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RAJESH KASTURIRANGAN: My
name is Rajesh Kasturirangan.

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I'm one of the
co-founders of ClimateX,

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which is one of the co-sponsors
of this event along with Fossil

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Free MIT and many, many other
organizations on the MIT

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campus.

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We also have non-MIT people
here, several of whom--

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some of whom are MIT alums.

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So Jeff Warren is
one of our speakers.

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Britta Voss, who is on Skype
over there is another speaker.

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And then we have Nathan
Phillips and Audrey Schulman.

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So we have a really,
really fantastic lineup.

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But let me just explain
what we are doing and why.

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So ClimateX-- the idea is to
create an open climate learning

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platform for the whole world,
but starting with the MIT

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community and then
broadening that

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to the greater Boston area.

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So IAP, as some of you know,
is the Independent Activities

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Period at MIT.

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And that's the time when we
do all kinds of fun things.

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And there are many, many
climate-related courses

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being offered, which we
decided why not bring them

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under one umbrella and
call it The Climate IAP.

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So if you go to
sites.google.com/cliap you will

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see all of the courses
that are being organized.

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And so that's across
the spectrum, everything

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from climate science, to
policy, to energy negotiations

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in places like Mexico.

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So what we're doing
here is to say

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how can citizens
directly take action

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which is grounded in science?

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And we have actually some
fantastic speakers here today

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who have contributed to
that in many different ways.

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Our first speaker, who will
be introduced by Britta,

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will be Jeff Warren.

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And Jeff Warren is one of the
founders of Public Lab, which

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does, you could say,
community science

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around environmental questions,
both building the hardware that

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allows you to sense
environmental variables

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and the discussion and
analysis that comes

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from collecting that data.

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We have Nathan Phillips
and Audrey Schulman,

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who have done some
great work together

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on gas leaks in the
greater Boston area.

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And those gas leaks will be the
focus of not just this session,

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but also the next three.

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So we have three more
sessions after this one.

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There's one on the 23rd,
which is a data hackathon.

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So we're going to take a dump
of data from Audrey and Nathan,

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and we're going to do really
fantastic things with it.

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And then, if you're really
interested in seeing where

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these gas leaks are, we're going
to go on a tour on the 30th

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across the
Cambridge-Somerville area

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and do some gas
sensing on our own.

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And once that's
done, we're going

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to come back on
the 1st of February

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and say, how do we take this
and make that work for us

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in the public interest, right?

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And so generally,
I think the flow

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that we are trying to prototype
here in these four sessions

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is that citizens can work with
scientists and policymakers

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and others to directly
take charge of the climate

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challenges that affect
them wherever they are.

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And that by doing so, we can
contribute to climate action,

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but climate action that's
grounded in knowledge

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and not just pure advocacy.

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So I think that's a really
fantastic new opportunity that

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did not exist even
a few years ago.

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So I'm really, really
happy that we have

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a wonderful cast of speakers.

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I'm going to turn it
over to Britta Voss

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to introduce today's session.

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BRITTA VOSS: Great.

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All right.

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Thanks, Rajesh.

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Can everybody hear me?

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RAJESH KASTURIRANGAN: Yes.

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BRITTA VOSS: OK.

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So my name is Britta Voss.

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And I'm an MIT alum from 2014.

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So I just wanted to
start off with a sort

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of a brief overview
of our motivation

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and the idea behind
Community Science.

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And so we called this
From Community Science

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to Community Action.

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And that really gets at
sort of a larger motivation

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for this series of seminars--
of taking science and putting

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it to use for people.

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And it gets at
the mission of MIT

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as an institution of using
science for [INAUDIBLE]..

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I just want to start off
really, really broad here

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and ask the question of
what is science even for?

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Why do we have science?

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And my interpretation
of this is that humans

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are naturally
curious, and we want

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to understand the
world around us.

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And we also have needs.

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We need food and shelter
and transportation.

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And so science has this
double purpose for humanity.

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It feeds our curiosity, but it
also helps us solve problems.

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And it gives us a
process and a framework

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for addressing both
of those issues.

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And we all know
that science is very

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important in modern society.

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It's pretty much everywhere
you go, from your smartphones

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to social networking
to the systems

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and the infrastructure to
make modern life possible.

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And although we're all
very aware of that,

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very few people have
a direct relationship

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with science, either by doing
it themselves in their day

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to day lives, or even the
other people in their lives.

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And so another motivation
for this seminar series

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is that we're looking
for an angle that

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will help us make science
more relevant to people,

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make people care
more about science,

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because it has a very
important role in our society.

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And despite how
important science is,

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we all know that
science is often

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misused and mischaracterized
at shockingly high levels

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of our leadership.

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When you see very prominent
people making comments

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about scientifically
false issues,

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and even to the point of someone
like a US senator bringing

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a snowball to the
floor of the Senate

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to prove that climate
change is false.

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So there's obviously
a lot that needs

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to be done to make
society more aware of

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and informed about science.

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And so how can community
science address that?

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Community science
is a way of making

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science speak for communities.

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So climate change is probably
the best way, or the best

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example, of an area of science
where community involvement

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is critical.

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Because here, for
example, you can

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see the effects of climate
change on agriculture

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affect people's livelihoods.

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They affect the economy.

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And people who depend on
agriculture, which is not just

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all of us, the food
we eat, but people

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who make their livelihood
off of farming,

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need to understand how
climate change is affecting

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agricultural productivity
from droughts and wildfires

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and all sorts of issues.

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And so science can
help them with that

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if it is directly
addressing their needs.

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And then just a
few more examples--

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climate change is
affecting water temperature

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in rivers which has effects
on migratory fish populations

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that serve as important
cultural and economic basis

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for Native American populations.

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Nuisance flooding in
cities like Boston,

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and especially in South Florida,
is becoming a big problem

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for quality of life and economic
vitality in a lot of areas.

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Communities in the
Arctic are literally

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falling into the sea
in some places because

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of thawing permafrost.

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And then, of course,
in northern Alberta,

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you have tar sands mining
that's wiping out the forests,

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and it's dumping lots of
toxins into local rivers.

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And these toxins are going
downstream and making

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first nations communities sick.

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And so by producing independent
science for those groups,

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you can help them fight
back against these sorts

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of environmental threats.

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Communities living downwind
of coal-fired power plants

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similarly are at
serious risk of things

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like mercury contamination,
articulate aerosols,

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and other negative
health effects.

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And so if these communities
have tools of science,

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they might be able to
file lawsuits or come

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to their policy makers
and say that they need

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a certain regulation or policy.

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And another good
example, of course,

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is fracking, where the local
communities, especially

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if there's wastewater
injection going on,

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might be at risk for ground
water contamination, irregular

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seismic activity, and lots
of other environmental risks.

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So the motivations
for community science

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would be empowering
communities by giving them

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ownership of their
data and responding

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to their specific needs.

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And with respect
to the scientists,

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it increases public
awareness and interest

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in science, which is
important to making sure

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that science is still a
part of decision making

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and that science is
supported long term.

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And also importantly,
especially in the context

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of climate sciences,
making sure that scientists

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have access to local knowledge
that they might not otherwise

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be aware of.

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But of course, there's
also challenges.

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So just like with
traditional science,

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community science needs to
ensure the data is high quality

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and that it can be used for the
purposes of the community that

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needs it.

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For instance, that it will
hold up in a court of law.

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These projects need to
have long term support.

00:10:16.450 --> 00:10:19.255
So if you're looking at a
long term monitoring program,

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it can be hard to make sure
that that's financially

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viable over the long term.

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And then, the community's
needs might change over time,

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if the environmental
threats change,

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or if the make up of
the community changes.

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And so research projects need
to be able to respond to that.

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And I'm sure Jeff can
talk more about this--

00:10:37.600 --> 00:10:40.070
just a few ideas
about what can make

00:10:40.070 --> 00:10:42.210
community science successful.

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A few key factors are making
data and methods open source

00:10:46.370 --> 00:10:49.085
so they're freely available
and open for discussion.

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And similarly,
open communication

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between the community
members and the scientists

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themselves to make sure that
everyone is working together

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and not for their own purposes.

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And probably the
most important thing

00:10:59.715 --> 00:11:01.090
is making sure
that the community

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is involved from
the planning stages

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and not just
brought in later on.

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And that's basically
the key difference

00:11:07.290 --> 00:11:09.960
between community science
and what's usually

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known as citizen science.

00:11:12.510 --> 00:11:15.210
And finally, just in terms
of the appeal of community

00:11:15.210 --> 00:11:17.210
science, it's important
to encourage creativity,

00:11:17.210 --> 00:11:21.460
both from scientists
and community members.

00:11:21.460 --> 00:11:23.989
And I think one of the really
important aspects of community

00:11:23.989 --> 00:11:25.905
science is that it can
be a synthesis of tools

00:11:25.905 --> 00:11:29.490
and ideas from different fields
that might not happen naturally

00:11:29.490 --> 00:11:33.300
in traditional
scientific enterprise.

00:11:33.300 --> 00:11:37.212
So just, finally, some
examples-- there's

00:11:37.212 --> 00:11:38.420
probably many more out there.

00:11:38.420 --> 00:11:40.890
But Public Lab, as
Rajesh mentioned,

00:11:40.890 --> 00:11:43.984
you're going to hear from
Jeff about it pretty soon.

00:11:43.984 --> 00:11:45.900
And then there's also
the EarthWorks Community

00:11:45.900 --> 00:11:49.340
Empowerment Project, which gives
these forward-looking infrared

00:11:49.340 --> 00:11:53.550
cameras to communities
that want to monitor

00:11:53.550 --> 00:11:56.730
air balloons from local
operations such as fracking.

00:11:56.730 --> 00:11:59.670
And then one I just learned
about is Safecast, which

00:11:59.670 --> 00:12:03.740
is in response to the Fukushima
nuclear meltdown, which

00:12:03.740 --> 00:12:06.570
is getting communities
scientific tools for monitoring

00:12:06.570 --> 00:12:09.000
radiation contamination
in their communities.

00:12:09.000 --> 00:12:12.760
So with that, I will
turn it over to Jeff

00:12:12.760 --> 00:12:17.070
to tell you about some more
specific tools for community

00:12:17.070 --> 00:12:17.750
science.

00:12:17.750 --> 00:12:24.330
[APPLAUSE]

00:12:24.330 --> 00:12:28.180
JEFF WARREN: You know, as Britta
said-- thank you, Britta--

00:12:28.180 --> 00:12:30.607
I'm one of the
founders of Public Lab.

00:12:30.607 --> 00:12:31.690
There were seven founders.

00:12:31.690 --> 00:12:34.296
And I'll get into a
little bit about where

00:12:34.296 --> 00:12:35.170
Public Lab came from.

