WEBVTT

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All right, so before I
introduce our eminent speaker,

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I just have a few announcements
that I've been given.

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So this is the iPad,
GVU lunch lecture.

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So I just want to get an idea

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of the people that are here.

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So, can I get a show in for
more accredited students?

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Okay, just leave it up
for just a little bit.

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And then other
students that are, I

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guess not accredited,
Vibes, excellent.

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And then, interested guests.

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Hi,

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excellent.

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Thank you.

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A reminder that students
that are taking this for

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credit, you must sign in by
your QR code or manually.

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We're about to
have a really fun,

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engaging talk from our speaker.

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So please, talk to your phones.

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Talk to your trash
before leaving.

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and another reminder
that meals are for our

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lunch lecture attendees
only so don't dine and

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dash sitting right there
tripping anyone before

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I introduce Alex I
also want to announce

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that next lunch lecture
next Thursday is Alex

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there's three of us
there's at least three

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of them different
speaker of health care

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and And we'll hear
about that next week.

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So it is my absolute pleasure

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to introduce
Duncan Alex Cabral.

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Alex is, as well as,
a postdoctoral fellow

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in the Palomoba lab
here at Georgia Tech.

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She is also an incoming
assistant professor

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very soon in the
Department of Urban

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Studies and Planning
and Institute for Data

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Systems and Society
at MIT. Not the one in

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Michigan, but the
one in Massachusetts.

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A little old university
that's come to get.

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She has a life-full experience,

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and I'll cover a
little bit of it.

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A few highlights. She
got her PhD from Harvard.

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She also spent
time at Microsoft

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Research and Microsoft Xbox.

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She also was a high
school teacher for

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STEM and math, if I
remember correctly,

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as well as when she joined
us, it's very important

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that leads a very
large part of our lab

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focused on environmental
justice, understanding

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environmental racism,
of building out sensors

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and really working for
us in the communities.

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And she has won many awards.

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She's going to go on to
do great, amazing things

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like her to pay attention
and learn as much as

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possible. So let's thank
you for taking the help.

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Thank you, Josiah. It's
great to see so many of

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you here, so many
friendly faces, unexpected

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friendly faces, new faces.
Really appreciate it.

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So yeah, I will dive in
and try to leave some time

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for questions at the
end. What this will look

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like, the motivation for
my work, general approach,

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the three sort of
subparts that I think make

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up that approach, and
then this new section

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that I'm playing
around with at the end.

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So the motivation for this
work comes from a lot of

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things, and I always like
to think about where we are

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locally. And so a few years
ago, this was a news headline

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in Atlanta about a lead
-tainted neighborhood becoming

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a major Superfund site.
Now, a Superfund site is a

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really dangerously polluted
site. Usually, it used to

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be some sort of manufacturing
site, for example, and

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there's thousands of them around
the country. But actually,

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a relatively small percent
get to be these national

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priorities list. So, this
makes this particular

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Atlanta neighborhood special
in a bad way. Now you may

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wonder where this is it is
shockingly close to us. So here

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we are I'm not tall enough
but there we are Georgia

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Tech and this yellow diamond
taken from the EPA Superfund

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map shows where that lead
site is west site lead.

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Now next to this over
here I got a map from this

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fun little site called
census dots where it

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shows a dot for every
person with a color based

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on their race. And you
can see that it is pretty

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much surrounded by all
black neighborhoods.

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You can also see crazy
segregation. We'll see that

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a little more later. So
this is West Side Lead, a

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super fun site, very, very
close to where we are now.

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And now this isn't just
an Atlanta issue. So I

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looked for an example in
another city. Our friend Moy

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can't be here, but he's
from Macon. And I found

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that there's two of these
national priority list

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Superfund sites on the
outskirts of Macon. And perhaps

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unsurprisingly for many
of us, again, these are

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located near majority
black neighborhoods, while

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the white neighborhood
gets to be pretty far away.

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And this issue is
way more than just

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Superfund sites.
So for example,

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here's census dots
for all of Atlanta.

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One thing you can see is
how crazy segregated it is

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all black neighborhoods
here all white and others

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up there and now here is
a map of food insecurity

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and so this is based on
the city health dashboard

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they took information from
the CDC and mapped the

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percentage of families that
are facing food insecurity

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and you can see that
almost all of them are in

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that same area where there's
mostly black neighborhoods

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and we see this another
things. So fresh produce,

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for example, is not
equitable across the city.

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Health is a big one.
This is looking at the

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percentage of residents
with obesity. Again, you

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could see in primarily
those neighborhoods.

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And even as crazy as life
expectancy. So your race

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can affect where you live,
can affect the food that

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you're given, the soil that
you're exposed to, the air

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that you're exposed to,
and then even how long you

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are expected to live. And
if that is not crazy to

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you, I don't know what to
say. I think it's absolutely

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insane. And it's clearly
based on these historical

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redlining issues, what we
call in the U.S., where

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certain races live in
certain areas and are then

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exposed to way more
negative things than others.

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Now, all of this has sort
of culminated in a movement

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which many refer to as
environmental justice.

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And there's a lot of
definitions for this. I pulled

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one from the American
Public Health Association,

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which is really just
environmental justice, the

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idea that people and
communities can live in safe

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and healthy environments,
that it should be equal,

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and that they should be
involved in those actions.

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Now, a big thing in actually
moving towards environmental

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justice is that we need
data to do so. So people

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need to be able to, quote
unquote, prove that they live

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in a neighborhood that has
bad soil, that doesn't have

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enough food, that has poor
air, etc. And with these

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data, people can then, one,
identify the issues and the

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locations where it's happening.
Two, hopefully inform

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policy, whether it's at a
local level or a national

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level. And then three, determine
what sort of action may

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actually take place. And
there are few, but there are

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success stories where this
actually does work to some

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extent. So one example is in
Flint, Michigan. Many of us

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may remember the water crisis
that they had. And even

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though this is still ongoing,
the community was able

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to quote-unquote prove that
they were exposed to poor

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water. They were then given
bottled water, and now

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actually a lot of the lead
pipes have been replaced. In

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addition, a much more recent
example is that some of us

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have heard of the XAI facility
that's being deployed in

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South Memphis that a lot of
environmental justice groups

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are upset about because it
is a predominantly black

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neighborhood. And the Southern
Environmental Law Center,

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which has an office just
down the street from here,

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they are now going to sue
Elon Musk and XAI because

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they're using gas turbines,
which are not allowed. And

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so again, having these data
can help, but it can be

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difficult to gather. And
regulatory monitoring is not

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enough. So for example, this
is a regulatory monitor for

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air pollution. It is large.
It is expensive. When I say

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expensive, I mean hundreds
of thousands of dollars. It

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requires special expertise
for maintenance. The data

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might come in hourly or
daily rather than continuous.

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And perhaps most importantly,
these are often placed

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far away from polluting
sources. And it might actually

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be that they are purposely
placed far away from polluting

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sources, but that's a
conversation for another day.

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Now why, or what does
this look like? So

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interestingly, for example,
in Atlanta, just about six

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months ago, there was a
report that the air quality

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is getting worse, especially
for ozone and particulate

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matter. But if you look at
where we have regulatory

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monitors, they're so tiny,
they're very tiny dots.

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You can see that we have at
Georgia Tech, so we monitor

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ozone particulate matter
here. We have one there,

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which I believe measures
ozone, and then we have one up

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there in Hills Park. And
so interestingly, those all

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say that the air pollution
is good, but if the American

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Lung Association is telling
us that the pollution

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is bad in particular areas
where we don't have monitors,

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then how are we supposed
to know what's going on.

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Now, another motivation,
and this is depressing,

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is that regulatory monitoring
data might not always

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live forever, right? So
just this year, the Trump

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administration deleted
a lot of this data from

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federal databases. We were
fortunate that researchers

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and advocacy groups
created their own backups,

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but this really points to
a need that communities

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have for more than just
regulatory monitoring.

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Now one thing that has
started to serve this gap

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is hyperlocal sensors.
So for air pollution, the

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most common one is called
purple air. It's a small

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sensor that you can
purchase for about $200 to

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measure particulate matter.
And these have started

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to become quite popular
because they are much lower

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cost, they can connect
wirelessly, you can put

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them anywhere, and they
collect data every minute.

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This is an example of
purple air in Atlanta. So I

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captured all the outdoor
sensors. And you can remember

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that EPA, we had the
three locations. Here we

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have many more than three.
So it seems successful.

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But the problem with these
sorts of sensors is one,

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they're designed by engineers.
I know that's probably

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a sore spot. That's a
lot of us. But engineers

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aren't always the best at
thinking through all of

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the community implications
and all of the needs that

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communities have. Another
is that they have limited

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or no maintenance. So
they're like closed box

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systems where if something
goes wrong, consumers don't

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know how to fix them or
what they might do. They

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don't give a lot of
visualizations. You usually just

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get a dashboard that's
like here's your plot, but

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you can't really get granular
into the information.

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You rely on users telling
you where they place them,

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if they're outside or
inside, which can of course

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cause some errors. And
the biggest issue though

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is that they often show up
in rich white neighborhoods.

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And so we're really
then just seeing that

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these devices are not being
placed where people need

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them, but rather by the
people who have extra money

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to spend to put a device
outside in their yard.

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Now, another interesting
thing, if we think back

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to the West Side Lead example,
is that this Superfund

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site was placed on the
national priority list

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because an Emory University
doctoral student gathered

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data and shared it with
the EPA. And then a few

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years later, the EPA is
now doing sampling. And so

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we can see that if we can
gather data, even we as

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students can gather data
and work to show it to the

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people who have power,
we can make a difference.

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So ultimately, this all
leads into my broader

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research question of
how we can design these

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sorts of sensing systems
with and for communities

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who are really facing
the most negative

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effects of environmental
injustice and racism.

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So the broader approach that
I take, which I've referred

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to as co-designed hyper
-local environmental sensing,

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really it pulls from a
lot of different areas,

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primarily around sensing
and cyber infrastructure and

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HCI, and then combining theory
applications and engagement

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in these three sorts of
areas that I look at,

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designing the hardware,
designing the deployment, and

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designing the interfaces.
And now it's important to

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take like a sidestep here
just to talk about community

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engagement, because I think
it's something that we

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throw around a lot, but it's
not easy. And I want to be

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clear that a lot of the
work and a lot of the talks

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we see where people are
doing this, it sounds like,

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oh, I'll just go out and
engage with communities. Great.

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This takes time. It sometimes
takes years to build

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these relationships and
to maintain it. It takes a

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commitment to sticking through
with that relationship.

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A big one that I
think Carl mentioned a

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couple weeks ago, too,
it takes willingness

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to be a novice. And
so we are not experts

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in living in these
areas necessarily.

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So we need to hear from
the people who are. And a

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big one is that building
on existing relationships.

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So a lot of the times other
people in our community

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may have relationships,
and we need to then

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build onto those in order
to engage with communities.

