Los Angeles is using AI in a pilot program to try to predict homelessness and allocate aid

In
December
of
last
year,
single
mom
Courtney
Peterson
was
laid
off
from
her
job
working
for
a
now-shuttered
inpatient
transitional
living
program.
Aside
from
giving
her
the
ability
to
bring
her
7-year-old
son
to
work,
the
job
also
paid
enough
to
cover
rent
in
a
studio
apartment
in
the
Van
Nuys
neighborhood
in
Los
Angeles,
where
they
had
lived
for
a
year
and
a
half. 

After
she
was
laid
off,
Peterson
said
she
grew
immediately
concerned
about
making
January’s
rent
and
began
researching
potential
avenues
for
help. When
her
son
was
an
infant,
they
lived
in
a
travel
trailer,
she
said,
a
situation
she
did
not
want
to
return
to.

“I
started
to
reach
out
to
local
churches
or
places
that
said
they
offered
rent
assistance,”
Peterson
told
CNBC. “But
a
lot
of
them
wanted
me
to
have
active
eviction
notices
in
order
to
give
me
assistance.
I
felt
like
I
was
running
out
of
options.
I’d
reached
out
to
pretty
much
everyone
I
could
possibly
think
of
with
no
luck.”

Instead
of
an
eviction
notice,
Peterson
received
a
letter
from
the
Homelessness
Prevention
Unit
within
the
Los
Angeles
County
Department
of
Health
Services,
offering
a
lifeline.
The
pilot
program
uses
predictive
artificial
intelligence
to
identify
individuals
and
families
at
risk
of
becoming
homeless,
offering
aid
to
help
them
get
stabilized
and
remain
housed.

In
2023,
California
had
more
than
181,000
homeless
individuals,
up
more
than
30
percent
since
2007,
according
to
data
from
the
Department
of
Housing
and
Urban
Development.
A
report
from
the
California
State
Auditor’s
Office
found
that
the
state
spent
$24
billion
on
homelessness
from
2018
through
2023.

Launched
in
2021,
the
program
has
helped
the
department
serve
nearly
800
individuals
and
families
at
risk
of
becoming
homeless,
with
86
percent
of
participants
retaining
permanent
housing
when
they
leave,
according
to
Dana
Vanderford,
associate
director
of
homelessness
prevention
at
the
county’s
Department
of
Health
Services. 

Individuals
and
families
have
access
to
between
$4,000
and
$8,000,
she
said,
with
the
majority
of
the
funding
for
the
program
coming
from
the
American
Rescue
Plan
Act.
Tracking
individuals
down
to
help
and
convincing
them
that
the
offer
is
real
and
not
a
scam
can
be
a
challenge,
but
once
contact
is
established,
aid
is
quickly
put
into
motion.

“We
often
meet
our
clients
within
days
of
a
loss
of
housing,
or
days
after
they’ve
had
a
medical
emergency.
The
timing
with
which
we
meet
people
feels
critical,”
Vanderford
said. “Our
ability
to
appear
out
of
nowhere,
cold-call
a
person,
provide
them
with
resources
and
prevent
that
imminent
loss
of
housing
for
86
percent
of
the
people
that
we’ve
worked
with
feels
remarkable.”

Peterson
said
she
and
her
son
received
some
$8,000
to
cover
rent,
utilities
and
basic
needs,
allowing
her
to
stay
put
in
her
apartment
while
she
looks
for
a
new
job.
The
program
works
with
clients
for
four
months
and
then
follows
up
with
them
at
the
six-month
mark
and
the
12-month
mark,
as
well
as
18
months
after
discharge.
Caseworkers
like
Amber
Lung,
who
helped
Peterson,
say
they
can
see
how
important
preventive
work
is
firsthand.

“Once
folks
do
lose
that
housing,
it
feels
like
there’s
so
many
more
hurdles
to
get
back
to
[being]
housed,
and
so
if
we
can
fill
in
just
a
little
bit
of
a
gap
there
might
be
to
help
them
retain
that
housing,
I
think
it’s
much
easier
to
stabilize
things
than
if
folks
end
up
in
a
shelter
or
on
the
streets
to
get
them
back
into
that
position,”
Lung
said.

The
AI
model
was
developed
by
the
California
Policy
Lab
at
UCLA
over
the
course
of
several
years,
using
data
provided
by
Los
Angeles
County’s
Chief
Information
Office,
or
CIO.
The
CIO
integrated
data
from
seven
different
county
departments,
de-identified
for
privacy,
including
emergency
room
visits,
behavioral
health
care
and
large
public
benefits
programs
from
food
stamps
to
income
support
and
homeless
services,
according
to
Janey
Rountree,
executive
director
of
the
California
Policy
Lab.
The
program
also
pulled
data
from
the
criminal
justice
system.