00:12:35.170 --> 00:12:40.062
But I really wanted
to talk about

00:12:40.062 --> 00:12:41.770
what makes Public Lab
different, and what

00:12:41.770 --> 00:12:43.660
that has to do with
some of the topics

00:12:43.660 --> 00:12:47.690
that we're going to dive
into in this course.

00:12:47.690 --> 00:12:49.810
I titled the talk
Renegotiating Expertise.

00:12:49.810 --> 00:12:52.510
Because I think there's
kind of this moment

00:12:52.510 --> 00:12:55.270
we're in now where
people are beginning

00:12:55.270 --> 00:13:00.520
to be more aware of the
mechanisms of expertise

00:13:00.520 --> 00:13:05.570
and where they are working and
where they need improvement.

00:13:05.570 --> 00:13:09.180
And so I had some thoughts
on this, and these are--

00:13:09.180 --> 00:13:10.390
yeah, they're preliminary.

00:13:10.390 --> 00:13:12.460
So I'm eager for the
discussion portion

00:13:12.460 --> 00:13:15.930
of the talk to just sort of dive
into some of these questions.

00:13:15.930 --> 00:13:21.970
And also, they're not
necessarily right.

00:13:21.970 --> 00:13:23.470
But I'm going to
put them out there.

00:13:23.470 --> 00:13:26.540
And I'm eager to
hear your thoughts.

00:13:26.540 --> 00:13:30.640
So Public Lab does what
we call community science.

00:13:30.640 --> 00:13:36.080
And this involves supporting
community knowledge production,

00:13:36.080 --> 00:13:38.680
which means creating
bridges and shared spaces

00:13:38.680 --> 00:13:42.500
between formal expertise
and community needs.

00:13:42.500 --> 00:13:44.770
So in the picture
above, you can see

00:13:44.770 --> 00:13:47.080
a group that is on the Gowanus
Canal in Brooklyn, which

00:13:47.080 --> 00:13:48.880
is a Superfund site.

00:13:48.880 --> 00:13:52.030
It's heavily contaminated
with polyaromatic hydrocarbons

00:13:52.030 --> 00:13:53.770
and raw sewage.

00:13:53.770 --> 00:13:56.500
I think somewhere in the
order of 300 million gallons

00:13:56.500 --> 00:13:58.690
of raw sewage go into
the canal every year.

00:13:58.690 --> 00:14:01.090
And that's actually
part of how the New York

00:14:01.090 --> 00:14:02.080
sanitary system works.

00:14:04.780 --> 00:14:08.790
I don't think there are any
current plans to change that.

00:14:08.790 --> 00:14:11.200
That's it, functioning properly.

00:14:11.200 --> 00:14:14.770
But this picture is actually
the day after Hurricane Sandy.

00:14:14.770 --> 00:14:18.250
And folks in the
Brooklyn sort of chapter,

00:14:18.250 --> 00:14:20.970
or sort of local
group of Public Lab--

00:14:20.970 --> 00:14:23.230
Public Lab's an open
community, so anyone can join--

00:14:23.230 --> 00:14:25.870
went out in canoes, as they had
done many times before in part

00:14:25.870 --> 00:14:27.880
of their monitoring
of the cleanup,

00:14:27.880 --> 00:14:31.150
and took a bunch of remarkable
images of lots of stuff

00:14:31.150 --> 00:14:33.072
having been washed
into the canal as well

00:14:33.072 --> 00:14:34.780
as also some of the
infrastructure that's

00:14:34.780 --> 00:14:37.030
been put in place,
like these booms,

00:14:37.030 --> 00:14:39.640
to prevent pollution
from entering the canal.

00:14:39.640 --> 00:14:41.890
This is next to what
is now a Whole Foods.

00:14:41.890 --> 00:14:44.980
So this boom was actually
added in response

00:14:44.980 --> 00:14:48.730
to previous monitoring by that
group of the construction site.

00:14:51.370 --> 00:14:54.179
And I think folks
sometimes misunderstand

00:14:54.179 --> 00:14:54.970
what Public Lab is.

00:14:54.970 --> 00:14:57.220
Like a friend once
told me that it's great

00:14:57.220 --> 00:14:59.890
that we're helping the
public to understand science.

00:14:59.890 --> 00:15:01.940
And I think that is part of it.

00:15:01.940 --> 00:15:05.410
But that's really not the core
function or the core purpose

00:15:05.410 --> 00:15:06.760
of Public Lab.

00:15:06.760 --> 00:15:09.760
I think Public Lab is
different because we

00:15:09.760 --> 00:15:14.500
focus a lot on the
question of who above what.

00:15:14.500 --> 00:15:17.440
We're not necessarily
teaching people about science

00:15:17.440 --> 00:15:18.120
exclusively.

00:15:18.120 --> 00:15:20.620
We're trying to negotiate a new
relationship between science

00:15:20.620 --> 00:15:24.100
practice and the public, perhaps
a more equitable or mutually

00:15:24.100 --> 00:15:25.990
beneficial relationship.

00:15:25.990 --> 00:15:31.990
And that involves a lot
of obviously big issues.

00:15:31.990 --> 00:15:34.510
But I think just
through our work,

00:15:34.510 --> 00:15:37.460
and in trying to support
communities facing pollution,

00:15:37.460 --> 00:15:40.310
the question of how
our expertise works,

00:15:40.310 --> 00:15:42.700
how it functions,
comes up a great deal.

00:15:42.700 --> 00:15:45.664
And that's something we've been
sort of receptive to coming

00:15:45.664 --> 00:15:47.080
from communities
we've worked with

00:15:47.080 --> 00:15:49.280
and tried to understand deeply.

00:15:49.280 --> 00:15:52.570
These questions like
who builds knowledge?

00:15:52.570 --> 00:15:54.160
Who is it for?

00:15:54.160 --> 00:15:55.750
Who asks the questions?

00:15:55.750 --> 00:15:58.310
And who understands the answers?

00:15:58.310 --> 00:16:00.250
These are pretty deep questions.

00:16:00.250 --> 00:16:02.800
And I doubt we'd be able to
unwrap them all in this session

00:16:02.800 --> 00:16:03.300
today.

00:16:03.300 --> 00:16:06.220
But they're pretty fundamental
to some of the issues

00:16:06.220 --> 00:16:09.200
that we're going to
talk about later.

00:16:09.200 --> 00:16:11.800
I think what's key
is that we're really

00:16:11.800 --> 00:16:14.860
trying not only to seek to make
science findings accessible--

00:16:14.860 --> 00:16:16.780
I think that is
important-- but also,

00:16:16.780 --> 00:16:21.520
its methods, its tools, its
structure of participation,

00:16:21.520 --> 00:16:23.920
and the depth of
participation that people

00:16:23.920 --> 00:16:27.820
have in how science functions.

00:16:27.820 --> 00:16:30.340
This means both making
more accessible on ramps

00:16:30.340 --> 00:16:32.690
to make it--

00:16:32.690 --> 00:16:34.510
I won't necessarily say easier--

00:16:34.510 --> 00:16:37.060
but I think accessible is
a slightly different shade

00:16:37.060 --> 00:16:38.200
than easier.

00:16:38.200 --> 00:16:39.940
But it also means
challenging what's

00:16:39.940 --> 00:16:44.050
possible in science practice
by leveraging things

00:16:44.050 --> 00:16:46.450
like peer production,
open source

00:16:46.450 --> 00:16:49.540
as Britta mentioned, and things
like the maker community, which

00:16:49.540 --> 00:16:53.980
I think is changing our
understanding of what

00:16:53.980 --> 00:17:00.640
technology development can
do and how it can function.

00:17:00.640 --> 00:17:04.119
So just for some
concretes, you may

00:17:04.119 --> 00:17:06.740
have heard of Public Lab's
balloon mapping project.

00:17:06.740 --> 00:17:08.819
This is our oldest project.

00:17:08.819 --> 00:17:11.319
And we developed this technique
with a number of communities

00:17:11.319 --> 00:17:14.457
in the Gulf Coast to
monitor the BP oil spill,

00:17:14.457 --> 00:17:16.540
to take aerial photographs
in very high resolution

00:17:16.540 --> 00:17:21.560
of spill-affected sites before,
during, and after the spill.

00:17:21.560 --> 00:17:24.937
And basically, you just
attach a camera to a balloon.

00:17:24.937 --> 00:17:26.520
I mean, it's easy
to say it like that.

00:17:26.520 --> 00:17:27.950
But there's a lot of
little things about it--

00:17:27.950 --> 00:17:30.366
in how you connect things up
with string and rubber bands,

00:17:30.366 --> 00:17:32.750
in how you archive the
data and interpret it.

00:17:32.750 --> 00:17:37.774
And it really is this whole
embodied research project

00:17:37.774 --> 00:17:39.440
in a community that
is primarily made up

00:17:39.440 --> 00:17:42.530
of nonscientists or
nonprofessional scientists,

00:17:42.530 --> 00:17:43.342
we'll say.

00:17:43.342 --> 00:17:44.300
This is a good example.

00:17:44.300 --> 00:17:46.490
There's a group, two
people in a canoe,

00:17:46.490 --> 00:17:48.890
again on the Gowanus
Canal, this time

00:17:48.890 --> 00:17:50.576
in the middle of the winter.

00:17:50.576 --> 00:17:51.950
In the box-- and
it's hard to see

00:17:51.950 --> 00:17:53.690
with the color on the
projector, but this

00:17:53.690 --> 00:17:56.830
is a large plume of raw
sewage that's on the Canal.

00:17:56.830 --> 00:17:58.580
As I mentioned, this
happens all the time.

00:17:58.580 --> 00:18:00.038
So people who live
there are really

00:18:00.038 --> 00:18:03.010
familiar with when and
where it happens, how often,

00:18:03.010 --> 00:18:05.010
and what volumes.

00:18:05.010 --> 00:18:06.886
And they've structured
their research project

00:18:06.886 --> 00:18:08.968
based on their understanding,
their deep knowledge

00:18:08.968 --> 00:18:10.010
of this particular site.

00:18:10.010 --> 00:18:11.820
And one thing that
they discovered-- oh,

00:18:11.820 --> 00:18:14.040
it's not in this picture--

00:18:14.040 --> 00:18:16.850
later slide-- teaser.

00:18:16.850 --> 00:18:20.330
So we also focus on
making your own tools.

00:18:20.330 --> 00:18:23.300
Now I wouldn't say this is a
prerequisite or an absolutely

00:18:23.300 --> 00:18:24.770
necessary portion of our work.

00:18:24.770 --> 00:18:28.320
But it has been a really
important part of it.

00:18:28.320 --> 00:18:31.520
We've managed to engage
pretty large numbers of people

00:18:31.520 --> 00:18:36.710
in constructing tools
and experimental setups.