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Now, it also comes with
several challenges. A

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big one is around pacing.
So in academia, we often

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have deadlines for papers,
for grants. We have

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students who are leaving.
But communities are facing

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these issues, and oftentimes
they take decades in

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order to actually address.
Another one is trust.

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Particularly with
researchers and with these

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communities, of course,
there's been a lot of

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exploitation. There's been
a mistrust based on what

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governments have done,
what people have done.

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And so acknowledging
the issues of trust and

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taking time to build it is
super important. And then

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finally, there's this
whole power hierarchy.

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The most interesting example
I like to refer to is

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like IRBs and consent forms,
for example. So you may

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be working with a community
and thinking, oh, well,

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I'm going to turn this
into a great paper. And

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then you'll do a study and
interview them. And once

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you bring about a consent
form, though, it really

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introduces this power dynamic
that perhaps you didn't

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want in a community engaged
scenario, which isn't

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to say that we shouldn't
do it, but which is just to

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acknowledge that this is
a challenge we will face.

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Okay, so back down to
the main road after our

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detour. I want to take you
through these different

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parts of my research
approach and what that

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has looked like through
a couple of projects.

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So the first is thinking about
co-designing the hardware,

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which really constrains
what data we can collect.

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So for this example, I want
to tell you a bit about

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manumen, which is a wild
rice that used to grow

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abundantly across a lot of
the United States. It grows

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in the water, and it's a
grain that is important to

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Native American communities
who have been harvesting

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this for generations, and
they rely on it for food,

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for the economy, spiritual
and cultural events, etc.

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Now, there's several
threats to manumen,

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including, of course,
climate change,

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human use of water and
land like boating and urban

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development, even birds
for example and populations

15:34.440 --> 15:37.780
that can change based on
climate change and human

15:37.780 --> 15:40.840
actions such as mining
and pipelines. And so this

15:40.840 --> 15:44.220
image shows all the lakes
and rivers with wild rice

15:44.220 --> 15:47.880
as yellow dots and then
a proposed pipeline and

15:47.880 --> 15:51.600
a red line that would go
through so many of those.

15:53.460 --> 15:57.080
Now monitoring this wild
rice, though, it's also

15:57.080 --> 15:59.800
very difficult. So if you've
ever been to Wisconsin,

15:59.820 --> 16:02.660
Minnesota, Michigan, what
you may know is that these,

16:02.660 --> 16:04.980
I think Minnesota is
literally called the land of

16:04.980 --> 16:08.030
10,000 lakes. And so
these are places that have

16:08.030 --> 16:11.380
thousands of bodies of water.
So thinking about how you

16:11.380 --> 16:13.820
would actually go out to
all these bodies of water,

16:13.820 --> 16:16.700
many of which are remote,
is very difficult. It's

16:16.700 --> 16:19.560
time intensive to grab
things like water quality

16:19.560 --> 16:22.900
samples or to look at the
abundance of the wild rice.

16:22.900 --> 16:25.220
And even though there's
satellite imagery, of course,

16:25.220 --> 16:27.200
it's pretty low resolution.
You might not be able

16:27.200 --> 16:30.320
to really see what's
going on there. And so an

16:30.320 --> 16:33.780
approach that we've taken is
to gather this hyper-local

16:33.780 --> 16:37.540
environmental data, data
where the wild rice actually

16:37.540 --> 16:41.600
is or may be, to sit
within the bed. And these

16:41.600 --> 16:45.090
we've called macaque,
which is a Native American

16:45.090 --> 16:47.940
Ojibwe word, the tribes we
work with, for containment.

16:48.820 --> 16:52.500
Now in designing this
hardware we first started by

16:52.500 --> 16:55.420
learning from field researchers
and natural resources.

16:55.420 --> 16:58.400
So one of our grad students
Eric spent a summer up north

16:58.400 --> 17:01.600
working with a lot of
tribes and natural resource

17:01.600 --> 17:04.320
departments to learn how they
do their work and how these

17:04.320 --> 17:06.780
sorts of sensors might fit
in with their practice.

17:07.380 --> 17:10.660
We then built a pilot,
which looked like

17:10.660 --> 17:14.640
this, and which we
deployed last summer, 2024,

17:14.760 --> 17:17.300
for about five months with four

17:17.300 --> 17:18.790
of our partner organizations.

17:18.790 --> 17:22.620
And these collected data
such as the temperature of

17:22.620 --> 17:26.300
the water at the surface
and depth, air humidity,

17:26.740 --> 17:29.440
water pressure to be
able to gather as a

17:29.440 --> 17:32.240
proxy for water level
changes, acceleration

17:32.240 --> 17:34.960
for things like
waves and boat wakes.

17:35.460 --> 17:38.400
and then of course you know
connected data wirelessly

17:39.070 --> 17:42.800
and from the pilot what
we found was okay well the

17:42.800 --> 17:45.560
devices themselves are pretty
well correlated so we had

17:45.560 --> 17:51.280
two devices over here that
were on the same lake a

17:51.280 --> 17:53.560
very big lake different ends
and so we would expect to

17:53.560 --> 17:56.360
see that okay the temperature
sort of changes similarly

17:56.360 --> 17:59.440
throughout the day great
and the water level changes

17:59.440 --> 18:01.800
about the same throughout
the season, that's great

18:01.800 --> 18:06.100
too. But what we also found
was that there were a lot

18:06.100 --> 18:08.880
of issues with connectivity
where some devices could

18:08.880 --> 18:11.380
just never connect to
the cell signal at all to

18:11.380 --> 18:15.080
transmit data and a lot of
the batteries ended up dying

18:15.080 --> 18:18.540
either intermittently or
just early on in the summer.

18:19.520 --> 18:22.920
So for moving to V2 then,
of course we had to learn

18:22.920 --> 18:26.780
from one, our failures, and
two, trying to integrate some

18:26.780 --> 18:29.080
more of the local knowledge,
especially that our

18:29.080 --> 18:32.620
tribal partners have. And so
in talking to them, one of

18:32.620 --> 18:35.360
the quotes that really stuck
out to me was this one where

18:35.360 --> 18:37.780
one of our partners said,
well, seeds can be dormant

18:37.780 --> 18:40.320
for years, so maybe we
need to know what the light

18:40.320 --> 18:43.020
looks like down there. I
think Josiah and I were up at

18:43.020 --> 18:45.480
a meeting and someone told
a story about a person who

18:45.480 --> 18:48.780
bought a lake house in
Minnesota and went to build a

18:48.780 --> 18:51.820
dock there. And as they were
digging up the muck to put

18:51.820 --> 18:54.560
in the dock, what happened?
A bunch of rice started

18:54.560 --> 18:58.220
growing up that hadn't been
there for 10 or 15 years and

18:58.220 --> 19:01.040
so getting a sense of you
know maybe it's that the sun

19:01.040 --> 19:03.840
isn't reaching the seeds
can we try to adapt for that

19:03.840 --> 19:07.180
so our hardware then tried
to address this by also

19:07.180 --> 19:11.000
looking at light we added
in water quality sensors as

19:11.000 --> 19:13.820
well and we learned from
our failures we put in an sd

19:13.820 --> 19:17.580
card for storage in case the
devices were offline we had

19:17.580 --> 19:20.500
solar charging to be able to
actually have the batteries

19:20.500 --> 19:23.600
hopefully last all the
summer and we added gps

19:23.600 --> 19:27.560
location in case devices got
swept away by strong winds.

19:28.700 --> 19:31.860
Now what this looked like for
this summer was interesting.

19:31.860 --> 19:33.840
We deployed a lot more
sensors with a lot more

19:33.840 --> 19:38.640
partners. We had 19 total
and the biggest issue was

19:38.640 --> 19:41.840
that we had really poor
connectivity. So you can see

19:41.840 --> 19:45.180
all these red diamonds are
ones that didn't connect at

19:45.180 --> 19:47.900
least at some point and
we had only about two or

19:47.900 --> 19:51.220
three that did and of course
part of this could be an

19:51.220 --> 19:53.180
engineering problem where we
say okay okay, well, maybe

19:53.180 --> 19:56.020
we need to use LoRaWAN, maybe
we need to use satellite,

19:56.020 --> 19:58.980
et cetera. But I think it
also reflects an important

19:59.180 --> 20:01.040
socioeconomic problem,
which is that these

20:01.040 --> 20:05.660
communities that are facing
these issues of land use, mining,

20:05.660 --> 20:08.400
all of these things happening
on their tribal lands

20:08.400 --> 20:11.940
are also facing issues
around technical equality.

20:11.940 --> 20:14.980
They don't have the
connectivity even for us to be

20:14.980 --> 20:18.240
able to try and collect these
real-time data for them.

20:19.950 --> 20:22.060
Now, one of the things
I've also been thinking

20:22.060 --> 20:25.820
about moving forward is
how we might be able to

20:25.820 --> 20:29.220
redesign the hardware. And
so we've gotten better. This

20:29.220 --> 20:31.400
is certainly better than
what we first put out.

20:31.400 --> 20:33.300
But something that really
struck me is that the

20:33.300 --> 20:36.540
word mccuc is an Ojibwe
word that means container.

20:36.540 --> 20:40.120
And so one of our master
students in the back corner,

20:40.120 --> 20:43.060
Madison, looked last
semester at how we might

20:43.060 --> 20:46.860
actually make a device that
looks like what the mccucke

20:46.860 --> 20:50.120
looked like for the Ojibwe
culture. So these are

20:50.120 --> 20:53.280
beautiful birch bark
containers and what we've found

20:53.280 --> 20:55.060
through some of our partners
is that a lot of them

20:55.060 --> 20:57.260
still have the traditional
knowledge to make these

20:57.260 --> 21:00.400
sorts of things. And because
they make canoes out of

21:00.400 --> 21:03.320
birch bark, in theory these
should be somewhat waterproof

21:03.320 --> 21:05.980
and floatable. And so
we're really thinking about

21:05.980 --> 21:08.880
what that might look like
and now working with a

21:09.080 --> 21:12.380
3D modeler at the tribal
college up north to see

21:12.380 --> 21:15.540
if we can make something
that perhaps more closely

21:15.540 --> 21:18.980
mimics this sort of
shape, idea, culture, etc.

21:19.940 --> 21:23.780
So sort of summing up this
section with the co-design

21:23.780 --> 21:26.240
sensing hardware what
we found is that you can

21:26.240 --> 21:29.140
integrate all these forms of
local knowledge and expand

21:29.140 --> 21:32.680
the sphere of whom these
experts are and then also get

21:32.680 --> 21:36.480
interesting perhaps more than
human sensory experiences.

21:36.480 --> 21:39.860
So we think about, for
example, light on rice

21:39.860 --> 21:43.520
beds, especially deep in the
water. As one of our partners

21:43.520 --> 21:46.660
said, this is more like
the experience of a rice

21:46.660 --> 21:49.520
bed. How can we think about
sensors that enable long?

21:51.100 --> 21:53.540
So the second main
part of the approach

21:53.540 --> 21:55.680
that I look at is
deployment strategy. Where

21:55.680 --> 21:57.580
do we place sensors?
Because that kind of

21:57.580 --> 22:00.180
determines what
questions we can answer.

