Samsung shows we need an Apple approach to generative AI
It
feels
as
if
practically
everyone
has
been
using Open
AI’s ChatGPT
since
the
generative
AI
hit
prime
time.
But
many
enterprise
professionals
may
be
embracing
the
technology
without
considering
the
risk
of
these
large
language
models
(LLMs).
It
feels
as
if
practically
everyone
has
been
using Open
AI’s ChatGPT
since
the
generative
AI
hit
prime
time.
But
many
enterprise
professionals
may
be
embracing
the
technology
without
considering
the
risk
of
these
large
language
models
(LLMs).
That’s
why
we
need
an
Apple
approach
to
Generative
AI.
What
happens
at
Samsung
should
stay
at
Samsung
ChatGPT
seems
to
be
a
do-everything
tool,
capable
of
answering
questions,
finessing
prose,
generating
suggestions,
creating
reports,
and
more.
Developers
have
used
the
tool
to
help
them
write
or
improve
their
code
and
some
companies
(such
as
Microsoft)
are
weaving
this
machine
intelligence
into
existing
products,
web
browsers,
and
applications.
That’s
all
well
and
good.
But
any
enterprise
user
should
heed
the
warnings
from
the
likes
of
Europol
and
UK
intelligence
agency
NCSC
and
consider
the
small
print
before
committing
confidential
information.
Because
the
data,
once
shared,
is
no
longer
controlled
by
the
entity
that
shares
that
data,
but
by
OpenAI
—
meaning
confidential
information
is
no
longer
secure.
That
may
be
a
basic
privacy
issue
for
many
users,
but
for
companies,
particularly
those
handling
privileged
information,
it
means
using
ChatGPT
carries
serious
risks.
There
have
been
warnings
to
this
effect
in
circulation
since
the
software
appeared,
but
they’re
clearly
not
being
heard
over
the
pro-LLM
hype.
That’s
suggested
by
news
that
engineers
at
Samsung
Semiconductor
have
been
using
ChatGPT
and
in
doing
so
generated
three
leaks
of
sensitive
data
in
just
20
days.
Engineers
used
ChatGPT
to
fulfil
quite
straightforward
tasks:
-
Check
errors
in
source
code. -
Optimize
code
used
to
identify
defective
facilities. -
Transcribe
a
meeting
recorded
on
a
smartphone
to
create
meeting
minutes.
The
problem
is
that
in
all
these
cases,
the
employees
effectively
took
proprietary
Samsung
information
and
gave
it
to
a
third
party,
removing
it
from
control
of
the
company.
Naturally,
once
it
found
these
events
had
taken
place,
Samsung
warned
its
employees
about
the
risks
of
using
ChatGPT.
Its
vital
workers
understand
that
once
information
is
shared,
it
could
be
exposed
to
an
unknown
number
of
people.
Samsung
is
taking
steps
to
mitigate
against
such
use
in
the
future,
and
if
those
don’t
work
will
block
the
tool
from
use
on
its
network.
Samsung
is
also
developing
its
own
similar
tool
for
internal
use.
The
Samsung
incident
is
a
clear
demonstration
of
the
need
for
enterprise
leaders
to
understand
that
company
information
cannot
be
shared
this
way.
We
need
an
Apple
approach
to
Generative
AI
That,
of
course,
is
why
Apple’s
general
approach
to
AI
makes
so
much
sense.
While
there
are
exceptions
(including
at
one
time
the
egregious
sharing
of
data
for
grading
within
Siri),
Apple’s
tack
is
to
try
to
make
intelligent
solutions
that
require
very
little
data
to
run.
The
argument
is
that
if
Apple
and
its
systems
have
no
insight
into
a
user’s
information,
then
that
data
remains
confidential,
private,
and
secure.
It’s
a
solid
argument
that
should
by
rights
extent
to
generative
AI
and
potentially
any
form
of
search. Apple
doesn’t
seem
to
have
an
equivalent
to
ChatGPT,
though
it
does
have
some
of
the
building
blocks
upon
which
to
create
on-device
equivalents
of
the
tech
for
its
hardware.
Apple’s
incredibly
powerful
Neural
Engine,
for
example,
seems
to
have
the
horsepower
to
run
LLM
models
with
at
least
somewhat
equivalent
operations
on
the
device.
Doing
so
would
deliver
a
far
more
secure
tool.
Though
Apple
doesn’t
yet
have
its
own
Designed
In
Cupertino
take
on
Generative
AI
waiting
in
the
wings,
it’s
inevitable
that
as
the
risks
of
the
ChatGPT
model
become
more
widely
understood,
the
demand
for
private
and
secure
access
to
similar
tools
will
only
expand.
Enterprises
want
the
productivity
and
efficiency
without
the
expense
of
confidentiality.
The
future
of
such
tools
seems,
then,
likely
to
be
based
on
taking
such
solutions
as
much
as
possible
out
of
the
cloud
and
onto
the
device.
That’s
certainly
the
direction
of
travel
Microsoft
seems
to
be
signalling
as
it
works
to
weave
OpenAI
tools
within
Azure
and
other
products.
In
the
meantime,
anyone
using
LLMs
should
follow
the
advice
from
the
NCSC
and
ensure
they
don’t
include
sensitive
information
in
the
queries
they
make.
They
should
also
ensure
they
don’t
submit
queries
to
public
LLMs
that
“would
lead
to
issues
were
they
made
public.”
And,
given
that
humans
are
the
weak
link
to
every
security
chain,
most
businesses
probably
need
to
develop
an
action
plan
in
the
event
an
infringement
does
take
place.
Perhaps
ChatGPT
can
suggest
one?
Please
follow
me
on Mastodon,
or
join
me
in
the AppleHolic’s
bar
&
grill and Apple Discussions groups
on
MeWe.
About Author