00:18:36.710 --> 00:18:39.830
For example, paper
craft spectrometers--

00:18:39.830 --> 00:18:42.980
optical range spectrometers
built around a webcam,

00:18:42.980 --> 00:18:47.180
and doing comparative work using
different sample preparations,

00:18:47.180 --> 00:18:51.080
and in some cases, ultraviolet
light to induce fluorescence.

00:18:51.080 --> 00:18:54.770
And so this is just a graph of
how many people have actually

00:18:54.770 --> 00:18:57.110
built and uploaded data
using a spectrometer

00:18:57.110 --> 00:18:58.820
that they built themselves.

00:18:58.820 --> 00:19:00.870
This graph is, I think,
the past 52 weeks.

00:19:00.870 --> 00:19:03.140
But overall, almost 10,000
people, which I think

00:19:03.140 --> 00:19:09.810
is an interesting
project for us.

00:19:09.810 --> 00:19:12.380
So all in all, people
come to PublicLab.org,

00:19:12.380 --> 00:19:15.090
they post their work to
share it with others,

00:19:15.090 --> 00:19:17.660
but also to ask for help.

00:19:17.660 --> 00:19:19.200
These people might
be scientists.

00:19:19.200 --> 00:19:20.510
Many of them are.

00:19:20.510 --> 00:19:23.544
But they're just as likely to
be educators, to be hobbyists.

00:19:23.544 --> 00:19:25.460
And the group we're most
interested in serving

00:19:25.460 --> 00:19:27.980
are those community
groups who experience

00:19:27.980 --> 00:19:32.240
environmental
problems firsthand.

00:19:32.240 --> 00:19:34.090
So I guess it's a big question.

00:19:34.090 --> 00:19:37.120
Why do it yourself?

00:19:37.120 --> 00:19:40.570
Why go beyond simply
dissemination of science

00:19:40.570 --> 00:19:41.705
knowledge to the public?

00:19:41.705 --> 00:19:44.080
And I think there's a bunch
of different reasons to this.

00:19:44.080 --> 00:19:45.970
But this is sort of the crux.

00:19:45.970 --> 00:19:47.826
In some ways, it's
because experts, I think,

00:19:47.826 --> 00:19:50.200
often have a pretty narrow
conception of where the public

00:19:50.200 --> 00:19:52.717
could become involved.

00:19:52.717 --> 00:19:54.550
For example, public
dissemination of science

00:19:54.550 --> 00:19:56.292
is part of most federal grants.

00:19:56.292 --> 00:19:58.000
There's some portion
of it where you have

00:19:58.000 --> 00:19:59.600
to communicate your findings.

00:19:59.600 --> 00:20:01.300
This is an area that
people, I think,

00:20:01.300 --> 00:20:03.010
are making good progress on.

00:20:03.010 --> 00:20:07.840
But involvement in the
design of experiments,

00:20:07.840 --> 00:20:10.550
in the formulation of
research questions,

00:20:10.550 --> 00:20:13.270
in the interpretation and
application of those findings

00:20:13.270 --> 00:20:15.940
to real world scenarios--
those are often

00:20:15.940 --> 00:20:18.100
considered outside
the scope, sometimes

00:20:18.100 --> 00:20:21.310
even of science practitioners,
but certainly outside the scope

00:20:21.310 --> 00:20:23.800
of a partnership with
a community group

00:20:23.800 --> 00:20:27.410
facing a challenge or a problem.

00:20:27.410 --> 00:20:30.190
Of course, I think with
the do it yourself kits

00:20:30.190 --> 00:20:33.250
and so forth, the cost barrier
is definitely a factor for us.

00:20:33.250 --> 00:20:35.890
It's hard to get
more people involved

00:20:35.890 --> 00:20:39.700
in performing science, doing
science, and understanding

00:20:39.700 --> 00:20:40.240
science--

00:20:40.240 --> 00:20:43.125
any of those-- unless there's
cheaper instrumentation.

00:20:43.125 --> 00:20:45.250
This is not true for all
fields, but it's certainly

00:20:45.250 --> 00:20:47.080
true for some.

00:20:47.080 --> 00:20:49.851
But I think really to answer
this question more thoroughly,

00:20:49.851 --> 00:20:51.850
I think we need to take
a few steps back and try

00:20:51.850 --> 00:20:55.189
to better understand how
shared knowledge is produced--

00:20:55.189 --> 00:20:57.730
the key word there being shared
knowledge, not just knowledge

00:20:57.730 --> 00:21:00.550
that's held by
scientists, but knowledge

00:21:00.550 --> 00:21:03.730
that is commonly held,
which I hope is the goal--

00:21:03.730 --> 00:21:06.820
and how expertise works.

00:21:06.820 --> 00:21:08.770
So a depressing slide, I know.

00:21:08.770 --> 00:21:12.400
But this is The New York
Times' up shots sort

00:21:12.400 --> 00:21:14.530
of meta poll of polls.

00:21:14.530 --> 00:21:16.960
So they're listing all of the
projections of the outcome

00:21:16.960 --> 00:21:19.090
of the November 8th election.

00:21:19.090 --> 00:21:25.120
Obviously, the data
didn't fit the outcome.

00:21:25.120 --> 00:21:27.700
But I do think it's
an interesting case.

00:21:27.700 --> 00:21:32.760
In part because it
has a lot to do with--

00:21:32.760 --> 00:21:35.600
in my eyes, it has
a lot to do with how

00:21:35.600 --> 00:21:38.580
expertise is represented today
and how it's communicated.

00:21:38.580 --> 00:21:41.060
How are our projections
or predictions made?

00:21:41.060 --> 00:21:44.840
This isn't representative of
that many forms of science,

00:21:44.840 --> 00:21:47.410
but I think it's a
relevant data point.

00:21:47.410 --> 00:21:50.360
And specifically, why
and when people trust

00:21:50.360 --> 00:21:52.410
these kinds of projections--

00:21:52.410 --> 00:21:56.180
and I'm not necessarily
calling these wrong.

00:21:56.180 --> 00:22:00.050
I think there's
something really--

00:22:00.050 --> 00:22:02.570
I'll get into this
in a moment, sorry.

00:22:02.570 --> 00:22:04.730
So data and its
interpretation increasingly

00:22:04.730 --> 00:22:06.852
drives decision
making in our society.

00:22:06.852 --> 00:22:08.810
And this is something
that happens a little bit

00:22:08.810 --> 00:22:10.518
outside of the scope
of what we typically

00:22:10.518 --> 00:22:12.470
understand as science
practice, but it

00:22:12.470 --> 00:22:15.200
is an important ramification.

00:22:15.200 --> 00:22:17.270
And I just want to suggest this.

00:22:17.270 --> 00:22:21.230
I think you can see how this
might become a problem, not

00:22:21.230 --> 00:22:25.880
in itself, but where it
displaces, where it happens

00:22:25.880 --> 00:22:32.360
at the cost of a more discursive
mode of debate in a democracy.

00:22:32.360 --> 00:22:36.470
And I really am not saying
that we should use democracy

00:22:36.470 --> 00:22:37.670
to do science.

00:22:37.670 --> 00:22:40.520
What I'm saying is that there is
a relationship between the two

00:22:40.520 --> 00:22:42.740
that we need to
better understand.

00:22:42.740 --> 00:22:48.320
And I think this could present
challenges not only because

00:22:48.320 --> 00:22:49.310
of possible biases--

00:22:49.310 --> 00:22:52.160
I mean, there's clear
problems with science

00:22:52.160 --> 00:22:55.220
being paid for in
certain spheres as well

00:22:55.220 --> 00:22:57.770
as ideological issues
and their relationship

00:22:57.770 --> 00:23:02.930
with science in Congress
as was mentioned earlier.

00:23:02.930 --> 00:23:05.540
But I think also it has to
do with some of the areas

00:23:05.540 --> 00:23:07.790
that Public Lab is
focusing on, which

00:23:07.790 --> 00:23:10.400
may be the most objective
parts of science--

00:23:10.400 --> 00:23:15.230
the selection of problems
and questions to pursue,

00:23:15.230 --> 00:23:17.760
and of course, the application
of science is findings.

00:23:17.760 --> 00:23:20.564
These are sometimes
outside the scope, please.

00:23:20.564 --> 00:23:22.273
AUDIENCE: I don't want
to derail us but--

00:23:22.273 --> 00:23:23.272
JEFF WARREN: No, please.

00:23:23.272 --> 00:23:25.544
AUDIENCE: Did you say that
data and its interpretation

00:23:25.544 --> 00:23:29.968
increasingly drives decision
making in our society?

00:23:29.968 --> 00:23:35.944
I think there's a common
belief that, sadly, opposite

00:23:35.944 --> 00:23:36.940
is now true.

00:23:36.940 --> 00:23:38.580
JEFF WARREN: Oh, timescales--

00:23:38.580 --> 00:23:40.440
I mean, the last
200 or 300 years.

00:23:40.440 --> 00:23:41.505
[LAUGHTER]

00:23:41.505 --> 00:23:42.296
JEFF WARREN: Sorry.

00:23:42.296 --> 00:23:43.549
Very-- yeah.

00:23:43.549 --> 00:23:44.507
AUDIENCE: But there's--

00:23:44.507 --> 00:23:45.965
I mean, one of the
reasons I'm here

00:23:45.965 --> 00:23:48.536
is because I have great
concern that we've

00:23:48.536 --> 00:23:53.400
lost this notion of truth and
falsehood in public discourse.

00:23:53.400 --> 00:23:55.230
JEFF WARREN: Absolutely.

00:23:55.230 --> 00:23:57.395
I desperately want
to talk about that.

00:23:57.395 --> 00:24:00.171
I'm being a little round
about, so I apologize.

00:24:00.171 --> 00:24:00.670
Yeah.

00:24:00.670 --> 00:24:02.294
So I mean, as you
said, it's concerning

00:24:02.294 --> 00:24:03.480
when people lose trust.

00:24:03.480 --> 00:24:06.240
This is a graph of the 48
hours surrounding the election,

00:24:06.240 --> 00:24:10.260
and the projections of
the election's outcome.

00:24:10.260 --> 00:24:13.300
And it's a really depressing
graph to look at for me.

00:24:13.300 --> 00:24:14.620
I found it really interesting.

00:24:14.620 --> 00:24:16.257
This is The New
York Times upshot.

00:24:16.257 --> 00:24:18.090
But I found it very
interesting the language

00:24:18.090 --> 00:24:21.360
that fivethirtyeight.com
used, and a lot

00:24:21.360 --> 00:24:23.610
of other data driven
analysts are increasingly

00:24:23.610 --> 00:24:28.740
using, to tune how they
communicate certainty.

00:24:28.740 --> 00:24:31.380
And this is something
where, in the days following

00:24:31.380 --> 00:24:35.130
the election, you heard some
analysts talking about, well,

00:24:35.130 --> 00:24:38.460
we said it was 70 something
percent or whatever.