22:00.300 --> 22:02.980
And so for this I'll
talk a bit about another

22:02.980 --> 22:05.940
project that's rooted
in urban air pollution.

22:05.940 --> 22:08.790
And so I think many of
us are familiar with the

22:08.790 --> 22:11.340
issue of urban air
pollution. And one of the

22:11.340 --> 22:14.640
most harmful pollutants
is called PM 2.5. So

22:14.640 --> 22:17.840
these are particles that
could be sand, smoke,

22:18.000 --> 22:22.380
smog. And the 2.5 comes
from them being two and a

22:22.380 --> 22:26.180
half micrometers in diameter,
which is one thirtieth

22:26.180 --> 22:28.580
of the width of a human
hair, if you can even

22:28.580 --> 22:30.800
mentally process that
which, honestly, I can't.

22:31.760 --> 22:35.840
This is a huge issue. It
causes deaths every year.

22:35.840 --> 22:39.420
It causes childhood asthma
cases all around the

22:39.420 --> 22:42.440
world, particularly in
Southeast Asia and Africa. A

22:42.440 --> 22:45.240
lot of urban residents are
exposed to poor air quality.

22:45.240 --> 22:48.220
But even in the U.S.,
this isn't such an issue.

22:49.080 --> 22:52.040
And so, as I mentioned
before, regulatory

22:52.040 --> 22:54.200
monitoring is not
enough. So this

22:54.200 --> 22:56.320
project, which took
place in Chicago.

22:56.640 --> 23:00.560
Here you can see the EPA
stations around Chicago.

23:00.560 --> 23:02.500
And so what you can see
is that most of them are

23:02.500 --> 23:05.320
actually not in Chicago
where people live. They're

23:05.320 --> 23:08.300
more in the suburban areas.
And another interesting

23:08.300 --> 23:11.220
thing is that they're on
rooftops of buildings,

23:11.220 --> 23:13.540
some of them which are
pretty tall. And so this is

23:13.540 --> 23:16.540
myself and a colleague
deploying sensors at an EPA

23:16.540 --> 23:19.200
station and we had to take
an elevator up five or

23:19.200 --> 23:22.740
six floors. And so really
these aren't measuring what

23:22.740 --> 23:25.780
people are experiencing,
which is a huge issue.

23:26.460 --> 23:30.640
Now for this project, I
worked closely with the Urban

23:30.640 --> 23:33.600
Innovation Initiative at
Microsoft Research to develop

23:33.600 --> 23:36.280
a sensor called Eclipse.
And so these were lower

23:36.280 --> 23:41.870
cost air quality sensors
that monitored PM 2.5, ozone,

23:42.560 --> 23:46.560
sulfur dioxide, nitrogen
dioxide, and carbon monoxide.

23:46.560 --> 23:51.000
And we placed them around
the city at bus shelters,

23:51.120 --> 23:53.880
working with a company
called J.C. Deco, which

23:53.880 --> 23:56.240
owns them. And so the great
thing about placing them

23:56.240 --> 23:58.540
at bus shelters is that
they were only about eight

23:58.540 --> 24:00.760
feet off the ground. And
in theory, we could also

24:00.760 --> 24:03.280
start to see something
about all of the residents

24:03.280 --> 24:06.240
who rely on the bus system
and what sort of air

24:06.240 --> 24:09.000
quality they're exposed to
as they're waiting outside.

24:09.880 --> 24:13.180
Now, in determining where
to actually place these

24:13.180 --> 24:15.660
sensors, we thought
about a couple different

24:15.660 --> 24:18.860
criteria. And so one was
that we wanted to be flexible

24:18.860 --> 24:20.940
so that we could answer
different research

24:20.940 --> 24:23.560
questions. But we also
wanted to make sure that we

24:23.560 --> 24:26.780
prioritize environmental
justice. And so I don't have

24:26.780 --> 24:29.040
a map here, but if you're
familiar with Chicago,

24:29.310 --> 24:32.500
just like Atlanta and many
other U.S. cities, it is

24:32.500 --> 24:35.440
unfortunately quite segregated.
And so most of the black

24:35.440 --> 24:38.220
and brown communities live
on the west and the south

24:38.220 --> 24:41.840
of Chicago, whereas most
of the rest of the city is

24:41.840 --> 24:45.700
quite heavily white. And so
what we did was we worked

24:45.700 --> 24:48.980
with environmental justice
communities from those

24:48.980 --> 24:53.180
areas of Chicago and allowed
them to select where to

24:53.180 --> 24:55.680
place a certain number of
sensors. And many of them

24:55.680 --> 24:58.860
wanted to place sensors near
schools, parks, churches,

24:58.860 --> 25:01.640
places where the community
often congregated outside.

25:01.840 --> 25:06.380
So we had 118 sensors that
we placed and we used a mix

25:06.380 --> 25:09.260
of the environmental
justice groups, some of our

25:09.260 --> 25:11.920
partner orgs like the Chicago
Department of Public Health,

25:11.920 --> 25:15.840
choosing a few, and then
stratified random sampling

25:15.840 --> 25:19.900
where we split the city up
into a grid of 200 meters

25:19.900 --> 25:23.900
by 200 meters assigned whether
they were high traffic,

25:23.900 --> 25:27.380
high population, low
traffic, low population, etc.

25:27.380 --> 25:29.820
And then split them up so
we had 20 in each different

25:29.820 --> 25:32.380
type. And then we also
had some that we placed

25:32.380 --> 25:36.080
at EPA stations for
calibration. I don't go into

25:36.080 --> 25:38.300
depth here, but I'm happy
to talk about that as well.

25:39.120 --> 25:41.580
So what does this actually
look like when you

25:41.580 --> 25:45.080
deploy it this way? Well,
we compared our network to

25:45.080 --> 25:48.240
the EPA and the Purple
Air, which, reminder, are

25:48.240 --> 25:50.820
those consumer ones that
people can buy for $200.

25:51.120 --> 25:55.060
And we looked to see, okay,
how far are these sensors

25:55.060 --> 25:58.540
from the average Chicago
resident, the average

25:58.540 --> 26:00.860
black Chicago resident,
and the average Hispanic

26:00.860 --> 26:03.600
Chicago resident? And we
found that our sensors were

26:03.600 --> 26:05.660
always closer. And you
may just say, well, of

26:05.660 --> 26:09.500
course, you have more sensors,
duh, which is true. But

26:09.500 --> 26:11.800
we also then looked at,
okay, well, what about the

26:11.800 --> 26:15.940
sensors that are running
for more than 75% of the

26:15.940 --> 26:18.820
days of the year. And we
use that criteria because

26:18.820 --> 26:21.960
that's what the EPA requires
for calibration. They

26:21.960 --> 26:24.700
say your sensors have to
run for at least 75% of

26:24.700 --> 26:26.940
the year. And what we
found were that our sensors

26:26.940 --> 26:29.780
were still closer and
shockingly even some of the

26:29.780 --> 26:34.360
EPA monitors don't run for
75% or more of the year.

26:34.940 --> 26:38.080
Now furthermore we looked
to see well what is the

26:38.080 --> 26:40.740
difference if we look at the
ones that we chose somewhat

26:40.740 --> 26:44.200
randomly versus that our
community partners chose.

26:44.200 --> 26:46.460
And what we found was
that our community partner

26:46.460 --> 26:51.700
locations were much more
likely to be near manufacturing

26:51.700 --> 26:54.860
zones, about three times
more likely. They also had

26:54.860 --> 26:58.760
about three times more rail
miles close to them. And

26:58.760 --> 27:02.320
so they were identifying
these manufacturing sites,

27:02.320 --> 27:05.900
these toxic release inventory
sites, and these rail

27:05.900 --> 27:09.060
stations, which our random
sampling didn't capture.

27:09.060 --> 27:13.280
And so this is super interesting
because one, in seeing

27:13.280 --> 27:15.760
the communities, we can
see what's important to

27:15.760 --> 27:18.640
them. And then two, it also
really touches on the fact

27:18.640 --> 27:22.220
that environmental justice
could be very different

27:22.220 --> 27:24.820
based on the local communities
that we're talking to.

27:25.180 --> 27:27.720
Now another interesting
thing about our deployment

27:27.720 --> 27:31.500
strategy is that we were
able to capture hyper

27:31.500 --> 27:34.780
-local events and widespread
events. So for example,

27:34.780 --> 27:36.960
if you look at the top,
you can see we first

27:36.960 --> 27:39.720
deployed just before 4th
of July. And we saw a

27:39.720 --> 27:43.220
huge stake, as did the
EPA, which is shown in red,

27:43.280 --> 27:47.280
around the fireworks. So
TLDR fireworks are terrible,

27:47.280 --> 27:49.660
just don't do it, like
keep your hands, also your

27:49.660 --> 27:52.580
lungs, but also because
of things like barbecuing,

27:52.580 --> 27:56.620
grilling, etc. We also saw
a spike around wildfires

27:56.620 --> 27:59.280
that were coming in from
Canada at the time. But then

27:59.280 --> 28:02.260
we also saw that there were
lots of events that one

28:02.260 --> 28:05.160
of our centers was picking
up that the EPA wasn't.

28:05.160 --> 28:08.040
And so when we went to
investigate some of these sensors,

28:08.040 --> 28:12.100
we found very hyperlocal
sources of pollution.

28:12.100 --> 28:15.800
For example, one being this
fried chicken spot. And so

28:15.800 --> 28:18.500
this sensor, we knew
something was going on because

28:18.500 --> 28:20.960
we placed it across the
street from another sensor

28:20.960 --> 28:24.620
as our sanity check. And
this one was going up every

28:24.620 --> 28:28.420
day around 10 30 until about
9 p.m. And we found that

28:28.420 --> 28:31.100
it's because the vent,
the exhaust for the fried

28:31.100 --> 28:33.940
chicken was right there.
And so this is crazy because

28:33.940 --> 28:35.880
if you imagine waiting
for the bus, maybe you're

28:35.880 --> 28:38.040
like oh that fried chicken
smells so good but actually

28:38.040 --> 28:41.220
it's not really that great
for you. A similar issue

28:41.220 --> 28:44.380
is that we found one near
a bar that was like tiki

28:44.380 --> 28:47.940
churches outside at night
and so similarly right you

28:47.940 --> 28:50.580
think oh great ambiance but
in fact releasing all of

28:50.580 --> 28:52.980
these particles which are
harmful for human health.

28:53.760 --> 28:56.580
Now some of the challenges
we had several but I wanted

28:56.580 --> 28:59.280
to touch on some. So one
of the big ones was again

28:59.280 --> 29:03.460
around connectivity and charging
and this may be surprising.

29:03.460 --> 29:05.720
It was for me because
we're in a city. We're in a

29:05.720 --> 29:08.260
massive city. Why wouldn't
we be able to connect to

29:08.260 --> 29:12.040
cellular? But we found that
11 of the sites that we had

29:12.040 --> 29:14.500
originally planned for
couldn't connect to cellular at

29:14.500 --> 29:17.680
all. And three of them were
ones that community selected.

