Ed.
note:
This
is
the
latest
in
the
article
series, Cybersecurity:
Tips
From
the
Trenches, by
our
friends
at Sensei
Enterprises,
a
boutique
provider
of
IT,
cybersecurity,
and
digital
forensics
services.
Lawyers
have
long
known
that
expert
testimony
can
make
or
break
a
case.
Whether
the
issue
concerns damages,
causation,
medical
matters,
engineering
analysis,
or
economic
modeling,
experts
provide
the
specialized
knowledge
courts
rely
on.
Artificial
intelligence (AI) has
now
entered
this
space,
not
as
a
replacement
for
experts
but
as
a
tool reshaping how
expert
testimony
is
analyzed,
prepared,
and
challenged.
To
be
clear,
no
AI
system
is
about
to
take
the
stand.
What
AI
can
do,
and
already
does,
is
change
the
mechanics
of
how
expert
evidence
is
reviewed
and
tested.
Used
thoughtfully,
AI
offers
real
strategic
advantages.
Used
carelessly,
it
can
undermine
credibility
and,
in
some
cases,
lead
to
the
exclusion
of
critical
testimony.
What
we
are
seeing
is
not
an
AI
takeover
of
expert
witnesses,
but
a supplemental model in
which lawyers
and
experts
use
AI
to
amplify
insight
and
scrutiny.
AI
as
a
Litigation
Multiplier
One
of
the
most
powerful
uses
of
AI
in
expert
work
is
large-scale
review.
Expert
reports,
deposition
transcripts,
prior
testimony,
data
tables,
and
technical
literature
can
now
be
analyzed
at
a
scale
no
human
team
could
reasonably
manage.
AI
tools
can
flag
internal
inconsistencies,
identify
conflicts
with
prior
opinions,
and
surface
alternative
explanations
that
might
otherwise
go
unnoticed.
This
changes
the
dynamic
in
the
war
room.
Instead
of
spending
countless
hours
on
review,
lawyers
can
focus
on
interpretation,
judgment,
and
strategy.
AI
does
all
the
heavy
lifting,
and lawyers
can
decide
what
matters.
Sharpening the
Edge
on Cross-Examination
AI
is
also
being
used
to
simulate
adversarial
questioning.
By
feeding
an
expert’s
report
and
prior
statements
into
a
model
configured
to
challenge
assumptions
and
probe
weaknesses,
lawyers
can pressure-test testimony
before
it
ever
reaches
the
courtroom.
This
does
not
replace
traditional
mock
examinations.
It
enhances
them.
Experts
can
refine
responses,
anticipate
lines
of
attack,
and
identify
weak
points
early.
On
the
flip
side,
lawyers
challenging
opposing
experts
can
use
AI
to
synthesize
prior
testimony
and technical
literature
into
focused
lines
of cross-examination that
expose
contradictions
or
unsupported
assumptions.
Translation,
Accessibility,
and
Persuasion
Expert
testimony
often
fails
not
because
it
is
wrong,
but
because
it
is
incomprehensible.
AI
can
help
translate
dense
technical
analysis
into
language that judges
and
juries
can understand.
Used
properly,
AI
can
help
recast
complex
engineering
conclusions
into
practical
explanations,
distill
economic
models
into
plain
language,
and
highlight
the
core
takeaways
without
distorting
substance.
This
is
not
about
dumbing
things
down.
It
is
about
effective
communication.
Lawyers
who
can
present
expert
findings
clearly
and
persuasively
will
always
have
an
advantage
over
those
who
bury
the
factfinder
in
technical
jargon.
Hallucinations
and
Overreliance
Are
Real
Risks
The
risks
of
AI
use
are
not
hypothetical.
Courts
have
already
rejected
expert
submissions
that
included
AI-generated
citations
or
analyses
that
did
not
exist.
In
those
cases,
the
very
tool
meant
to
improve
efficiency
became
a
source
of
false
information
because
it
was
not
adequately
supervised.
This
is
a
cautionary
tale
every
litigator
should
internalize.
AI
can
generate
content
that
looks
plausible
but
is
not
real.
A
human
must
still
verify
every
citation,
dataset,
and
conclusion.
The
duty
to
ensure
accuracy
has
not
changed.
Ethics
and
Best
Practices
AI
is
not
a
magic
solution.
Responsible
use
in
expert
work
requires
structure
and
discipline.
Lawyers
should
clearly
document
how
AI
tools
were
used
in preparation or
review
of expert
testimony.
Experts
should
receive
guidance
on
avoiding hallucinogenic content
and
ensuring
that
all
conclusions
are
independently
validated.
Confidential
data
must
be
protected,
and
sensitive
material
should
not
be
fed
into
tools
that
lack
appropriate
safeguards.
Transparency
also
matters.
As
courts
become
more
familiar
with
AI,
judges
may
expect
disclosure
when
AI
plays
a
meaningful
role
in
expert
analysis.
That
expectation
is
not
about
discouraging the
use
of
AI.
It
is
about
maintaining
trust
in
the
reliability
of
evidence.
The
Bottom
Line
AI
is
not
replacing
expert
witnesses,
but
it
is
transforming
how expert testimony
is
handled
in
litigation.
Lawyers
who
use
AI
thoughtfully
can
review
more
material,
prepare
more
effectively,
and
present
complex
ideas
more
clearly.
Those
who
ignore
it
risk
falling
behind.
Those
who
misuse
it
risk
harming
their
cases and
their
credibility.
At
its
best,
AI
turns
overwhelming
volumes
of
information
into
actionable
insight.
At
its
worst,
it
turns
fiction
into
fact.
The
difference
is
human
oversight,
and
that
responsibility
still
rests
squarely
with
the
lawyer
Michael
C.
Maschke
is
the
President
and
Chief
Executive
Officer
of
Sensei
Enterprises,
Inc.
Mr.
Maschke
is
an
EnCase
Certified
Examiner
(EnCE),
a
Certified
Computer
Examiner
(CCE
#744),
an
AccessData
Certified
Examiner
(ACE),
a
Certified
Ethical
Hacker
(CEH),
and
a
Certified
Information
Systems
Security
Professional
(CISSP).
He
is
a
frequent
speaker
on
IT,
cybersecurity,
and
digital
forensics,
and
he
has
co-authored
14
books
published
by
the
American
Bar
Association.
He
can
be
reached
at [email protected].
Sharon
D.
Nelson
is
the
co-founder
of
and
consultant
to
Sensei
Enterprises,
Inc.
She
is
a
past
president
of
the
Virginia
State
Bar,
the
Fairfax
Bar
Association,
and
the
Fairfax
Law
Foundation.
She
is
a
co-author
of
18
books
published
by
the
ABA.
She
can
be
reached
at [email protected].
John
W.
Simek
is
the
co-founder
of
and
consultant
to
Sensei
Enterprises,
Inc.
He
holds
multiple
technical
certifications
and
is
a
nationally
known
digital
forensics
expert.
He
is
a
co-author
of
18
books
published
by
the
American
Bar
Association.
He
can
be
reached
at [email protected].