00:24:38.460 --> 00:24:41.310
And that's not-- that's
actually not very certain.

00:24:41.310 --> 00:24:45.900
You know, there's something
hidden in that or something

00:24:45.900 --> 00:24:49.610
that needs to be unwrapped about
the communication of certainty.

00:24:49.610 --> 00:24:51.360
And I think it's
a real challenge.

00:24:51.360 --> 00:24:53.276
I don't know that people
have answers to this,

00:24:53.276 --> 00:24:55.530
but it's something
I'm interested in.

00:24:55.530 --> 00:24:59.160
I know they sometimes would
say things, like, more probable

00:24:59.160 --> 00:25:00.540
than making a field goal.

00:25:00.540 --> 00:25:01.800
That didn't help me, because
I don't know anything

00:25:01.800 --> 00:25:02.425
about football.

00:25:02.425 --> 00:25:04.860
But they're trying
to communicate

00:25:04.860 --> 00:25:06.259
what the graphs mean.

00:25:06.259 --> 00:25:08.550
You know, it's easy to just
look and see all blue dots.

00:25:08.550 --> 00:25:10.950
But it's a very different
thing to understand

00:25:10.950 --> 00:25:14.970
what the ramifications are
for how reality plays out.

00:25:14.970 --> 00:25:16.200
And then, of course, yeah--

00:25:16.200 --> 00:25:17.780
this is the big thing.

00:25:17.780 --> 00:25:20.950
That sort of scenario plays out
on a lot of other narratives,

00:25:20.950 --> 00:25:21.450
right?

00:25:21.450 --> 00:25:25.612
Adjacent displays and
communications of data--

00:25:25.612 --> 00:25:27.570
many of you may have seen
this Bloomberg thing.

00:25:27.570 --> 00:25:31.560
It's very interactive,
extremely data dense.

00:25:31.560 --> 00:25:34.350
Like, there's so many
studies and so many data

00:25:34.350 --> 00:25:37.560
points that have been summarized
and metasummarized to create

00:25:37.560 --> 00:25:40.200
something which communicates,
I think, very effectively

00:25:40.200 --> 00:25:42.810
about warming trends.

00:25:42.810 --> 00:25:44.670
If you haven't used it,
go and play with it.

00:25:44.670 --> 00:25:47.320
It's really, really interesting.

00:25:47.320 --> 00:25:53.460
And so, you sort of have to
ask why isn't it persuasive

00:25:53.460 --> 00:25:55.370
to everybody, you know?

00:25:55.370 --> 00:25:57.390
Because it's pretty good.

00:25:57.390 --> 00:26:00.690
And I think it's easy
to demonize experts

00:26:00.690 --> 00:26:03.870
for not being good communicators
when things go wrong.

00:26:03.870 --> 00:26:05.370
I think a lot of
complex knowledge

00:26:05.370 --> 00:26:08.440
is communicated in pretty rich
and pretty interactive ways.

00:26:08.440 --> 00:26:11.250
It's not just learn
this by rote, you know?

00:26:11.250 --> 00:26:14.130
AUDIENCE: Is that the name of
the tool, compare and contrast?

00:26:14.130 --> 00:26:18.250
JEFF WARREN: It's Bloomberg.com
What's Warming the World?

00:26:18.250 --> 00:26:20.970
And I think it's pretty great.

00:26:23.960 --> 00:26:26.270
So I think, yeah,
with such a wealth

00:26:26.270 --> 00:26:30.710
of data and such persuasive
communication of that data,

00:26:30.710 --> 00:26:32.440
with all the tools
we have today,

00:26:32.440 --> 00:26:37.370
what is-- or is-- something
broken about expertise?

00:26:37.370 --> 00:26:39.290
And I think that, in
some cases, people

00:26:39.290 --> 00:26:41.540
are very much afraid that
there is something broken,

00:26:41.540 --> 00:26:43.920
maybe not about all expertise,
but about some portions.

00:26:43.920 --> 00:26:45.004
You have a thought?

00:26:45.004 --> 00:26:47.022
AUDIENCE: --comment again.

00:26:47.022 --> 00:26:48.906
I don't think
expertise is broken.

00:26:48.906 --> 00:26:51.732
But I think there's a
feeling among experts

00:26:51.732 --> 00:26:56.420
that no one has the patience
or wherewithal to listen.

00:26:56.420 --> 00:26:57.170
JEFF WARREN: Yeah.

00:26:57.170 --> 00:26:59.950
AUDIENCE: And when you
add that to the conflation

00:26:59.950 --> 00:27:02.480
And obfuscation
of fact by people

00:27:02.480 --> 00:27:09.841
who really are pure
advocates, and kind of have--

00:27:09.841 --> 00:27:11.813
whatever the interest
may be, whether it's

00:27:11.813 --> 00:27:15.902
to show up to their party,
whether it's to curry favor

00:27:15.902 --> 00:27:17.415
for any position--

00:27:17.415 --> 00:27:18.290
JEFF WARREN: Funding.

00:27:18.290 --> 00:27:20.210
[LAUGHS] Yeah.

00:27:20.210 --> 00:27:23.012
AUDIENCE: --that seems
to have overwhelmed

00:27:23.012 --> 00:27:26.489
the voice of reason and
fact-- it's just my opinion.

00:27:26.489 --> 00:27:27.780
JEFF WARREN: I agree with that.

00:27:27.780 --> 00:27:30.860
I think the way that I'm
using the term expertise here

00:27:30.860 --> 00:27:37.190
is potentially trying to
understand it in a wider scope.

00:27:37.190 --> 00:27:39.290
Which is to say
expertise could be

00:27:39.290 --> 00:27:42.950
defined as a body of
knowledge which is contained

00:27:42.950 --> 00:27:45.440
or known or collected.

00:27:45.440 --> 00:27:48.220
But what I mean, broke--

00:27:48.220 --> 00:27:50.630
when I'm using
the term here, I'm

00:27:50.630 --> 00:27:52.880
talking about it as a set
of relationships as well.

00:27:52.880 --> 00:27:53.796
AUDIENCE: [INAUDIBLE].

00:27:53.796 --> 00:27:56.240
JEFF WARREN: Expertise-- yeah.

00:27:56.240 --> 00:28:00.130
And relationships with experts--

00:28:00.130 --> 00:28:03.090
and who are experts,
how are they identified,

00:28:03.090 --> 00:28:05.690
how do we trust what they say?

00:28:05.690 --> 00:28:08.270
How do we, if we are
experts, communicate

00:28:08.270 --> 00:28:10.760
in a trustful manner to people.

00:28:10.760 --> 00:28:12.110
There's a whole set of issues.

00:28:12.110 --> 00:28:12.752
AUDIENCE: The scientific
method was supposed

00:28:12.752 --> 00:28:13.877
to be the solution to that.

00:28:13.877 --> 00:28:15.970
But I think
everyone's just too--

00:28:15.970 --> 00:28:18.257
JEFF WARREN: Well, let's
not give up on it yet.

00:28:18.257 --> 00:28:20.340
AUDIENCE: But we can't
push a button [INAUDIBLE]..

00:28:20.340 --> 00:28:20.930
JEFF WARREN: Yeah.

00:28:20.930 --> 00:28:21.260
It's true.

00:28:21.260 --> 00:28:21.650
AUDIENCE: --wayside.

00:28:21.650 --> 00:28:22.040
Forgive me.

00:28:22.040 --> 00:28:22.820
I'll [INAUDIBLE].

00:28:22.820 --> 00:28:24.153
JEFF WARREN: No, no, no, please.

00:28:24.153 --> 00:28:25.130
And thank you, no.

00:28:25.130 --> 00:28:26.300
I'm glad you're engaging.

00:28:26.300 --> 00:28:28.670
Because it's something I
think about a great deal

00:28:28.670 --> 00:28:31.070
and have thought about,
especially recently.

00:28:31.070 --> 00:28:36.080
So Harry Collins is not
popular in all fields.

00:28:36.080 --> 00:28:40.610
But he does do a very close
and careful examination

00:28:40.610 --> 00:28:42.322
of different kinds of expertise.

00:28:42.322 --> 00:28:44.030
And I think it's a
very interesting thing

00:28:44.030 --> 00:28:46.432
to think about
what distinguishes

00:28:46.432 --> 00:28:47.640
different kinds of expertise.

00:28:47.640 --> 00:28:52.080
And one in particular that he
talks about is meta expertise.

00:28:52.080 --> 00:28:54.950
And it's the ability to
distinguish expertises,

00:28:54.950 --> 00:28:58.910
the ability to compare and to
choose an expert among several

00:28:58.910 --> 00:29:00.980
who are purporting
to be experts.

00:29:00.980 --> 00:29:03.650
And he says, you
know, and I think

00:29:03.650 --> 00:29:05.290
this is a persuasive
point of his,

00:29:05.290 --> 00:29:07.980
that it's a particularly
difficult one,

00:29:07.980 --> 00:29:11.340
but it's one which many people
are called upon to have.

00:29:11.340 --> 00:29:15.460
It's one that is often based
on long term reputation.

00:29:15.460 --> 00:29:18.740
It's based on, in some
cases, relationships,

00:29:18.740 --> 00:29:24.290
personal relationships,
and it can sometimes

00:29:24.290 --> 00:29:27.040
be affected by a different kind
of expertise, which he calls--

00:29:27.040 --> 00:29:29.540
I think he calls it downward
discrimination expertise, which

00:29:29.540 --> 00:29:35.990
is essentially the
ignoring of one expert

00:29:35.990 --> 00:29:38.450
because you perceive
a different expert

00:29:38.450 --> 00:29:41.120
to be of a greater authority.

00:29:41.120 --> 00:29:44.030
So I don't know about every
observation he's made.

00:29:44.030 --> 00:29:47.000
But I do appreciate the
taxonomy he's created

00:29:47.000 --> 00:29:48.650
and the attempt
to understand what

00:29:48.650 --> 00:29:51.950
are the mechanisms
that allow expertise

00:29:51.950 --> 00:29:52.955
to occur in our society.

00:29:55.500 --> 00:30:00.380
And I think the question for
Public Lab and for some of us

00:30:00.380 --> 00:30:03.350
is what do we do about
the widening gap?

00:30:03.350 --> 00:30:05.870
Because although
there is a tendency

00:30:05.870 --> 00:30:09.860
to think that the ability
to question expertise

00:30:09.860 --> 00:30:15.560
is driving a wedge,
the democratization

00:30:15.560 --> 00:30:21.180
of knowledge production is
an assault on expertise.

00:30:21.180 --> 00:30:23.570
But I actually think
maybe it's like there's

00:30:23.570 --> 00:30:25.046
a few other dimensions to that.