29:17.780 --> 29:20.760
And this is crazy because
it shows again that sort

29:20.760 --> 29:24.900
of socioeconomic intermingling
of all the different

29:24.900 --> 29:28.820
issues that people have, right?
Air pollution, connectivity.

29:28.860 --> 29:31.900
Even some of the sites
didn't have bus shelter,

29:31.900 --> 29:35.560
so a lot of the south were
more sparse and places where

29:35.560 --> 29:37.780
people wanted to place sites
that weren't enough bus

29:37.780 --> 29:40.560
shelters for us to be able
to actually place a center.

29:40.680 --> 29:43.480
And we also had issues
with solar charging, so

29:43.480 --> 29:45.960
we lost a lot of data,
and some of this may

29:45.960 --> 29:48.040
seem obvious. If you're
familiar with Chicago,

29:48.040 --> 29:50.700
that's downtown there,
that yellow dot is real.

29:53.680 --> 29:56.300
Sorry, technical difficulties.
That yellow dot is

29:56.300 --> 29:58.900
right next to a giant
building, and so it makes sense

29:58.900 --> 30:00.700
that that one wouldn't
be able to connect. But

30:00.700 --> 30:04.300
this one out here was actually
like much more suburban

30:04.300 --> 30:07.240
and again in a low-income
black and brown community

30:07.240 --> 30:10.040
and what we found was
that it may have just been

30:10.040 --> 30:12.820
trees but it's really
difficult to try and predict

30:12.820 --> 30:15.440
these issues because the
open data for buildings

30:15.440 --> 30:18.600
and trees is not always
there not always accurate

30:19.360 --> 30:23.060
and so yeah trying to figure
it out is very difficult

30:23.060 --> 30:25.190
and this is the same for
cellular connectivity.

30:27.170 --> 30:29.400
I'm okay. I'll clip it on
again in a sec. Thanks.

30:29.920 --> 30:33.200
Now, another challenge that
we had is that not everyone

30:33.200 --> 30:35.460
was happy, which I mean
is life, but still it's

30:35.460 --> 30:37.720
important to consider when
you're working with people.

30:37.720 --> 30:40.120
So for example, this is
actually from one of our

30:40.120 --> 30:42.800
partners who worked for the
Chicago Department of Public

30:42.800 --> 30:46.300
Health. And he was upset
because we had totally

30:46.300 --> 30:49.200
ignored the area that he
lived in. And he said, you

30:49.200 --> 30:51.560
know, I think this is a
misconception that everyone

30:51.560 --> 30:54.780
thinks the north side is rich
and white, but I work for

30:54.780 --> 30:57.680
the city and my wife is a
teacher. We're not rich.

30:58.580 --> 31:00.860
So of course this brings
about the question, well,

31:00.860 --> 31:04.460
how can we then make a
fair sensor network? And so

31:04.460 --> 31:06.720
that question is actually
one that I tackled for

31:06.720 --> 31:09.120
part of my dissertation. I
won't go into it now, but

31:09.120 --> 31:13.280
what I can tell you very
briefly is that fair itself

31:13.280 --> 31:16.220
is a very loaded word and
everyone has a completely

31:16.220 --> 31:19.020
different definition of
what's fair. And so really,

31:19.020 --> 31:21.520
again, this requires local
knowledge of knowing,

31:21.520 --> 31:25.040
well, what does fair mean
for this specific area?

31:25.980 --> 31:30.100
So in sum for this section,
co-designing the deployment

31:30.100 --> 31:32.600
strategy, we saw that
we could get coverage

31:32.600 --> 31:35.300
for underserved groups,
particularly in letting them

31:35.300 --> 31:39.500
choose where the devices
go. And they could sort of

31:39.500 --> 31:42.080
self-identify what the
important environmental

31:42.080 --> 31:45.540
justice areas were for them
rather than us trying to

31:45.540 --> 31:48.360
decide as outsiders or
letting an algorithm choose

31:48.360 --> 31:51.820
for them but then we also
found that we might need

31:51.820 --> 31:54.600
this perhaps even more so
than what we did for this

31:54.600 --> 31:59.080
perception of a fair design
I'll clip on in a second

32:02.300 --> 32:08.380
any quick questions while
I reclip yeah Michelle

32:14.960 --> 32:21.060
Yeah, that's a great
question. So we, we didn't

32:21.060 --> 32:23.580
record any of those
meetings. The question in

32:23.580 --> 32:25.200
case you didn't hear
was if we collected any

32:25.200 --> 32:28.780
commentary on why community
sites chose the places

32:28.780 --> 32:31.740
that they did. And so
we did not record those

32:31.740 --> 32:33.560
meetings. And again, that
sort of goes into the whole,

32:33.560 --> 32:35.700
you know, recording
makes things feel weird.

32:36.080 --> 32:39.260
But what I can tell you
is that a lot of it was

32:39.260 --> 32:42.260
really tied to like where
they know people are or

32:42.260 --> 32:46.240
where they know or think
specific sources of pollution

32:46.240 --> 32:48.840
are. So, for example,
by the railway station,

32:48.900 --> 32:52.740
a really good example is
there is an asphalt plant

32:52.740 --> 32:55.120
that one of the community
groups really wanted

32:55.120 --> 32:56.900
to get sensors near
because it was right across

32:56.900 --> 32:59.360
from a park where people
would spend time outside.

32:59.800 --> 33:02.000
The interesting note
of that is that that

33:02.000 --> 33:04.660
sensor that we placed
outside the asphalt plant

33:04.810 --> 33:08.260
mysteriously got ripped
off several times.

33:09.380 --> 33:10.700
No one knows why.

33:10.820 --> 33:12.920
Yes, but yeah, that's a
great question. And I think,

33:13.250 --> 33:16.020
yeah, getting a sense. And
I will say, too, though,

33:16.020 --> 33:18.330
that, like, of course,
community groups are not a

33:18.330 --> 33:20.840
monolith. And so we had
some groups who really cared

33:20.840 --> 33:22.900
about some issues and some
groups who really cared

33:22.900 --> 33:25.160
about others. Like one
group where their whole

33:25.160 --> 33:27.600
thing was they wanted more
trees and another where they

33:27.600 --> 33:28.920
didn't want construction.
And some of these groups

33:28.920 --> 33:32.300
also hated each other, which
made it quite difficult.

33:32.300 --> 33:34.590
But is the reality, again,
of all these people?

33:34.820 --> 33:35.700
No.

33:35.840 --> 33:38.460
Okay, cool. So I'll get
into this third main

33:38.460 --> 33:41.740
section then, which is around
data interfaces, right?

33:41.740 --> 33:43.640
So we collect all this
data. We actually have

33:43.640 --> 33:46.310
to do something with it
and show it to people and

33:46.310 --> 33:49.120
determine who can answer
what sort of questions.

33:50.980 --> 33:53.240
So for the Eclipse Project, we

33:53.240 --> 33:54.980
worked very closely with city,

33:55.280 --> 33:57.860
community, and research
stakeholders. So

33:57.860 --> 33:59.380
we did some interviews
to determine what

33:59.380 --> 34:01.260
sort of things people
were interested in

34:01.260 --> 34:03.560
with particulate matter
data specifically.

34:03.600 --> 34:06.180
And what we found is that
a lot of people wanted

34:06.180 --> 34:09.780
to look at things like
policy, education, and

34:09.780 --> 34:12.020
empowerment. And so we
tried to figure out how

34:12.020 --> 34:14.540
we could design interfaces
to support those.

34:14.540 --> 34:17.620
Now, the first interface
we made was kind of what

34:17.620 --> 34:21.960
you would expect. It was a
map with, you know, showing

34:21.960 --> 34:24.900
where all the sensors
were, colors, values, etc.

34:24.900 --> 34:28.040
and we thought we were being
like super cute by adding

34:28.040 --> 34:31.220
QR codes at the bus shelters
so that people would

34:31.220 --> 34:34.080
you know see the QR code
and scan it and then be

34:34.080 --> 34:36.840
able to see the map and of
course it turned out that

34:36.840 --> 34:40.340
no one ever scanned the
QR codes and we also found

34:40.340 --> 34:42.880
that people were like I
don't know this map doesn't

34:42.880 --> 34:45.500
really show me enough like
I want to know how different

34:45.500 --> 34:48.280
my neighborhood is from
the one that I think is

34:48.280 --> 34:51.080
much better for example
where people said you know

34:51.080 --> 34:53.640
With scanning a QR code, not
everyone has a smartphone.

34:53.640 --> 34:56.060
As we saw, there's not
cell signal everywhere.

34:56.430 --> 34:58.640
A lot of people want to
look things up in the

34:58.640 --> 35:01.560
library, and maybe they
don't have internet at home.

35:02.500 --> 35:06.160
Now, as we were making the
website, we also worked

35:06.160 --> 35:12.780
on a public API. And so
this was a way for primarily

35:12.780 --> 35:16.880
researchers and programmers
to be able to plug directly

35:16.880 --> 35:19.280
into our data and make
their own visualizations.

35:19.900 --> 35:22.160
And what we found, though, is

35:22.160 --> 35:24.420
that, perhaps unsurprisingly,

35:24.560 --> 35:27.180
community groups and
city employees, they

35:27.180 --> 35:29.000
don't really have the
time and maybe the

35:29.000 --> 35:31.700
expertise to work
directly with raw data.

35:31.900 --> 35:34.620
And so, you know, we
were trying to figure out

35:34.620 --> 35:36.620
how we could create
some sort of low and low

35:36.620 --> 35:38.860
cloud environment. And
now with the advances

35:38.860 --> 35:41.640
we have in chat GPT,
that's perhaps an option

35:41.640 --> 35:43.900
for people to be able
to say this is the sort

35:43.900 --> 35:46.320
of graph that I want
and work with the data.

35:46.720 --> 35:49.520
But at the time, we really
couldn't figure out how

35:49.520 --> 35:51.540
we could connect this
with the partners we were

35:51.540 --> 35:55.280
trying to work with. And
another challenge that arose

35:55.280 --> 36:00.660
is how we actually get the
data to the communities.

36:00.660 --> 36:03.460
And so this is something
that our partners often ask

36:03.460 --> 36:05.340
about. How do we show the
community members that

36:05.340 --> 36:08.100
we're even doing this and
what data we're collecting?

