
Role
of
AI
In
Training
Historically,
the
guild
system
was
used
to
train
lawyers
and
help
them
become
experts.
The
system
works
like
this:
the
young
lawyer
graduates
from
law
school
and
goes
to
work
for
an
experienced
lawyer.
The
young
lawyer
potentially
sits
at
the
feet
of
the
experienced
lawyer
and
learns
through
observation
and
undertaking
assigned
tasks
under
the
experienced
lawyer’s
supervision.
By
seeing
and
experiencing
various
scenarios
and
undertaking
tasks
repeatedly,
the
young
lawyer
learns
to
engage
in
critical
thinking,
assess
strategy,
envision
the
outcomes
from
various
actions,
and
read
clients
and
situations.
The
young
lawyer
thus
gradually
obtains
the
wisdom—gut
instinct—of
the
older,
more
experienced
lawyer.
That
system
is
time
honored
but
time
consuming.
And
it
is
often
inconsistent
in
its
results.
Some
young
lawyers
work
for
good
mentors
and
teachers
and
advance.
Other
young
lawyers
who
might
have
the
same
raw
ability
do
not
and
flounder.
AI
disrupts
that
system.
Many
of
the
tasks
that
young
lawyers
historically
undertook
in
their
development
cycle
will,
in
the
future,
be
done
by
AI.
As
I
have
written
before,
they
will
no
longer
have
the
in
person
opportunity
to
learn
through
conversation
and
constructive
criticism.
But
if
Mollick
is
correct,
there
may
be
an
answer.
AI
itself
could
ultimately
become
the
mentor,
the
experienced
voice
in
the
room.
It
could
be
the
aid
and
assistant
to
help
the
young
lawyer
develop
the
very
skills
that
the
traditional
system
promoted.
This
would
involve
using
AI
tools
in
the
right
way:
not
merely
telling
the
young
lawyer
to
use
AI
to
get
the
answer,
but
giving
the
young
lawyer
a
problem
and
asking
the
lawyer
to
create
a
solution.
Only
then
would
AI
be
used
for
suggestions
to
improve
the
solution.
This
is
much
like
what
an
experienced
lawyer
does
now.
Some
Examples
For
example,
if
assigned
to
prepare
a
list
of
questions
for
a
deposition
of
a
corporate
representative,
one
option
would
be
for
the
young
lawyer
to
ask
a
large
language
model
for
the
questions,
which
would
produce
a
list
from
which
the
young
lawyer
could
select.
However,
this
does
not
necessarily
train
the
young
lawyer
to
identify
the
best
questions
for
any
given
situation.
A
more
effective
approach
would
be
for
the
young
lawyer
to
first
develop
the
list
of
questions
and
then
ask
the
AI
tool
for
a
critique,
provided
of
course
that
the
AI
tool
could
do
that.
And
this
way,
young
lawyers
could
differentiate
themselves
in
an
AI-driven
world
by
having
critical
thinking
skills
and
the
ability
to
apply
those
skills
to
human
relationships
and
differences.
As
Mollick
points
out,
the
AI
tools
are
not
yet
at
this
point.
However,
he
believes
they
soon
will
be.
The
urgency
of
addressing
these
training
challenges
becomes
clear
when
we
consider
Mollick’s
final
insight.
AI
Is
the
Worst
It
Will
Ever
Be
Mollick
encourages
us
to
assume
that
the
AI
we
have
today
will
be
the
worst
AI
we
ever
have.
In
other
words,
AI
will
develop
perhaps
exponentially,
but
certainly
over
time.
Mollick
says
we
cannot
envision
AI
and
what
it
will
be
tomorrow.
Indeed
just
think
how
far
we
have
come
since
the
GenAI
went
public
in
November
2022
and
how
far
its
come
in
the
last
year.
This
concept
too
has
implications
for
legal.
We
should
begin
thinking
now
about
the
possibility
of
AI
becoming
a
valued
coach
in
the
development
of
young
lawyers
and
their
skills.
We
should
be
planning
and
thinking
about
how
that
training
looks,
what
it
needs
to
involve,
and
what
the
results
and
measurables
will
be.
Otherwise,
we
will
be
left
with
lawyers
who
know
little
about
the
practice
of
law
other
than
to
prompt
AI
for
a
list
of
deposition
questions,
which
may
or
may
not
be
relevant
given
the
facts
of
any
case.
What
Does
this
Mean?
Lawyers
and
law
firms
need
to
be
aware
of
the
enormous
implications
of
AI
and
its
impact.
These
last
two
insights
along
with
the
idea
that
AI
will
equalize
skills
suggest
that
the
legal
profession
is
at
an
inflection
point.
The
lawyers
who
thrive
will
be
those
who
understand
that
AI
levels
the
playing
field,
that
expertise
still
matters
but
its
development
looks
different,
and
that
the
tools
we
have
today
are
only
just
the
beginning.
The
question
for
every
lawyer
and
law
firm
is:
Are
you
preparing
for
this
future,
or
still
hoping
it
won’t
arrive?
Stephen
Embry
is
a
lawyer,
speaker,
blogger,
and
writer.
He
publishes TechLaw
Crossroads,
a
blog
devoted
to
the
examination
of
the
tension
between
technology,
the
law,
and
the
practice
of
law.