00:30:25.046 --> 00:30:26.420
And although I'm
not going to say

00:30:26.420 --> 00:30:29.607
that's not true in
some ways, I think

00:30:29.607 --> 00:30:31.940
that there are other ways we
can think about it as well.

00:30:31.940 --> 00:30:34.190
So what Public
Lab tries to do is

00:30:34.190 --> 00:30:35.760
to focus on problem definition.

00:30:35.760 --> 00:30:38.150
So this is the earliest
stage in the sort of sequence

00:30:38.150 --> 00:30:41.300
that might encompass
scientific inquiry.

00:30:41.300 --> 00:30:43.510
And staying close to
real world problems--

00:30:43.510 --> 00:30:47.900
Britta mentioned
communicating with people

00:30:47.900 --> 00:30:51.530
as early as possible, building
products in collaboration

00:30:51.530 --> 00:30:54.800
with groups that face problems,
engaging them in the problem

00:30:54.800 --> 00:30:57.950
selection in the formulation of
questions, and in some cases,

00:30:57.950 --> 00:31:00.440
in research design.

00:31:00.440 --> 00:31:05.060
There are specific
expertises and capacities

00:31:05.060 --> 00:31:06.860
to formulate an experiment.

00:31:06.860 --> 00:31:10.070
But those may be, in
some cases, the places

00:31:10.070 --> 00:31:12.770
where it's most likely that
you would learn something

00:31:12.770 --> 00:31:14.690
from a group that has
deep understanding

00:31:14.690 --> 00:31:17.480
of a particular problem,
first hand knowledge.

00:31:17.480 --> 00:31:21.720
So I'm really interested
in that potential, and in,

00:31:21.720 --> 00:31:24.900
really, collaborating as
much in asking questions

00:31:24.900 --> 00:31:26.580
as in answering them.

00:31:26.580 --> 00:31:29.719
But what are the
sources of mistrust?

00:31:29.719 --> 00:31:31.260
I think there are
many, but I'm going

00:31:31.260 --> 00:31:33.130
to try to dig into
a few of them.

00:31:33.130 --> 00:31:36.720
I think one of them is limited
ability to evaluate or test.

00:31:36.720 --> 00:31:39.279
So this affects,
perhaps, climate science

00:31:39.279 --> 00:31:41.070
more than almost any
other type of science,

00:31:41.070 --> 00:31:44.530
although I guess the
LHC is another example.

00:31:44.530 --> 00:31:52.100
But how can people
evaluate empirically

00:31:52.100 --> 00:31:55.740
what climate science is saying?

00:31:55.740 --> 00:31:56.820
It's not very possible.

00:31:56.820 --> 00:31:59.970
You can observationally
do it in some cases.

00:31:59.970 --> 00:32:02.670
But understanding that in
a context is difficult.

00:32:02.670 --> 00:32:05.757
And I mention this
one mainly because it

00:32:05.757 --> 00:32:07.590
underlies a lot of what
we do at Public Lab.

00:32:07.590 --> 00:32:09.839
Public Lab's not primarily
interested or not primarily

00:32:09.839 --> 00:32:11.560
engaged in climate research.

00:32:11.560 --> 00:32:14.580
We're primarily engaged
in pollution research.

00:32:14.580 --> 00:32:17.700
But we take it as
a powerful thing

00:32:17.700 --> 00:32:19.740
to be able to empirically
verify something.

00:32:19.740 --> 00:32:21.406
And that's why we're
focused on low cost

00:32:21.406 --> 00:32:25.240
tools and democratization
of the technologies.

00:32:25.240 --> 00:32:27.240
But this is linked in
climate to the following--

00:32:27.240 --> 00:32:31.680
when processes are too big to
see feedback loop personally.

00:32:31.680 --> 00:32:33.970
When you go and
you do something,

00:32:33.970 --> 00:32:36.480
it's one of the
longest feedback loops

00:32:36.480 --> 00:32:40.457
that we are confronted
with in research.

00:32:40.457 --> 00:32:41.290
But yeah, oh, sorry.

00:32:41.290 --> 00:32:42.331
I already mentioned this.

00:32:42.331 --> 00:32:44.790
But basically, we do
focus on testability

00:32:44.790 --> 00:32:48.780
at Public Lab on the question--
can you also build this?

00:32:48.780 --> 00:32:50.470
Do you also get the same result?

00:32:50.470 --> 00:32:53.400
And this is a picture of one
of our spectrometer prototypes.

00:32:53.400 --> 00:32:59.100
Someone literally, like, tweeted
a picture and a link to plans.

00:32:59.100 --> 00:33:02.790
And someone else built one
and tweeted that they had,

00:33:02.790 --> 00:33:04.440
as close as possible,
reproduced this.

00:33:04.440 --> 00:33:07.380
Harry Collins talks a lot
about the infinite regress.

00:33:10.650 --> 00:33:12.130
What's the-- anyway, whatever--

00:33:12.130 --> 00:33:13.290
I'll get back to it later.

00:33:13.290 --> 00:33:13.956
AUDIENCE: Sorry.

00:33:13.956 --> 00:33:15.180
Is that name Harry Collins?

00:33:15.180 --> 00:33:15.870
JEFF WARREN: Harry Collins?

00:33:15.870 --> 00:33:16.230
Yeah.

00:33:16.230 --> 00:33:16.600
Yeah.

00:33:16.600 --> 00:33:18.474
I'll talk a little more
about him later, too.

00:33:18.474 --> 00:33:22.060
I should probably start
moving a little faster.

00:33:22.060 --> 00:33:23.790
A couple of others--
environmental issues

00:33:23.790 --> 00:33:24.660
affect someone else.

00:33:24.660 --> 00:33:26.970
I think this is one where
it's not just about--

00:33:32.005 --> 00:33:33.630
I think there's many
sides to that one.

00:33:33.630 --> 00:33:34.770
It's a tough one.

00:33:34.770 --> 00:33:36.870
But I think
increasingly people are

00:33:36.870 --> 00:33:38.700
understating
environmental problems

00:33:38.700 --> 00:33:41.880
as ones which affect people.

00:33:41.880 --> 00:33:43.957
That's a major step forward.

00:33:43.957 --> 00:33:45.540
I think the environmental
movement had

00:33:45.540 --> 00:33:48.860
been very closely associated
with conservation,

00:33:48.860 --> 00:33:50.710
and I think
conservation is great.

00:33:50.710 --> 00:33:53.760
But I do think it is
important for people

00:33:53.760 --> 00:33:56.850
to recognize that there
are justice issues at stake

00:33:56.850 --> 00:33:58.650
with communities that
are facing pollution

00:33:58.650 --> 00:34:01.950
and don't have a way to
respond to it, or sometimes,

00:34:01.950 --> 00:34:04.650
even, to understand it.

00:34:04.650 --> 00:34:07.856
But increasingly, pollution
is affecting everybody,

00:34:07.856 --> 00:34:09.480
and the climate is
affecting everybody.

00:34:09.480 --> 00:34:12.989
And I think this is an
opportunity for common cause.

00:34:12.989 --> 00:34:16.560
The other one is one that
affects poor communities

00:34:16.560 --> 00:34:18.510
perhaps more than others.

00:34:18.510 --> 00:34:23.370
And that's that they
have very limited ability

00:34:23.370 --> 00:34:27.060
to respond, and in many
cases, to question.

00:34:27.060 --> 00:34:29.340
And therefore, they
already have the experience

00:34:29.340 --> 00:34:32.639
of having been lied to and hurt
by industries, and sometimes

00:34:32.639 --> 00:34:35.850
by the scientists that
those industries employ.

00:34:35.850 --> 00:34:38.699
I know this is a difficult
one for all of us.

00:34:38.699 --> 00:34:41.670
But I think that if
you talk to communities

00:34:41.670 --> 00:34:44.175
who face pollution
firsthand, this

00:34:44.175 --> 00:34:45.750
is a very common experience.

00:34:45.750 --> 00:34:47.219
And it's unfortunate.

00:34:47.219 --> 00:34:49.050
Harry Collins actually
mentions that he

00:34:49.050 --> 00:34:53.120
feels that the fact that we are
upset when we see that there

00:34:53.120 --> 00:34:55.199
has been an exchange
of money which

00:34:55.199 --> 00:34:58.620
has influenced the findings
of a research project--

00:34:58.620 --> 00:35:02.160
we are upset because we
know that that's wrong.

00:35:02.160 --> 00:35:04.500
Because there's something
essential and fundamental

00:35:04.500 --> 00:35:08.370
about science which is being
broken when that happens--

00:35:08.370 --> 00:35:11.170
so complex, but interesting.

00:35:11.170 --> 00:35:14.640
So OK, so what can I do as a
scientist or a technologist?

00:35:14.640 --> 00:35:16.980
These aren't the same
thing, but the question

00:35:16.980 --> 00:35:19.650
might be relevant to both.

00:35:19.650 --> 00:35:22.360
Tough-- we're going to
try to get into this.

00:35:22.360 --> 00:35:25.740
I have some ideas,
four broad ideas.

00:35:25.740 --> 00:35:31.200
This is an article which
I found very interesting.

00:35:31.200 --> 00:35:33.930
It recaps a lot of ideas which
Public Lab has championed

00:35:33.930 --> 00:35:35.160
over the last six years.

00:35:38.040 --> 00:35:41.790
But it also shows
how difficult it

00:35:41.790 --> 00:35:43.830
is to have an
articulate conversation

00:35:43.830 --> 00:35:48.060
about these things,
because it is very complex.

00:35:48.060 --> 00:35:51.469
The subtitle is maybe
more important--

00:35:51.469 --> 00:35:53.010
experts need to
listen to the public.

00:35:53.010 --> 00:35:54.840
I went into the
comments, all right?

00:35:54.840 --> 00:35:58.050
I know that's not always
a productive place to find

00:35:58.050 --> 00:35:58.550
things.

00:35:58.550 --> 00:36:01.230
But for once, I
actually thought it

00:36:01.230 --> 00:36:04.900
was really, really educational.

00:36:04.900 --> 00:36:05.610
Yeah.

00:36:05.610 --> 00:36:07.110
So I'll just read it.

00:36:07.110 --> 00:36:10.132
"No, scientists need to do
science, not run a PR campaign

00:36:10.132 --> 00:36:11.340
and become marketing experts.

00:36:11.340 --> 00:36:12.631
They aren't trained to do that.

00:36:12.631 --> 00:36:14.200
And it's silly to
expect them to.

00:36:14.200 --> 00:36:16.050
What the rest of us
need to do is invest in

00:36:16.050 --> 00:36:17.290
the school system"--

00:36:17.290 --> 00:36:19.290
well, that's interesting--
what the rest of us--

00:36:19.290 --> 00:36:22.444
so this gentleman does not
identify as a scientist--

00:36:22.444 --> 00:36:24.860
--"is invest in the school
system that we've basically let

00:36:24.860 --> 00:36:27.110
rot in many places so that
our citizenry has knowledge

00:36:27.110 --> 00:36:29.444
of the scientific method
beyond the third grade level.