36:08.100 --> 36:11.870
And so to this end, we
made a sort of crazy, wacky

36:11.870 --> 36:14.520
interface called the
EcoPod. pod. And so this was

36:14.520 --> 36:18.500
a horse trailer that we
purchased and we retrofitted

36:18.500 --> 36:21.720
it with solar panels with,
you know, little display

36:21.720 --> 36:24.380
areas. We drove it to
Chicago and we brought it

36:24.380 --> 36:27.160
to events such as Earth
Day at the Field Museum,

36:27.160 --> 36:29.600
which is a really big
natural history museum there,

36:29.600 --> 36:33.860
a big recycling event in a
park, et cetera. And so we

36:33.860 --> 36:36.860
went there, manned this
station, talked to people

36:36.860 --> 36:39.680
about the sensors. We had a
screen that showed all of the

36:39.680 --> 36:42.320
data in real time for people
to be able to interact

36:42.320 --> 36:44.740
with and we brought all the
different versions of the

36:44.740 --> 36:47.400
hardware that we had for
kids to play around with and

36:47.400 --> 36:50.040
they were super into that
and we also had tables for

36:50.040 --> 36:52.480
all of our community partners
to be able to also set

36:52.480 --> 36:55.760
up and interact with people
and what we found was

36:55.760 --> 36:58.520
that people were really
engaged with this and we would

36:58.520 --> 37:01.660
see a huge spike in website
traffic during the event

37:01.660 --> 37:04.360
and then maybe a few days
after but then it would trickle

37:04.360 --> 37:06.740
down again and so this
points to a lot of questions

37:06.740 --> 37:10.070
of how we can keep that
sort of engagement, and

37:10.070 --> 37:12.340
especially, I think, how we
can have residents feel like

37:12.340 --> 37:14.440
they're inputting something.
Because what we learned

37:14.440 --> 37:17.080
at these experiences was
that a lot of people wanted

37:17.080 --> 37:19.360
to tell us their stories.
They wanted to tell us what

37:19.360 --> 37:21.460
they knew, what they
experienced, and we didn't really

37:21.460 --> 37:24.300
have that sort of input
in the interfaces we made.

37:25.640 --> 37:29.220
Now, another challenge that
arises in these sorts of

37:29.220 --> 37:31.560
interfaces is how we can
integrate different sorts

37:31.560 --> 37:35.140
of cultures. And so last
year and chatting with some

37:35.140 --> 37:38.200
of our partners up north
for the Manuman project,

37:38.520 --> 37:41.540
one of them told me, well,
people go out and harvest

37:41.540 --> 37:44.280
the rice in Labor Day weekend
because that's when they

37:44.280 --> 37:46.140
think they're supposed to
do it. But really, it's not

37:46.140 --> 37:49.180
about Labor Day. It's about
the ricing moon. And so it

37:49.180 --> 37:51.980
would be really cool if instead
of showing a traditional

37:51.980 --> 37:54.960
calendar, we could show
some sort of moon calendar.

37:55.180 --> 37:58.260
And so for the interface
we made for these

37:58.260 --> 38:01.280
devices, which we've
called Noondawin, which is

38:01.280 --> 38:04.800
an Ojibwe word for as
one is heard. We started

38:04.800 --> 38:07.980
exploring some culturally
situated interfaces.

38:07.980 --> 38:10.660
And so we had a great
master's student named

38:10.660 --> 38:13.420
Jonavi who was working on
this last year. And what

38:13.420 --> 38:15.840
she did was she looked
at all of these different

38:15.840 --> 38:19.280
Ojibwe art pieces. So
beading, for example,

38:19.420 --> 38:22.100
paintings, some of the
art that our partners

38:22.100 --> 38:24.740
publish in their quarterly
magazines and on their

38:24.740 --> 38:28.000
websites, the moon, which
is often shown as a turtle

38:28.000 --> 38:30.280
with all the different
moon cycles and started

38:30.280 --> 38:32.380
thinking about, well,
what would this even look

38:32.380 --> 38:35.300
like if we had a timeline
that showed something

38:35.300 --> 38:38.540
like moon cycles rather
than the Julian calendar?

38:38.540 --> 38:41.480
We also looked at
different iconography and

38:41.480 --> 38:43.740
integrating the Ojibwe
language as well.

38:46.160 --> 38:49.160
Another challenge we have
is protecting Native Nations

38:49.160 --> 38:52.040
data. So tribes need to
protect their data. It's

38:52.040 --> 38:55.720
often been exploited by
governments. And even non-tribes,

38:55.720 --> 38:57.620
even all of these
marginalized communities have

38:57.620 --> 39:00.780
good reason to want to
protect their own data. And so

39:00.780 --> 39:03.380
this of course requires
respecting the knowledge, the

39:03.380 --> 39:06.420
sovereignty. A big one in
tribal communities is elders

39:06.420 --> 39:09.640
and tradition and then also
our non-human relatives.

39:09.640 --> 39:13.080
So in a lot of the communities
we work with up north,

39:13.080 --> 39:16.640
they really look at rice,
animals, plants, etc. as

39:16.640 --> 39:19.580
relatives rather than as
resources we would exploit.

39:20.600 --> 39:23.440
And then finally we have
this challenge of turning

39:23.440 --> 39:27.040
data to action. So like how
do we take data and make

39:27.040 --> 39:30.580
it into policies? What do
we have control over? How

39:30.580 --> 39:34.300
do we know where to actually
go and do something? So

39:34.300 --> 39:36.980
with Eclipse, we had some
pretty good success through

39:36.980 --> 39:40.160
our API where local news
would publish stories about

39:40.160 --> 39:42.580
it. And again, we would
see traffic on the site. We

39:42.580 --> 39:46.260
would see people locally
try and do things. And even

39:46.260 --> 39:48.380
the Chicago Department
of Public Health went to

39:48.380 --> 39:51.020
investigate one site that
we found had high pollution

39:51.020 --> 39:53.880
and change some of the
traffic patterns around there.

39:54.580 --> 39:57.240
For the Wild Rice
Project, what we've been

39:57.240 --> 40:01.430
looking into is... we
can do something called

40:01.430 --> 40:04.150
agenda alerts. And so
this is based on the

40:04.150 --> 40:08.510
Public Meeting Act,
which is a U.S. thing,

40:08.690 --> 40:11.010
United States thing, that
says that local governments

40:11.010 --> 40:13.490
who have public meetings,
so city council, town

40:13.490 --> 40:17.890
council, et cetera, they
have to tell you beforehand

40:17.890 --> 40:19.710
that the meeting is
happening and what's going to

40:19.710 --> 40:22.390
be discussed. And so based
on that, could we then

40:22.390 --> 40:24.630
alert people to say, hey,
they're going to have a

40:24.630 --> 40:27.350
meeting talking about this
lake you care about or this

40:27.350 --> 40:31.570
project you care about or
your town for example so

40:31.970 --> 40:34.270
i've been working on that
with one of my collaborators

40:34.270 --> 40:36.150
and there's a lot of
challenges right it sounds

40:36.150 --> 40:38.430
like everything it sounds
easy but it turns out that

40:38.430 --> 40:40.930
these agendas a lot of
them are kind of just like

40:41.140 --> 40:44.570
useless text um and so
this is an example of one

40:44.570 --> 40:47.190
and you can see that it's
like oh you know comments

40:47.190 --> 40:49.170
whatever and then there's
just a lot of numbers and

40:49.170 --> 40:52.750
addresses and you know It
provides challenges, and

40:52.770 --> 40:55.450
a lot of people now would
say, well, throw an LLM at

40:55.450 --> 40:57.290
it. Well, there's not
really enough text to do

40:57.290 --> 41:00.590
anything with it, maybe if
you read every agenda ever.

41:00.990 --> 41:03.770
And so we're working
on this now, trying

41:03.770 --> 41:07.510
to look at named
entities, which is towns,

41:07.630 --> 41:11.090
people, et cetera, and
then also looking to see if

41:11.090 --> 41:13.830
maybe the meeting minutes
that get published after

41:13.830 --> 41:16.990
the agendas can be used
to learn more about it.

41:17.970 --> 41:20.410
But again, open
challenges around action.

41:20.410 --> 41:22.650
One of the biggest
ones is the livelihood.

41:22.650 --> 41:24.510
A lot of the people in
these communities are

41:24.510 --> 41:28.070
working for the industries
that are polluting.

41:28.070 --> 41:30.090
And so their livelihood
depends on it, but

41:30.090 --> 41:32.570
their actual lives are
being harmed by it.

41:32.570 --> 41:34.550
There's also politics,
of course. Once you

41:34.550 --> 41:36.940
finally get inroads
with one mayor to put up

41:36.940 --> 41:38.450
censors, well, then
they get voted out and

41:38.450 --> 41:40.430
now you have the next
mayor to worry about.

41:40.530 --> 41:42.820
And a big one, of
course, is accuracy.

41:42.820 --> 41:45.610
Low-cost censor data
does not equal proof.

41:45.740 --> 41:47.510
So I'm going to skip
ahead to make sure we

41:47.510 --> 41:49.690
have enough time for
questions. But I really

41:49.690 --> 41:51.410
want to talk about
this last idea of

41:51.410 --> 41:53.990
what I'm calling
redefining local knowledge.

41:54.090 --> 41:57.590
And so we throw this
term around a lot in HCI.

41:57.590 --> 41:59.630
And one of the things I've
really been thinking about

41:59.630 --> 42:01.810
is like how we can
incorporate different kinds of

42:01.810 --> 42:04.520
knowledge. So one of them
is indigenous knowledge,

42:04.570 --> 42:08.090
which is basically like
ancestral knowledge that's been

42:08.090 --> 42:10.630
passed down through
generations about land. And

42:10.630 --> 42:14.170
usually it's oral tradition,
songs, stories, et cetera.

42:14.250 --> 42:16.890
And so the question
is, well, how might we

42:16.890 --> 42:19.650
use that? So I've been
working on collecting

42:19.650 --> 42:22.210
indigenous knowledge.
A lot of it is through

42:22.210 --> 42:24.890
books, for example,
online through songs.

42:25.030 --> 42:27.910
I had a student help do
some interviews about wild

42:27.910 --> 42:31.230
rice. And for example, this
might look like a traditional

42:31.230 --> 42:34.050
wild rice story where
Nanabuju, who's often the

42:34.050 --> 42:38.410
character in this story,
can't find food. He's getting

42:38.410 --> 42:41.090
annoyed, follows the ducks,
and they take him to a

42:41.090 --> 42:44.430
lake full of rice. And he
sees all the ducks and geese

42:44.430 --> 42:47.190
eating it. and now he knows,
oh great, there's rice

42:47.190 --> 42:50.190
here and the ducks and geese
eat it. So could we use

42:50.190 --> 42:53.290
that then to incorporate
something like a microphone

42:53.290 --> 42:56.470
into our sensing systems
to say, hey, we hear a lot

42:56.470 --> 42:59.770
of ducks and geese munching
on something. Maybe it's

42:59.770 --> 43:03.050
time to go harvest the
rice, for example, when we

43:03.050 --> 43:05.690
combine that with all of the
other information we have.

43:05.950 --> 43:07.990
Now the last quick thing
I want to talk about

43:07.990 --> 43:10.470
for local knowledge is
this idea of experience.

43:10.830 --> 43:15.930
So Cleo and I have been
working on a very strong,

43:16.090 --> 43:18.790
depressing project around
carceral facilities.