That
data,
linked
together
over
many
years,
are
what
would
be
used
to
make
predictions
about
who
would
go
on
to
experience
homelessness.

Once
the
model
identified
patterns
in
who
experienced
homelessness,
the
lab
used
it
to
attempt
to
make
predictions
about
the
future,
creating
an
anonymized
list
of
individuals
ranked
from
highest
risk
to
lowest.
The
lab
provided
the
list
to
the
county
so
it
could
reach
out
to
people
who
may
be
at
risk
of
losing
housing
before
it
happened.

However,

past
research
has
found
that
anonymized
data
can
be
traced
back
to
individuals
based
on
demographic
information.
A
sweeping
study
on
data
privacy,
based
on
1990
U.S.
Census
data,
found
that
87%
of
Americans
could
be
identified
using
ZIP
code,
birth
date
and
gender.

“We
have
a
deep,
multi-decade
long
housing
shortage
in
California,
and
the
cost
of
housing
is
going
up,
increasingly,
and
that
is
the
cause
of
our
people
experiencing
homelessness,”
Rountree
said. “The
biggest
misperception
is
that
homelessness
is
caused
by
individual
risk
factors,
when
in
fact
it’s
very
clear
that
the
root
cause
of
this
is
a
structural
economic
issue.”

The
Policy
Lab
provided
the
software
to
the
county
for
free,
Rountree
said,
and
does
not
plan
to
monetize
it.
Using
AI
in
close
partnership
with
people
who
have
relevant
subject-matter
expertise
—
from
teachers
to
social
workers
—
can
help
to
promote
positive
social
outcomes,
she
said. 

“I
just
want
to
emphasize
how
important
it
is
for
every
community
experiencing
homelessness,
to
test
and
innovate
around
prevention,”
she
said. “It’s
a
relatively
new
strategy
in
the
lifespan
of
homeless
services.
We
need
more
evidence.
We
need
to
do
more
experiments
around
how
to
find
people
at
risk.
I
think
this
is
just
one
way
to
do
that.”

The
National
Alliance
to
End
Homelessness
found
in
2017
that
a
chronically
homeless
person
costs
the
taxpayer
an
average
of
$35,578
per
year,
and
those
costs
are
reduced
by
an
average
of
nearly
half
when
they
are
placed
in
supportive
housing.

Los
Angeles
County
has
had
initial
conversations
with
Santa
Clara
County
about
the
program,
and
San
Diego
County
is
also
exploring
a
similar
approach,
Vanderford
said.

AI
in
the
hands
of
government
agencies
has
faced
scrutiny
due
to
potential
outcomes.
Police
reliance
on
AI
technology
has
led
to

wrongful
arrests,
and,
in
California,
voters
rejected
a
plan
to
repeal
the
state’s
bail
system
in
2020
and
replace
it
with
an
algorithm
to
determine
individual
risk,
over
concerns
it
would

increase
bias
in
the
justice
system.

Broadly
speaking,
Margaret
Mitchell,
chief
ethics
scientist
at
AI
startup
Hugging
Face,
said
ethics
around
the
government
use
of
AI
hinge
on
the
context
of
use
and
safety
of
identifiable
information,
even
if
anonymized.
Mitchell
also
pointed
to
the
importance
of
receiving
informed
consent
from
people
seeking
help
from
government
programs.

 “Are
the
people
aware
of
all
the
signals
that
are
being
collected
and
the
risk
of
it
being
associated
to
them
and
then
the
dual
use
concerns
for
malicious
use
against
them?”
Mitchell
said. “There’s
also
the
issue
of
how
long
this
data
is
being
kept
and
who
might
eventually
see
it.”

While
the
technology
aims
to
provide
aid
to
those
in
need
before
their
housing
is
lost
in
Los
Angeles
County,
which
Mitchell
said
is
a
positive
thing
to
do
from
a “virtue
ethics”
perspective,
there
are
broader
questions
from
a
utilitarian
viewpoint.

 “Those
would
be
concerns
like, ‘What
is
the
cost
to
the
taxpayer
and
how
likely
is
this
system
to
actually
avoid
houselessness?'”
she
said.

As
for
Peterson,
she’s
in
the
process
of
looking
for
work,
hoping
for
a
remote
position
that
will
allow
her
flexibility.
Down
the
road,
she’s
hoping
to
obtain
her
licensed
vocational
nursing
certification
and
one
day
buy
a
home
where
her
son
has
his
own
room.

“It
has
meant
a
lot
just
because
you
know
my
son
hasn’t
always
had
that
stability.
I
haven’t
always
had
that
stability,”
she
said
of
the
aid
from
the
program. “To
be
able
to
call
this
place
home
and
know
that
I’m
not
going
to
have
to
move
out
tomorrow,
my
son’s
not
going
to
have
to
find
new
friends
right
away…
It’s
meant
a
lot
to
both
me
and
my
son.”