00:36:29.444 --> 00:36:30.860
If they understand
what science is

00:36:30.860 --> 00:36:32.290
and what it has
accomplished, then they'll

00:36:32.290 --> 00:36:33.224
appreciate its value.

00:36:33.224 --> 00:36:34.640
It's the job of
the public schools

00:36:34.640 --> 00:36:38.030
to teach this, not
career scientists."

00:36:38.030 --> 00:36:41.090
There's almost too much in that
statement for me to peel apart.

00:36:41.090 --> 00:36:44.309
But we'll try to get to some
of these questions as we go.

00:36:44.309 --> 00:36:46.850
And I'm not putting it up here
because I think this person is

00:36:46.850 --> 00:36:47.614
completely wrong.

00:36:47.614 --> 00:36:50.030
I'm putting it up here because
it's a series of statements

00:36:50.030 --> 00:36:53.180
that have some value.

00:36:53.180 --> 00:36:55.040
I think that it is
overlooking other things,

00:36:55.040 --> 00:36:57.537
but the next two
are even better.

00:36:57.537 --> 00:36:59.120
"This boils down to
wanting scientists

00:36:59.120 --> 00:37:00.620
to basically add
some responsibilities

00:37:00.620 --> 00:37:02.630
to the number of things
they have to do already,

00:37:02.630 --> 00:37:04.046
yet it doesn't
seem to dangle much

00:37:04.046 --> 00:37:06.670
in the way of tangible
money for that extra work."

00:37:06.670 --> 00:37:11.150
True-- TLDR-- less
science, more photo ops.

00:37:11.150 --> 00:37:12.920
I think that wasn't
a helpful comment.

00:37:12.920 --> 00:37:16.915
But I think it's reductive in
a way that is helpful for us

00:37:16.915 --> 00:37:18.290
as we're looking
at this problem.

00:37:21.850 --> 00:37:23.251
So educate yourself.

00:37:23.251 --> 00:37:25.000
That's what the first
commenter is saying.

00:37:25.000 --> 00:37:27.520
But actually, I want to say
it to everybody, including

00:37:27.520 --> 00:37:30.380
scientists and technologists.

00:37:30.380 --> 00:37:31.630
I think it's really important.

00:37:31.630 --> 00:37:34.520
Because we tend to think, and
we're taught science, often,

00:37:34.520 --> 00:37:38.922
in the public schools
somewhat historically.

00:37:38.922 --> 00:37:39.880
Where did it come from?

00:37:39.880 --> 00:37:41.320
How long has it been around?

00:37:41.320 --> 00:37:43.510
Why does it work this way?

00:37:43.510 --> 00:37:46.630
And how did it develop
into what it is today?

00:37:50.060 --> 00:37:51.130
I mean science studies--

00:37:51.130 --> 00:37:53.230
MIT has a great department
of science, technology,

00:37:53.230 --> 00:37:55.370
and society.

00:37:55.370 --> 00:37:57.580
You know, basically,
I think it's important

00:37:57.580 --> 00:37:58.880
not to be naive about this.

00:37:58.880 --> 00:38:02.350
Understand how the field
works empirically as well

00:38:02.350 --> 00:38:03.580
as theoretically.

00:38:03.580 --> 00:38:06.040
As in, you know,
how do we aspire

00:38:06.040 --> 00:38:09.190
for it to work versus
empirically, how can we measure

00:38:09.190 --> 00:38:14.200
it to be working or not or in
what ways, who it's benefited

00:38:14.200 --> 00:38:16.000
and how it developed over time.

00:38:16.000 --> 00:38:18.340
This is one thing that
I really respect folks

00:38:18.340 --> 00:38:22.540
like Harry Collins for
trying to understand, apart

00:38:22.540 --> 00:38:25.900
from the different ways
that people have actually

00:38:25.900 --> 00:38:27.400
come up with to understand it.

00:38:27.400 --> 00:38:30.880
I mean, Harry Collins
is just one perspective.

00:38:30.880 --> 00:38:32.480
Part of this, I
think, is vocabulary.

00:38:32.480 --> 00:38:34.210
And just about this
particular topic

00:38:34.210 --> 00:38:36.480
that Public Lab
is engaged in, you

00:38:36.480 --> 00:38:38.609
might have seen three
different phrases.

00:38:38.609 --> 00:38:40.150
You'd come across
these three phrases

00:38:40.150 --> 00:38:44.044
to describe closely
related ideas.

00:38:44.044 --> 00:38:45.460
Public Lab uses
community science.

00:38:45.460 --> 00:38:47.630
It's a term that we've
helped to define.

00:38:47.630 --> 00:38:50.770
In part, we've used it
because there's actually

00:38:50.770 --> 00:38:53.500
two definitions of citizen
science, which are competing

00:38:53.500 --> 00:38:55.140
and quite confusing.

00:38:55.140 --> 00:39:00.940
There's the 1995, Alan Irwin's
definition of citizen science.

00:39:00.940 --> 00:39:03.130
Rick Bonney describes
it as a methodology

00:39:03.130 --> 00:39:05.530
for engaging a large
group of people outside

00:39:05.530 --> 00:39:10.360
of science practice in
performing data collection.

00:39:10.360 --> 00:39:13.690
For example, doing bird
counts, submitting data,

00:39:13.690 --> 00:39:15.610
being an extension
of science's ability

00:39:15.610 --> 00:39:16.705
to interrogate the world.

00:39:16.705 --> 00:39:18.080
And this is a very
powerful thing

00:39:18.080 --> 00:39:20.590
that I think that
Public Lab uses as well.

00:39:20.590 --> 00:39:22.480
But actually, I think
Public Lab is perhaps

00:39:22.480 --> 00:39:26.470
more inspired by the older
definition of citizen science

00:39:26.470 --> 00:39:27.610
by Irwin.

00:39:27.610 --> 00:39:34.030
And Irwin described the
work of HIV activists

00:39:34.030 --> 00:39:43.560
in the '90s and earlier
who included AIDS patients,

00:39:43.560 --> 00:39:51.160
and who were involved in
drug trials in early AIDS

00:39:51.160 --> 00:39:52.180
treatments.

00:39:52.180 --> 00:39:55.090
And they organized.

00:39:55.090 --> 00:39:55.800
They protested.

00:39:55.800 --> 00:40:00.220
They did die ins at the
National Institutes of Health.

00:40:00.220 --> 00:40:06.000
And ultimately,
they gained what--

00:40:06.000 --> 00:40:09.700
and again, I'm over
reference term by Collins--

00:40:09.700 --> 00:40:12.220
interactional
expertise, which is

00:40:12.220 --> 00:40:16.900
that they could read
and debate papers

00:40:16.900 --> 00:40:19.240
and peer-reviewed research.

00:40:19.240 --> 00:40:24.640
They could challenge the
structure of drug trials,

00:40:24.640 --> 00:40:27.240
and they successfully
did so, persuading

00:40:27.240 --> 00:40:30.460
those who ran the trials
to modify how they worked.

00:40:30.460 --> 00:40:33.760
And in some cases, they did so
in an extremely disruptive way

00:40:33.760 --> 00:40:34.780
to the researchers.

00:40:34.780 --> 00:40:38.830
Which is to say they
sometimes exchanged

00:40:38.830 --> 00:40:41.170
the drugs they
were given in order

00:40:41.170 --> 00:40:44.200
to intentionally mix
placebos with nonplacebos

00:40:44.200 --> 00:40:47.890
because they found it
to be unethical to do

00:40:47.890 --> 00:40:50.560
double blind research on
people who are suffering.

00:40:50.560 --> 00:40:53.620
So it's a complicated
story, many sides,

00:40:53.620 --> 00:40:59.350
many, many important
aspects of this.

00:40:59.350 --> 00:41:04.060
But what happened was not
that scientists, per se,

00:41:04.060 --> 00:41:06.130
decided to include
people in their research,

00:41:06.130 --> 00:41:08.230
but that they were
persuaded to do so.

00:41:08.230 --> 00:41:11.950
And they eventually did so,
some of them, voluntarily.

00:41:11.950 --> 00:41:15.380
And collaborated with
activists, in some cases,

00:41:15.380 --> 00:41:17.110
in order to recruit
for new trials.

00:41:17.110 --> 00:41:19.360
So there were constructive
collaborations that led out

00:41:19.360 --> 00:41:21.190
of this sequence of events.

00:41:21.190 --> 00:41:24.400
And it's a fascinating history.

00:41:24.400 --> 00:41:29.040
It's a fascinating set
of new organizations

00:41:29.040 --> 00:41:33.880
or new relationships between
people who did not originally

00:41:33.880 --> 00:41:36.610
have almost any
kind of expertise

00:41:36.610 --> 00:41:41.290
besides the immediate expertise
of being a victim or a patient

00:41:41.290 --> 00:41:45.070
and people who had
expertise of the kind

00:41:45.070 --> 00:41:46.450
that we are more familiar with.

00:41:46.450 --> 00:41:49.750
So OK, fascinating,
and difficult

00:41:49.750 --> 00:41:52.150
to distinguish the two now
that the terminology has

00:41:52.150 --> 00:41:55.430
been overwritten.

00:41:55.430 --> 00:41:58.510
So Harry Collins--
also Sandra Harding,

00:41:58.510 --> 00:42:00.400
another controversial
figure, but one

00:42:00.400 --> 00:42:02.020
who I really appreciate.

00:42:02.020 --> 00:42:04.840
She wrote Whose Science
and Whose Knowledge?

00:42:04.840 --> 00:42:06.460
And she talks about
the relationship

00:42:06.460 --> 00:42:11.570
of feminist epistemology
with scientific research.

00:42:11.570 --> 00:42:14.530
And she just has so much to say.

00:42:14.530 --> 00:42:15.876
It's amazing.

00:42:15.876 --> 00:42:17.500
But one thing that
I really appreciated

00:42:17.500 --> 00:42:22.640
was her focus on the
selection of problematics,

00:42:22.640 --> 00:42:28.470
the choosing of scientific
questions as an area which,

00:42:28.470 --> 00:42:30.970
well, as she was writing in
the '80s, was understudied,

00:42:30.970 --> 00:42:34.230
she felt. So she has a
lot to say about that.

00:42:34.230 --> 00:42:36.180
Harry Collins has a book--

00:42:36.180 --> 00:42:38.920
Are We All Scientific
Experts Now?

00:42:38.920 --> 00:42:40.230
Spoiler alert, no.

00:42:40.230 --> 00:42:43.390
[LAUGHS] Definitively,
he says no.

00:42:43.390 --> 00:42:46.550
And I'm persuaded by
a lot of what he says,

00:42:46.550 --> 00:42:49.180
but not by all of it.