43:19.190 --> 43:23.250
And these are another huge
environmental justice issue

43:23.250 --> 43:26.310
where people are dying
because of heat, because of

43:26.310 --> 43:29.410
pests, because of illness,
because they're not being

43:29.410 --> 43:33.430
treated in a humane way. And
this is a particularly huge

43:33.430 --> 43:35.930
issue in Georgia where
we have a large carceral

43:35.930 --> 43:40.590
population and where we have
so many facilities that get

43:40.590 --> 43:43.670
super hot in the summer and
do not have any kind of air

43:43.670 --> 43:47.550
conditioning so we interviewed
19 formerly incarcerated

43:47.550 --> 43:51.550
people as you can see the
majority are black um which

43:51.550 --> 43:56.350
is probably not surprising
black low income uh etc

43:56.350 --> 43:59.870
and we asked them questions
around what their experiences

43:59.870 --> 44:02.850
had been and then if we
were to have things like

44:02.850 --> 44:05.570
environmental sensors or
health sensors what they would

44:05.570 --> 44:08.950
be comfortable with us with
the data that's collected.

44:08.990 --> 44:11.530
And an interesting finding
about the health wearables

44:11.530 --> 44:14.790
is that a lot of them
actually wanted their location

44:14.790 --> 44:17.070
tracked, which was surprising
for us because most of

44:17.070 --> 44:20.030
us would say, I don't know,
location feels very personal.

44:20.030 --> 44:22.110
And they cared about that
much more than something

44:22.110 --> 44:24.990
like sleep tracking, which
many of us like to have as

44:24.990 --> 44:27.790
a monitor for our health.
And what was interesting

44:27.790 --> 44:30.610
was that for location, for
example, someone said, well,

44:30.610 --> 44:32.930
this is so important. It's
like the key to safety

44:32.930 --> 44:34.910
because you can be forced
somewhere you can be drugged

44:34.910 --> 44:37.750
somewhere you could be you
know beaten up somewhere

44:37.750 --> 44:40.210
somewhere you're not supposed
to be and it's essential for

44:40.210 --> 44:44.070
your life and well-being for
officers and administration

44:44.070 --> 44:47.060
to know where you are and
then sleep which seems

44:47.060 --> 44:49.710
innocuous to us well actually
maybe you get in trouble

44:49.710 --> 44:51.990
because you didn't go to
sleep the right time or you

44:51.990 --> 44:55.670
didn't wake up at the right
time and so it really just

44:55.670 --> 44:58.460
highlights the importance
of learning from this lived

44:58.460 --> 45:01.690
experience and what that
form of local knowledge is.

45:02.170 --> 45:03.570
I have a lot of collaborators.

45:05.020 --> 45:06.810
So many of them are in here,

45:06.810 --> 45:08.510
which is amazing, so thank you.

45:09.830 --> 45:11.870
And yeah, so please, you

45:11.870 --> 45:13.570
know, ask questions, comments.

45:13.690 --> 45:15.690
I'll leave up the
contributions. I already

45:15.690 --> 45:18.110
know what my lab will
be called at MIT. If

45:18.110 --> 45:20.450
you hate your advisor
here, let me know.

45:21.430 --> 45:24.410
If you have any promising
students and we are

45:24.410 --> 45:27.870
thinking of a postdoc
and any of this speaks to

45:27.870 --> 45:30.580
you yeah please reach out
thank you all so much a

45:44.510 --> 45:47.210
question now that I ran
through the end yeah Brittany

45:47.530 --> 45:51.010
thank you for the talk um
this is just a simple question

45:51.010 --> 45:54.150
but for I think it was
the project was there a

45:54.150 --> 45:57.750
reason why specifically you
all chose to create a website

45:57.750 --> 46:00.610
like was there any data
that kind of led to that to

46:00.610 --> 46:03.870
say this would be a useful
technology for people. I

46:03.870 --> 46:05.910
know you said that like
people in a scanning circle.

46:05.910 --> 46:07.750
Yeah, yeah, that's a great
question. So the question

46:07.750 --> 46:10.290
was like, for the air quality
project, why a website?

46:10.820 --> 46:14.050
So there's a lot of ways
to answer that. I guess the

46:14.050 --> 46:16.290
most simple is like,
that's just what people do,

46:16.290 --> 46:19.550
which I know is a bad answer
for why to do something.

46:20.110 --> 46:25.910
But spatio-temporal data
is difficult to work with.

46:27.510 --> 46:31.410
And how you visualize both
space and time together

46:31.410 --> 46:33.370
is something I think
about a lot, and I don't

46:33.370 --> 46:36.430
think anyone's come up with
a great solution for it.

46:37.610 --> 46:40.310
It was all, you know, part
of it too is back to that

46:40.310 --> 46:43.320
issue of pacing. Like we
had a date that we agreed on

46:43.320 --> 46:45.270
deploying these, and so part
of it was like, oh my God,

46:45.270 --> 46:48.110
what's the fastest thing
that we can get out of this?

46:48.310 --> 46:50.170
But it's interesting
because like even

46:50.170 --> 46:53.030
for our wild rice
project, for example,

46:53.030 --> 46:57.370
what we have come up
with is a dashboard.

46:57.570 --> 47:01.370
The dashboard is just the
common view, and it's it's

47:01.370 --> 47:03.090
one of those like unfortunate
interface things where

47:03.090 --> 47:06.830
it kind of ***** but no
one has figured out a great

47:06.920 --> 47:10.130
alternative for it yet and
yeah I know that's probably

47:10.130 --> 47:15.070
not a satisfying answer.
I was just curious if like

47:15.070 --> 47:18.170
because I know you talked a
lot about having the community

47:18.170 --> 47:20.210
like yeah I didn't know
if it was something that

47:20.210 --> 47:22.510
came up. Yeah so one thing
we had thought about which

47:22.510 --> 47:25.290
especially working with the
bus shelters um they have

47:25.290 --> 47:28.510
like you know sort of spaces
for advertisements and

47:28.510 --> 47:30.510
stuff and so we had wondered
you know what if we could

47:30.510 --> 47:33.150
put like some sort of screen
that's showing you or even

47:33.150 --> 47:35.530
a small led that's showing
you things in real time

47:35.530 --> 47:37.750
that way you don't have to
connect to a website and

47:37.750 --> 47:40.770
you can see it while you're
there um i mean that's an

47:40.770 --> 47:43.330
area of research i would
love to explore and yeah i

47:43.330 --> 47:44.690
guess i'm allowed to say
what i want now like full

47:44.690 --> 47:48.050
disclosure msr shut that
project down abruptly and it was

47:48.050 --> 47:51.050
very upsetting and we were
in the midst of working with

47:51.050 --> 47:53.910
new york city like you know
planning oh what amazing

47:53.910 --> 47:56.890
times square installation
what we do and oh my god

47:56.890 --> 48:00.230
we're gonna be famous um but
like obviously that didn't

48:00.230 --> 48:02.530
happen um but i think you
know something like that

48:02.530 --> 48:04.730
could be really powerful where
it's like maybe you don't

48:04.730 --> 48:06.890
why even have to pull out
your phone we don't need

48:06.890 --> 48:09.590
to do that right why not
just be able to show people

48:09.590 --> 48:11.730
so that everyone can see
it and maybe you could even

48:11.730 --> 48:14.250
spark a conversation at
the bus shelter rather than

48:14.250 --> 48:17.800
have people just staring at
their tiktok or whatever yes

48:18.920 --> 48:22.490
you mentioned putting up
QR codes at the bus stops.

48:22.510 --> 48:24.970
Can you describe
what those were?

48:24.970 --> 48:27.590
Like, was it just a QR
code on a sheet of paper?

48:27.690 --> 48:29.070
Yeah, yeah. What did
that artifact look like?

48:29.070 --> 48:30.510
Yeah, that's a very
great question. So we

48:30.510 --> 48:32.210
had these little
stickers, because you have

48:32.210 --> 48:33.990
to, like, put it on the
pole, which is rounded.

48:33.990 --> 48:36.430
So we made these
stickers, and they said,

48:36.770 --> 48:38.370
they had, like, a
little picture of the

48:38.370 --> 48:39.890
sensor. Like, hey, this
sensor is measuring

48:39.890 --> 48:42.050
air quality. Scan
here to view it.

48:42.890 --> 48:47.750
Did you print out maps
at all? Like, we're just

48:47.750 --> 48:50.150
going to take, you know,
every week we're going to go

48:50.150 --> 48:53.270
out and stick up a new
map of you know that's a

48:53.270 --> 48:55.390
great idea yeah especially
in that that big space

48:55.390 --> 48:57.010
that would have been a
great idea yeah where maybe

48:57.010 --> 48:59.490
it's some sort of right
it's like somewhat real time

48:59.490 --> 49:02.530
but um yeah not having
to be a screen that could

49:02.530 --> 49:05.610
get damaged or something
i love that no we didn't

49:05.610 --> 49:07.370
think about it but i might
steal it for the future

49:08.190 --> 49:12.670
okay amy in terms of local
knowledge i think you spoke

49:12.670 --> 49:16.810
a lot to like the value of
taking like local knowledges

49:16.810 --> 49:19.790
and bring that into research
into policy like giving

49:19.790 --> 49:22.570
them that power of precision
in a way to be more

49:22.570 --> 49:25.470
politically powerful i'm
also curious like what like

49:25.470 --> 49:29.050
local community members
learned themselves from doing

49:29.050 --> 49:32.170
these sort of about more
than i mean yes obviously the

49:32.170 --> 49:34.130
precision to have that
political power in a way but

49:34.130 --> 49:37.730
like what yeah what they
learn about these concepts and

49:37.730 --> 49:40.770
the way in which integrating
more quote-unquote local

49:40.770 --> 49:43.650
traditions of knowledge helps
that process yeah that's

49:43.650 --> 49:48.150
a really great question
um i guess so far that so

49:48.150 --> 49:50.750
that particular part that i
think you're talking about

49:50.750 --> 49:53.370
around like integrating the
indigenous knowledge for

49:53.370 --> 49:56.550
example like that's still
pretty early on i think in

49:56.550 --> 49:58.870
terms of more broadly
though like what communities

49:58.870 --> 50:01.790
might be learning one of my
hopes having formerly been a

50:01.790 --> 50:04.910
teacher is that there can
be lots of educational

50:04.910 --> 50:09.790
opportunities and in an ideal
world like it's not sustainable

50:09.790 --> 50:12.410
for researchers to develop
these and keep them

50:12.410 --> 50:16.330
running we need to make them
then community run and owned

50:16.330 --> 50:18.910
and so i think in an ideal
world perhaps community

50:18.910 --> 50:22.330
members who are interested
are learning the skills to

50:22.330 --> 50:26.190
do the data analysis even
to make the sensors for

50:26.190 --> 50:28.370
example right so that way it
could be like hey let's help

50:28.370 --> 50:31.030
you prototype and get
through the initial process

50:31.030 --> 50:34.290
but now this can be a community
run project and a community

50:34.290 --> 50:37.070
owned project in addition
to the data part of it

50:38.650 --> 50:39.490
Yeah.