00:42:49.180 --> 00:42:53.530
Collins also did a
really interesting sort

00:42:53.530 --> 00:42:58.660
of retrospective of
this set of studies

00:42:58.660 --> 00:43:01.990
from after the
Chernobyl disaster.

00:43:01.990 --> 00:43:05.170
He wrote a piece in the
early 2000s looking over

00:43:05.170 --> 00:43:07.780
that work called The
Science of the Lambs.

00:43:07.780 --> 00:43:11.860
He's part of a group of
scholars who are very punny.

00:43:11.860 --> 00:43:16.180
But he looked at how the
studies of radiation's

00:43:16.180 --> 00:43:20.560
effects on sheep in Cumbria
and other parts of the UK.

00:43:23.610 --> 00:43:27.100
He worked with
Trevor Pinch as well.

00:43:27.100 --> 00:43:30.000
Basically, it's, like,
it's complicated.

00:43:30.000 --> 00:43:35.560
But he looked at how researchers
trying to map out and quantify

00:43:35.560 --> 00:43:39.970
radiation did and did not
succeed in working with farmers

00:43:39.970 --> 00:43:44.920
and building bridges between
the farmers' knowledge of water

00:43:44.920 --> 00:43:49.000
flow, of exposure,
of site conditions,

00:43:49.000 --> 00:43:52.600
and the farming practices,
and their own expertise

00:43:52.600 --> 00:43:54.012
to rich conclusions.

00:43:54.012 --> 00:43:55.720
Tough one, but a really
interesting read,

00:43:55.720 --> 00:43:58.160
and a fairly short one?

00:43:58.160 --> 00:44:00.294
So Sandra Harding,
as I mentioned,

00:44:00.294 --> 00:44:02.710
who asked the questions which
science attempts to answer--

00:44:02.710 --> 00:44:04.810
I think it's a
really important one.

00:44:04.810 --> 00:44:06.360
I don't know.

00:44:06.360 --> 00:44:11.030
I mean, I know, but
got to dig into that.

00:44:11.030 --> 00:44:14.950
So OK, some tough ones here.

00:44:14.950 --> 00:44:18.790
The possibility that
scientists' practice today does

00:44:18.790 --> 00:44:22.030
have blind spots,
and specifically

00:44:22.030 --> 00:44:25.780
when it comes to other forms
of knowledge production.

00:44:25.780 --> 00:44:28.450
Not to say it's not
interested, but there

00:44:28.450 --> 00:44:30.250
are new forms of
knowledge- well,

00:44:30.250 --> 00:44:33.010
new-ish forms of knowledge
production emerging.

00:44:33.010 --> 00:44:34.430
And I really want to be clear.

00:44:34.430 --> 00:44:36.520
I'm absolutely not
saying we should try

00:44:36.520 --> 00:44:38.250
to recognize climate denial.

00:44:38.250 --> 00:44:40.410
No.

00:44:40.410 --> 00:44:42.810
That's not the kind of blind
spot I'm talking about.

00:44:42.810 --> 00:44:45.090
[LAUGHING] I think
that's really part

00:44:45.090 --> 00:44:47.640
of a parallel discussion
about the influence of money

00:44:47.640 --> 00:44:49.630
in politics and science.

00:44:49.630 --> 00:44:53.190
And it's one I'm not even going
to try to broach necessarily

00:44:53.190 --> 00:44:54.240
in this session.

00:44:54.240 --> 00:44:56.821
I'm talking about
the lived experience

00:44:56.821 --> 00:44:58.820
of those who suffer from
environmental problems.

00:44:58.820 --> 00:45:01.830
And to some degree, this sort
of humble recognition of our own

00:45:01.830 --> 00:45:04.650
limits and unknowns.

00:45:04.650 --> 00:45:06.940
And especially on questions,
critical questions

00:45:06.940 --> 00:45:09.490
of environmental harm.

00:45:09.490 --> 00:45:13.620
So number two-- in terms of--

00:45:13.620 --> 00:45:15.510
I wanted to tell the
story of this picture.

00:45:15.510 --> 00:45:17.430
That's a sunken
boat, so ignore it.

00:45:17.430 --> 00:45:21.020
This is-- I wrote it
over with letters, oops.

00:45:21.020 --> 00:45:24.840
But there's a darker
thing here, right?

00:45:24.840 --> 00:45:29.950
And that's actually melted ice
as water came out of a pipe

00:45:29.950 --> 00:45:31.110
on the side of this canal.

00:45:31.110 --> 00:45:33.735
And that wasn't on the
original engineering surveys.

00:45:33.735 --> 00:45:38.670
And it wasn't in the
EPA's data on this site.

00:45:38.670 --> 00:45:40.140
But it's an active inflow.

00:45:40.140 --> 00:45:43.710
There's water and whatever
else coming out of it,

00:45:43.710 --> 00:45:45.060
off of a construction site.

00:45:45.060 --> 00:45:47.640
And it's just a good example.

00:45:47.640 --> 00:45:49.590
There's a group who lives there.

00:45:49.590 --> 00:45:51.930
They go by that site every day.

00:45:51.930 --> 00:45:54.486
And they can do kinds
of observations.

00:45:54.486 --> 00:45:55.860
This is data
collection in a way.

00:45:55.860 --> 00:45:59.250
But they did it not because they
were contributing to science

00:45:59.250 --> 00:46:03.030
in a sort of a noble way,
but because they're engaged

00:46:03.030 --> 00:46:04.110
in the problem, you know?

00:46:04.110 --> 00:46:07.619
And they're critically
monitoring this site.

00:46:07.619 --> 00:46:08.910
They're watchdogging this site.

00:46:08.910 --> 00:46:13.590
And they're trying to hold
the abutters, the construction

00:46:13.590 --> 00:46:15.810
sites, and the potential
polluters-- they're

00:46:15.810 --> 00:46:17.435
trying to hold their
feet to the flame.

00:46:19.440 --> 00:46:21.780
They're not objective.

00:46:21.780 --> 00:46:24.870
But they were able to
submit data, including

00:46:24.870 --> 00:46:26.910
this photograph and
others, that updated

00:46:26.910 --> 00:46:31.170
the understanding of the site
and influenced the cleanup.

00:46:31.170 --> 00:46:36.171
OK, interesting, and
specifically, it's

00:46:36.171 --> 00:46:37.670
easy to take for
granted when you're

00:46:37.670 --> 00:46:40.200
speaking with your colleagues
where your expertise comes

00:46:40.200 --> 00:46:45.210
from, what kind of certainty
you're communicating.

00:46:45.210 --> 00:46:47.040
And this is something
that, you know,

00:46:47.040 --> 00:46:52.590
when people read the so-called
climate gate e-mails, insider

00:46:52.590 --> 00:46:54.690
talk is structured
in a certain way.

00:46:54.690 --> 00:46:55.410
It's hard.

00:46:55.410 --> 00:46:57.690
It's not designed to
communicate to all audiences.

00:46:57.690 --> 00:46:59.620
But when you are
communicating with people,

00:46:59.620 --> 00:47:02.790
especially outside of the group
that you work with immediately,

00:47:02.790 --> 00:47:06.990
how do people know where
your expertise comes from?

00:47:06.990 --> 00:47:09.060
I mean, you know,
I think titles,

00:47:09.060 --> 00:47:12.150
degrees, credentials help here.

00:47:12.150 --> 00:47:14.660
But they're not the whole story.

00:47:14.660 --> 00:47:19.400
And there's this really
interesting sidebar.

00:47:19.400 --> 00:47:22.320
The Quechua language
group in Peru

00:47:22.320 --> 00:47:23.910
has this fascinating quality.

00:47:23.910 --> 00:47:26.970
Which is that it has a
suffix which indicates

00:47:26.970 --> 00:47:28.770
the source of your knowledge.

00:47:28.770 --> 00:47:31.955
So you can say the same thing
and indicate grammatically

00:47:31.955 --> 00:47:34.080
whether you heard it from
someone else, whether you

00:47:34.080 --> 00:47:36.960
experienced it firsthand,
and several other forms

00:47:36.960 --> 00:47:43.040
of empirical context.

00:47:43.040 --> 00:47:46.080
And I often wish that I
did a better job at that.

00:47:46.080 --> 00:47:48.180
Full disclosure, in
terms of communicating

00:47:48.180 --> 00:47:50.062
how you get your
expertise, I'm not

00:47:50.062 --> 00:47:51.270
a scholar of science studies.

00:47:51.270 --> 00:47:53.550
Although I'm a fan of
it, as you can tell.

00:47:53.550 --> 00:47:55.770
I also have no formal
science training.

00:47:55.770 --> 00:47:58.840
I just have some thoughts.

00:47:58.840 --> 00:48:01.980
I think interactional expertise
is what Collins talks about,

00:48:01.980 --> 00:48:04.710
the ability to speak the
language of science, which

00:48:04.710 --> 00:48:10.230
is on the way to being able to
perform at science, to actually

00:48:10.230 --> 00:48:12.180
do science.

00:48:12.180 --> 00:48:13.090
It's hard to develop.

00:48:13.090 --> 00:48:15.660
He notes that AIDS
activists were able to do so

00:48:15.660 --> 00:48:16.990
with a lot of hard work.

00:48:16.990 --> 00:48:20.070
He also ran this
interesting experiment,

00:48:20.070 --> 00:48:21.430
hard to know what to make of it.

00:48:21.430 --> 00:48:25.140
But where he did a quiz
along with a number

00:48:25.140 --> 00:48:29.070
of gravitational
wave researchers,

00:48:29.070 --> 00:48:32.220
and then showed the
answers, his answers--

00:48:32.220 --> 00:48:35.890
he studied the community
for over a decade.

00:48:35.890 --> 00:48:38.580
But he doesn't do
gravitational wave science.

00:48:38.580 --> 00:48:43.410
And actually, I think,
seven out of nine of a panel

00:48:43.410 --> 00:48:45.090
were unable to
distinguish his answers

00:48:45.090 --> 00:48:49.840
from those of practicing
gravitational wave scientists.

00:48:49.840 --> 00:48:51.840
And that wasn't to say
that he thinks it's easy.

00:48:51.840 --> 00:48:53.167
He did this for decades.

00:48:53.167 --> 00:48:54.750
He worked with these
folks for decades

00:48:54.750 --> 00:48:56.792
to acquire that level of
interactional expertise.

00:48:56.792 --> 00:48:58.499
But what he's trying
to say is that there

00:48:58.499 --> 00:49:01.380
is a fine line of distinction
between be able to communicate

00:49:01.380 --> 00:49:06.960
and critique and interact with
people in a field of expertise

00:49:06.960 --> 00:49:11.309
versus being able to design
and perform experiments.