50:39.570 --> 50:42.370
Hi. Actually, I want to
continue asking a question

50:42.370 --> 50:45.230
on the QR code. Was
there also a concern of

50:45.230 --> 50:48.930
security and privacy? That's
why people did not scan?

50:49.030 --> 50:51.350
I think it was
during COVID, so I

50:51.350 --> 50:53.150
think there was
QR code fatigue.

50:53.150 --> 50:55.110
And I think most
people, I wouldn't walk

50:55.110 --> 50:57.330
up and just scan a
random QR code. Right?

50:57.470 --> 50:59.530
Like, everyone remember
that Super Bowl

50:59.530 --> 51:01.470
ad where they just
had the QR code back?

51:01.470 --> 51:03.330
I wasn't going to
scan that, you know?

51:03.450 --> 51:05.810
So I think that's part. And
also, probably people just

51:05.810 --> 51:09.210
didn't even see it. Like,
you know, if you actually

51:09.210 --> 51:12.090
sat and just watch people
walk around a city, what

51:12.090 --> 51:14.160
you'll see is that everyone's
in their phone anyway.

51:14.210 --> 51:15.850
So yeah.

51:16.150 --> 51:17.110
Yes.

51:17.640 --> 51:19.790
Yeah, and then I'll go with
that side. Sorry, yeah.

51:20.250 --> 51:23.530
About co-designing
with the communities,

51:24.010 --> 51:26.830
I was wondering how
much the visual,

51:27.170 --> 51:29.950
taking their cultural
traditions and incorporating

51:29.950 --> 51:32.630
that into the visual
aspects of things, of

51:32.630 --> 51:36.470
the tools, how much that
trusted trust with those

51:36.470 --> 51:39.410
communities and also
if you think increased

51:39.410 --> 51:42.310
trust for those communities
and better results?

51:42.730 --> 51:45.330
Yeah, yeah, great question.
So the question was if

51:45.330 --> 51:49.910
the co-designed with
especially community visuals

51:49.910 --> 51:52.930
knowledge might increase
trust. So we did do a user

51:52.930 --> 51:55.270
study with this dashboard
where we had some of the

51:55.270 --> 51:58.450
iconography and color
schemes, et cetera. We've also

51:58.450 --> 52:01.070
done some small user studies
about language. So the

52:01.070 --> 52:04.120
language part is a completely
different beast because

52:04.120 --> 52:07.390
so many people, unfortunately,
no longer know the

52:07.390 --> 52:09.950
language because of
colonization, assimilation, etc.

52:10.430 --> 52:12.790
With the cultural elements,
we didn't specifically

52:12.790 --> 52:15.810
ask about trust, but
people did remark that they

52:15.850 --> 52:17.910
liked the things that we
were doing. And I think

52:17.910 --> 52:20.720
it spoke to some of the
colors or some of the

52:20.720 --> 52:23.150
familiarity that they have
with things. One thing that

52:23.150 --> 52:27.670
we're working on now is
hiring an Ojibwe designer

52:28.070 --> 52:33.030
to help put even more of
this and have it fit in

52:33.030 --> 52:35.910
more with some of the
things they have. So, yeah,

52:35.910 --> 52:37.390
that's a great question,
and I think that's something

52:37.390 --> 52:38.630
we could explore in the
future. I'm going to

52:38.630 --> 52:40.610
go this side, and then
I'll come back to you. Yes.

52:59.150 --> 53:04.430
yeah yeah that is a great
question um that so yeah i

53:04.430 --> 53:08.230
mean it's funny if you talk
to like um i don't know

53:08.230 --> 53:11.050
how to if you talk to the
more senior researchers

53:11.050 --> 53:13.630
and sensors if you ever go
to a conference they love

53:13.630 --> 53:16.110
to talk about this thing
called sensor dust which is

53:16.110 --> 53:19.130
like you know the vision
that they had 20 30 years

53:19.130 --> 53:21.410
ago where sensors would be
so tiny they would just be

53:21.410 --> 53:23.810
floating around in the
air all around us which is

53:23.810 --> 53:26.090
absurd who wants to be
breathing that in but whatever

53:26.550 --> 53:30.450
and so if you ask a censor
person they would say yes

53:30.450 --> 53:32.850
but if you ask me like of
course not right like what

53:32.850 --> 53:36.150
city is going to have budget
to have a censor on every

53:36.150 --> 53:40.870
block even and so this is
where we the question of like

53:40.870 --> 53:42.910
how many do we need and
where do we need them is

53:42.910 --> 53:45.650
something I looked at in my
dissertation and the answer is

53:45.650 --> 53:49.650
who knows it's almost certainly
highly specific on the

53:49.650 --> 53:54.090
city itself or the place
you're looking in and so like

53:54.090 --> 53:56.750
what I looked at in my
dissertation was okay well one

53:56.750 --> 53:59.350
we want some idea of like
representative data so if

53:59.350 --> 54:03.010
I'm measuring over here is
that good enough for me to

54:03.010 --> 54:06.130
know what's happening five
blocks away for example and

54:06.130 --> 54:09.190
the answer is it probably
depends on the layout of a

54:09.190 --> 54:13.210
city and so there's different
types of street layouts

54:13.210 --> 54:15.050
like if you think about you
know there's some streets

54:15.050 --> 54:17.350
that are really narrow that
have tall buildings versus

54:17.350 --> 54:20.150
streets that are really wide
and have parks and so the

54:20.150 --> 54:22.710
way that like pollution
moves in those can be very

54:22.710 --> 54:25.970
different for example um there's
also like the very practical

54:25.970 --> 54:28.570
question of well where
are people right if we're

54:28.570 --> 54:31.610
measuring for people does
it really matter to measure

54:31.610 --> 54:34.710
something if people are never
over there for example um

54:34.710 --> 54:37.090
so usage is a big one and
then of course this whole

54:37.090 --> 54:39.070
idea of like you know we
talked about connectivity and

54:39.070 --> 54:42.210
charging issues like if we
actually knew where we would

54:42.210 --> 54:45.470
have these resources, that
could also play into it.

54:45.470 --> 54:48.810
And so, you know, I think
there's, I know that's not a

54:48.810 --> 54:51.730
solid answer for you, but
it really is a nuanced thing

54:51.730 --> 54:53.610
and it probably does matter
on budget. And I think

54:53.610 --> 54:55.830
there is such thing as overpay,
right? Like we also have

54:55.830 --> 55:00.090
to think about the, like
collecting even more data,

55:00.090 --> 55:02.150
adding to more data centers,
adding to more electronic

55:02.150 --> 55:05.710
waste. Like that's not the
solution necessarily, but

55:05.710 --> 55:08.210
having some sort of computational
model or at least like

55:08.210 --> 55:10.550
confidence that, hey,
something that's happening over

55:10.550 --> 55:13.110
there, I feel pretty be
confident that it's, I know

55:13.110 --> 55:15.330
what's happening to me. I
think that would be the goal.

55:16.270 --> 55:17.050
Yes?

55:17.360 --> 55:19.330
First of all, you're a great
speaker. Oh, thank you.

55:20.030 --> 55:22.710
And I like the fact that you
need the term environmental

55:22.710 --> 55:24.650
justice people are
because of political

55:24.650 --> 55:27.350
pressure. Yeah, I'll end up
on a blacklist, whatever.

55:29.250 --> 55:33.730
You touched upon it towards
the end of your talk was,

55:33.730 --> 55:36.890
have you done more studying
about translating? You

55:36.890 --> 55:38.730
can have all the great
data in the world, blah,

55:38.730 --> 55:41.450
blah, blah. lot, but
translating that into policy,

55:41.850 --> 55:43.390
so what? Yes.

55:43.610 --> 55:47.070
Yeah, so with the Wild
Rice Project, we're working

55:47.070 --> 55:49.210
with, we have a governance
team, and so we're

55:49.210 --> 55:53.310
working with them to try
and determine that so what,

55:53.310 --> 55:56.870
and what it involves, what
their work is, is a ton

55:56.870 --> 56:02.250
of reading, like, legal
policies, tribal agreements,

56:02.250 --> 56:05.510
you know, as far back as
the 1800s, for example,

56:05.630 --> 56:07.610
and then sort of
determining, like, okay,

56:07.610 --> 56:09.550
these are all the
different intersecting

56:09.550 --> 56:11.290
things and where we
might be able to have

56:11.290 --> 56:13.290
a play. I had a great
meeting this morning

56:14.170 --> 56:15.370
with Jackie

56:16.090 --> 56:19.790
from the South River
Water Alliance.

56:19.790 --> 56:21.650
Nope, something like
that. I had a great

56:21.650 --> 56:23.610
meeting this morning
where we were sort of

56:23.610 --> 56:25.890
talking about this and
it sounds, basically

56:26.260 --> 56:28.390
it takes a lot of work,
it takes a lot of reading

56:28.390 --> 56:30.630
and it takes, as far
as I learned from that

56:30.630 --> 56:34.390
conversation, the wings
to sue people or at least

56:34.390 --> 56:36.690
align with people who
are going to sue people.

56:39.010 --> 56:42.150
And so it seems that,
you know, and at least in

56:42.150 --> 56:44.030
working with tribes, that
certainly is the direction

56:44.030 --> 56:46.390
a lot of them are planning
to go. Like one of the

56:46.390 --> 56:49.070
tribes we work with,
they're somewhat famous now.

56:49.170 --> 56:52.630
It's called Bad River. They
have a documentary about

56:52.630 --> 56:55.050
them fighting against the
building of this pipeline.

56:55.050 --> 57:00.150
And so, like, they are,
that's their goal is to sue

57:00.150 --> 57:02.550
and say, hey, what you
guys are doing is violating

57:02.550 --> 57:06.230
our sovereignty and the
agreements that we have. But,

57:06.230 --> 57:09.050
yeah, it's so interesting
because, like, even in

57:09.050 --> 57:10.710
the meeting this morning
and even in working with the

57:10.710 --> 57:12.390
governance folks, like,
and trying to think, well,

57:12.390 --> 57:15.170
how can we help, right? Like,
could we make tools that

57:15.170 --> 57:17.570
read through these
documents? Sure, but could we

57:17.570 --> 57:19.800
trust them and know that
we're not missing something

57:19.800 --> 57:22.140
important or how can we
help make these inferences?

57:22.840 --> 57:24.670
So, yeah, it's something
I still wonder about. And

57:24.670 --> 57:26.990
I know, like, Haisley, for
example, is working on a

57:26.990 --> 57:29.070
project around data centers
and we're thinking, well,

57:29.070 --> 57:31.710
maybe there's something
about making tools for

57:31.710 --> 57:35.850
policy makers to see and
be like wait this is what's

57:35.850 --> 57:37.690
happening like that's
crazy because we know they

57:37.690 --> 57:40.170
don't read all the bills and
stuff anyway too so maybe

57:40.170 --> 57:42.170
part of it is figuring
out how we surface things

57:42.170 --> 57:44.950
better to them um so i
guess the answer is yes but

57:44.950 --> 57:49.110
not enough uh that's that's
the next big step yeah in

57:49.110 --> 57:51.610
the back i have a first
of all thank you for your

57:51.610 --> 57:55.370
talk um i have a more
practice oriented question uh

57:56.210 --> 57:59.990
i i'm currently trying to
do like more co-design in my

57:59.990 --> 58:03.590
research and uh i wanted to
ask like when When you do

58:03.590 --> 58:05.820
co-design with community
members, what do those

58:05.820 --> 58:08.530
engagements actually look like
in practice? Like, are you

58:08.530 --> 58:11.590
doing workshops, are you
doing interviews, et cetera?

58:11.650 --> 58:15.910
And after or during
those engagements, how

58:15.910 --> 58:17.850
do you decide when
to defer to community

58:17.850 --> 58:20.630
members for design or
technical decisions?

58:20.630 --> 58:23.130
Yeah, that's a great
question. So what the

58:23.130 --> 58:27.110
co-design actually
looks like, it's really

58:27.110 --> 58:30.810
tough. So I've done
very few of the, like,

58:32.090 --> 58:32.730
typical,

58:32.990 --> 58:34.250
I don't know if it's
typical, but, like, the

58:34.250 --> 58:37.810
often used HCI, like,
co-design things that

58:37.810 --> 58:40.530
people would say, like
the card sorting or the,

58:40.530 --> 58:42.690
you know, workshop.
I'm familiar with them.

58:43.010 --> 58:45.690
I encourage some of my
students to look at them.

58:45.690 --> 58:49.130
But for a lot of the
communities we've worked with,

58:49.950 --> 58:54.450
part of it is that, one,
they're more our collaborators

58:54.450 --> 58:58.830
than communities, if
that makes sense. And

58:58.830 --> 59:00.690
so, like, a lot of them,
for example, our tribal

59:00.690 --> 59:03.490
partners, we include them
as co-authors on our paper.

59:03.810 --> 59:06.840
We're not running
sessions where we are

59:06.840 --> 59:09.690
compensating them for an
hour of their time. we're

59:09.690 --> 59:12.270
meeting with them every
week, calling them

59:12.270 --> 59:13.870
on a lot of questions.
They're calling us

59:13.870 --> 59:15.830
when they have a question
there in our Slack.

59:16.290 --> 59:17.410
And so,

59:18.250 --> 59:21.160
I think part of, a lot
of it has to do with what

59:21.160 --> 59:23.610
sort of communities you're
working with and to what

59:23.610 --> 59:25.880
extent you want to do a co
-design. For like, starting

59:25.880 --> 59:28.890
out, you know, a small
project, like yes, I think

59:28.890 --> 59:31.590
like a workshop, a part
of some sort of validated

59:31.590 --> 59:35.690
activity makes a lot of
sense. for the incarceration

59:35.690 --> 59:37.770
project, like Theo and
I did semi-structured

59:37.770 --> 59:41.490
interviews that we put
together a real guide for it.

59:41.490 --> 59:44.650
And we compensated people
because that was a,

59:44.650 --> 59:46.930
hey, we're meeting
with you long time, and

59:46.930 --> 59:48.610
we're going to compensate
you for your pain.

59:48.610 --> 59:51.630
And for the more long-term
partnerships, what has worked

59:51.630 --> 59:54.520
for me is more of like,
hey, we are collaborators.

59:55.030 --> 59:56.350
And so,

59:56.570 --> 59:57.950
again, you end up with weird

59:57.950 --> 01:00:00.010
things around IRB and stuff.

01:00:01.250 --> 01:00:03.730
So, yeah, another thing
that I've learned, though,

01:00:03.730 --> 01:00:06.470
too, is, and there's
a great paper on this,

01:00:06.770 --> 01:00:09.610
Justice Design
Oriented Learning.

01:00:14.910 --> 01:00:19.470
And so, that paper highlights
something that we found

01:00:19.470 --> 01:00:21.490
in our work with tribes,
which is that, like, a lot

01:00:21.490 --> 01:00:25.370
of the ways that we in HCI
do these sorts of design

01:00:25.370 --> 01:00:28.550
activities don't necessarily
equate to how communities

01:00:28.550 --> 01:00:31.110
work. And so a good example
of tribes is that a lot

01:00:31.110 --> 01:00:34.730
of them prefer to do communal
feedback. And so, you

01:00:34.730 --> 01:00:36.190
know, we've talked about,
like, hey, let's bring the

01:00:36.190 --> 01:00:38.090
dashboard and, like, do a
little interview. They're

01:00:38.090 --> 01:00:40.370
like, actually, no, why
don't we have the, you know,

01:00:40.370 --> 01:00:43.070
whole town, whoever wants
to come, come sit, and you

01:00:43.070 --> 01:00:45.630
present in front of everyone
and get their feedback.

01:00:45.630 --> 01:00:47.690
They're like, it's the
talking circles. They're

01:00:47.690 --> 01:00:50.470
like, this would be me
talking at you. Like, no,

01:00:50.470 --> 01:00:52.570
let's sit in a circle and
all talk together. And

01:00:52.570 --> 01:00:54.630
so I think that's another
good thing, too, is, like,

01:00:54.630 --> 01:00:56.410
once you identify the
community, trying to

01:00:56.410 --> 01:01:00.060
determine how it is that
they prefer to participate.

01:01:00.770 --> 01:01:02.640
And then in terms of,
like, defined expertise,

01:01:02.640 --> 01:01:04.050
I mean, I think we
always have to defer

01:01:04.050 --> 01:01:06.610
their expertise. Carl
has great work on this,

01:01:06.610 --> 01:01:08.430
too, Carl DeSalvo, where
it's like, you know,

01:01:08.690 --> 01:01:11.810
maybe the output isn't,
quote-unquote, novel

01:01:11.810 --> 01:01:14.690
research, but what drives
you, right? What motivates

01:01:14.690 --> 01:01:16.470
you? I think that's the
big question. Of course,

01:01:16.470 --> 01:01:18.050
technical expertise, you
know, if they're like,

01:01:18.050 --> 01:01:20.510
hey, build a spaceship,
you know, I don't think I

01:01:20.510 --> 01:01:24.050
can do that. But most of
the time, requests are,

01:01:24.050 --> 01:01:26.510
you know, reasonable. And
I think then it can be

01:01:26.510 --> 01:01:28.910
a fun challenge to sort
of determine, you know,

01:01:28.910 --> 01:01:30.610
oh, well, based on what
you said, here's what I

01:01:30.610 --> 01:01:33.270
think would work, and,
yeah, find some happy ****.

01:01:36.090 --> 01:01:38.850
I've done homework
on this, but I did

01:01:38.850 --> 01:01:40.250
notice that you were
going to be a middle

01:01:40.250 --> 01:01:41.570
school teacher at
one point. Yeah.

01:01:41.660 --> 01:01:43.870
That is the Lord's work,
and I want you to believe

01:01:43.870 --> 01:01:46.990
in God that he did not
do. But I saw this, a

01:01:46.990 --> 01:01:49.950
lot of this stuff would
be very applicable to a

01:01:50.010 --> 01:01:53.950
middle school-type curriculum,
and having, especially

01:01:53.950 --> 01:01:56.030
with the, I was
thinking about the Rice

01:01:56.950 --> 01:01:59.510
Project, where you could
have the kids go out in

01:01:59.510 --> 01:02:02.350
canoes and play stuff,
and it would be a project

01:02:02.350 --> 01:02:05.670
that would build community,
and there's a, there,

01:02:06.510 --> 01:02:08.630
you did, you know
what it's like,

01:02:08.630 --> 01:02:10.490
those kids love
that kind of ****,

01:02:10.650 --> 01:02:13.950
that age just, it's very
exciting about life,

01:02:13.950 --> 01:02:17.330
and it would be a great
way, It's also a great

01:02:17.330 --> 01:02:19.810
way for the elders in the
community, I'm not talking

01:02:19.810 --> 01:02:26.390
about elders in particular,
to be, to integrate

01:02:26.390 --> 01:02:29.350
with their young people.
Yeah, absolutely.

01:02:29.350 --> 01:02:31.150
There's a lot of that.

01:02:36.600 --> 01:02:39.380
A lot of this could be,
I'm looking at it, I

01:02:39.380 --> 01:02:42.260
have a background in
wireless communication.

01:02:42.780 --> 01:02:45.080
A lot of this could be
dumbed down a lot. You

01:02:45.080 --> 01:02:47.800
know, you don't need as
much worry about this

01:02:47.800 --> 01:02:49.080
and that and the other.
but there's a lot of

01:02:49.080 --> 01:02:51.420
it that can be very basic
in terms of sensors.

01:02:51.420 --> 01:02:54.340
Sensors can be a lot cheaper
than what people can do.

01:02:54.340 --> 01:02:56.740
But I'm really intrigued
by this. I'll talk to you

01:02:56.740 --> 01:02:59.320
all. Yeah, thank you. Yeah,
no, and that's, you know,

01:02:59.320 --> 01:03:01.140
there's never enough time
to say everything you want

01:03:01.140 --> 01:03:03.800
to do, but that is why, you
know, the education is one

01:03:03.800 --> 01:03:05.740
of the E's in the future
of that name because that's

01:03:05.740 --> 01:03:09.180
so important to me. Like,
I love, I don't love kids.

01:03:09.180 --> 01:03:12.220
My God, they're terrible.
But I loved being a teacher

01:03:12.220 --> 01:03:14.570
and figuring out how to
make things fun for them.

01:03:14.570 --> 01:03:18.200
And, yeah, like, even, you
know, what Josiah and I have

01:03:18.200 --> 01:03:20.580
a couple times now run a
workshop up north where we

01:03:20.580 --> 01:03:23.220
use micro bits, which are
these very low-cost sensors

01:03:23.220 --> 01:03:25.600
made by Microsoft, and you
can use block coding to

01:03:25.600 --> 01:03:27.880
program them. And I've
figured out how to make those

01:03:27.880 --> 01:03:30.720
work with some water-quality
sensors to get them out.

01:03:31.080 --> 01:03:33.020
And, yeah, that's something
I'm super interested

01:03:33.020 --> 01:03:35.360
in, like, even how could
we make, like, some sort of

01:03:35.360 --> 01:03:37.920
low-cost toolkit? Could
we get kids to be really

01:03:37.920 --> 01:03:41.220
thinking of the enclosures?
And then also, too, you

01:03:41.220 --> 01:03:43.400
know, I think in terms of
touching on the expertise,

01:03:43.400 --> 01:03:45.430
like, these are also
people who live in the

01:03:45.430 --> 01:03:47.640
communities, who know what
to look for, who know what

01:03:47.640 --> 01:03:49.280
they want to measure,
where they want to measure

01:03:49.280 --> 01:03:51.800
things. And so tapping
into that form of expertise

01:03:51.800 --> 01:03:54.660
as well, I think, is super
useful. Yeah, thank you.

01:03:56.520 --> 01:03:57.540
Yeah, thanks.