00:49:11.309 --> 00:49:13.350
And I don't think it's a
matter of dumbing things

00:49:13.350 --> 00:49:19.170
down when we talk about
inviting other people into work.

00:49:19.170 --> 00:49:21.259
I think, as the commenter
said, that scientists

00:49:21.259 --> 00:49:23.550
aren't necessarily the best
at communicating knowledge.

00:49:23.550 --> 00:49:24.750
But that doesn't mean
that they're off the hook

00:49:24.750 --> 00:49:27.407
necessarily or that the
burden is on, exclusively,

00:49:27.407 --> 00:49:27.990
everyone else.

00:49:27.990 --> 00:49:30.320
I think that there has
to be some teamwork here.

00:49:30.320 --> 00:49:32.070
I'm going to move
forward, because I think

00:49:32.070 --> 00:49:33.622
we're running out of time here.

00:49:33.622 --> 00:49:35.040
[TAPS PODIUM]

00:49:35.040 --> 00:49:38.150
I did want to say--

00:49:38.150 --> 00:49:42.900
let's see, OK.

00:49:42.900 --> 00:49:46.580
I know that we often talk
about mass communication

00:49:46.580 --> 00:49:48.990
and so forth.

00:49:48.990 --> 00:49:52.260
But when outsider
groups are more

00:49:52.260 --> 00:49:57.420
able to challenge
expertise, we're

00:49:57.420 --> 00:50:00.970
living in an interesting time.

00:50:00.970 --> 00:50:03.690
I think there are positive and
negative ramifications of this.

00:50:03.690 --> 00:50:07.010
I think that the limitations
of science practice,

00:50:07.010 --> 00:50:08.760
that capacity, budgets,
some of the things

00:50:08.760 --> 00:50:12.510
these commenters very
clearly articulated,

00:50:12.510 --> 00:50:15.440
the fact that science isn't
suited for every problem we

00:50:15.440 --> 00:50:16.440
have on Earth, you know?

00:50:16.440 --> 00:50:21.330
It's not the end all, and it
cannot contain all knowledge.

00:50:21.330 --> 00:50:25.980
But I do think that there are
alliances that may be formed.

00:50:25.980 --> 00:50:28.230
I mentioned the maker
community, the hacker community.

00:50:28.230 --> 00:50:30.210
But also, environmental
justice groups

00:50:30.210 --> 00:50:35.130
who have worked for
decades to do science,

00:50:35.130 --> 00:50:38.580
but to do it to answer
questions about threats

00:50:38.580 --> 00:50:44.190
to their own health, to find
relationships between knowledge

00:50:44.190 --> 00:50:48.140
production and justice,
social justice,

00:50:48.140 --> 00:50:50.390
and who have been doing their
own monitoring and watch

00:50:50.390 --> 00:50:52.697
dogging, often with
very good relationships

00:50:52.697 --> 00:50:54.780
with the researchers who
choose to work with them.

00:50:57.290 --> 00:51:00.210
Yeah, again, I
think you can look

00:51:00.210 --> 00:51:03.420
at groups who use aerial
photography as Public Lab does

00:51:03.420 --> 00:51:07.920
or Google Street View to
investigate pollution issues.

00:51:07.920 --> 00:51:12.060
There are more empirical
means at our disposal today.

00:51:12.060 --> 00:51:16.890
And I wanted to mention, sort
of wrapping things up here,

00:51:16.890 --> 00:51:19.440
that Public Lab's participating
in the Environmental Data

00:51:19.440 --> 00:51:20.630
Governance Initiative.

00:51:20.630 --> 00:51:22.890
So Public Lab began
as an effort to create

00:51:22.890 --> 00:51:28.690
an independent record of the
BP spill, a separate data set.

00:51:28.690 --> 00:51:31.110
But with the
transition happening,

00:51:31.110 --> 00:51:33.840
the presidential
transition, EDGI

00:51:33.840 --> 00:51:35.400
is an effort to
download and archive

00:51:35.400 --> 00:51:37.560
EPA data before the
transition potentially

00:51:37.560 --> 00:51:40.330
cuts off access
or destroys data,

00:51:40.330 --> 00:51:42.420
as actually has happened
in previous presidential

00:51:42.420 --> 00:51:43.890
transitions.

00:51:43.890 --> 00:51:45.600
It's sort of a
breakneck effort that's

00:51:45.600 --> 00:51:48.150
been put together
over the past 10 weeks

00:51:48.150 --> 00:51:53.910
to literally, like, scrape
and download everything

00:51:53.910 --> 00:51:57.270
that the government
has online currently.

00:51:57.270 --> 00:52:01.590
Anyway, I mostly-- you
know, I don't have any where

00:52:01.590 --> 00:52:02.810
near all the answers here.

00:52:02.810 --> 00:52:04.309
But I'm trying to
ask hard questions

00:52:04.309 --> 00:52:06.450
and propose ways forward.

00:52:06.450 --> 00:52:09.300
I really am trying to find
places to build bridges

00:52:09.300 --> 00:52:12.480
and to build alliances
and not walls.

00:52:12.480 --> 00:52:15.570
And I think that
getting closer to people

00:52:15.570 --> 00:52:17.880
personally, getting to
know people personally

00:52:17.880 --> 00:52:21.660
who are outside of
your particular circle,

00:52:21.660 --> 00:52:23.190
is really powerful.

00:52:23.190 --> 00:52:25.800
To learn what people
know, what they need,

00:52:25.800 --> 00:52:30.420
even if you don't always
agree, and primarily

00:52:30.420 --> 00:52:34.090
to not assume that information
flows only one direction.

00:52:34.090 --> 00:52:36.120
So OK, I'll put the
hardest question up.

00:52:36.120 --> 00:52:39.840
Is bad science, like science
that doesn't serve the public,

00:52:39.840 --> 00:52:43.530
or that is misleading,
is it science gone wrong

00:52:43.530 --> 00:52:44.700
or is it science as usual?

00:52:44.700 --> 00:52:46.992
Is there something
fundamental about the way

00:52:46.992 --> 00:52:48.450
that we're doing
science today that

00:52:48.450 --> 00:52:49.824
needs to be reformed
in some way,

00:52:49.824 --> 00:52:51.540
or are there a
number of bad actors

00:52:51.540 --> 00:52:53.040
who are taking
advantage of science?

00:52:53.040 --> 00:52:57.490
And really, those are sort of
two sides of the same coin.

00:52:57.490 --> 00:52:59.997
I mean, in the sense that
if there are bad actors,

00:52:59.997 --> 00:53:01.830
we could reform science
to try to stop them.

00:53:06.580 --> 00:53:08.340
And Collins says that--

00:53:08.340 --> 00:53:11.670
well, I mentioned this sort
of idea of when we abhor--

00:53:11.670 --> 00:53:14.010
when there are bad actors,
when we can recognize

00:53:14.010 --> 00:53:15.960
when it is going wrong.

00:53:15.960 --> 00:53:18.479
And then, really, these
are things that I'm

00:53:18.479 --> 00:53:19.770
sure people have thought about.

00:53:19.770 --> 00:53:22.470
But you know, is science more
inclusive as a profession?

00:53:22.470 --> 00:53:24.430
Is it more inclusive
in its conclusions?

00:53:24.430 --> 00:53:29.100
And I guess is the broader
direction of science,

00:53:29.100 --> 00:53:32.040
and specifically, its questions
more than its answers,

00:53:32.040 --> 00:53:33.950
simply what we make of it?

00:53:33.950 --> 00:53:35.880
And I'm very clear
in that distinction.

00:53:35.880 --> 00:53:38.550
Because I don't mean that its
answers are what we make of it.

00:53:38.550 --> 00:53:42.471
But I do mean that we can
choose to pursue inquiry

00:53:42.471 --> 00:53:43.470
in different directions.

00:53:43.470 --> 00:53:49.080
And we can choose to
structure what we ask,

00:53:49.080 --> 00:53:52.608
even if we can't choose to
structure what we find out.

00:53:52.608 --> 00:53:53.560
Thank you.

00:53:53.560 --> 00:53:58.810
[APPLAUSE]

00:53:58.810 --> 00:54:01.541
AUDIENCE: I've been involved
with data collection

00:54:01.541 --> 00:54:05.400
in numerous ways that have
been citizen called for.

00:54:05.400 --> 00:54:08.620
One was with lead in
the soil, and the other

00:54:08.620 --> 00:54:12.370
was monitoring the
river out here.

00:54:12.370 --> 00:54:19.035
But now I see a really,
really important area

00:54:19.035 --> 00:54:24.090
for citizens in our
communities in having

00:54:24.090 --> 00:54:27.750
the skill to, you
might say, cross

00:54:27.750 --> 00:54:33.973
examine the experts, especially
around infrastructure projects.

00:54:33.973 --> 00:54:36.970
And I'm thinking
of the gas projects

00:54:36.970 --> 00:54:40.350
in Massachusetts, where
there've been a lot of hearings

00:54:40.350 --> 00:54:44.430
and the scientists,
or I would say,

00:54:44.430 --> 00:54:48.730
the utility representatives
have a lot of expertise.

00:54:48.730 --> 00:54:50.728
JEFF WARREN: Yeah.

00:54:50.728 --> 00:54:56.432
AUDIENCE: And so there
you have a great deal

00:54:56.432 --> 00:54:59.084
of information on their part.

00:54:59.084 --> 00:55:02.670
And then you have these limited
opportunities for citizens

00:55:02.670 --> 00:55:04.780
to raise their hand,
like, wait a minute,

00:55:04.780 --> 00:55:08.210
aren't we getting too
overdependent on gas.

00:55:08.210 --> 00:55:13.450
And what we don't have
is equivalent ability

00:55:13.450 --> 00:55:18.116
to question the basis for
how do you make decisions

00:55:18.116 --> 00:55:20.950
about these things and
being able to influence

00:55:20.950 --> 00:55:22.506
the decisions that are made.

00:55:22.506 --> 00:55:31.440
So I see a gap there with
whatever community ability we

00:55:31.440 --> 00:55:32.910
can --

00:55:32.910 --> 00:55:34.610
We need help in that vein.

00:55:34.610 --> 00:55:35.360
JEFF WARREN: Yeah.

00:55:35.360 --> 00:55:37.826
There's certainly
an asymmetry to it.

00:55:37.826 --> 00:55:39.200
And it's very
difficult to have--

00:55:43.070 --> 00:55:45.380
I mean, for example,
self-reporting is

00:55:45.380 --> 00:55:50.000
a common mechanism in
terms of regulations

00:55:50.000 --> 00:55:52.880
for producing knowledge
about emissions

00:55:52.880 --> 00:55:55.040
or about potential pollution.

00:55:55.040 --> 00:55:58.742
But self-reporting is
not blind, you know?

00:55:58.742 --> 00:56:01.970
It's telling people
what you did.

00:56:01.970 --> 00:56:05.120
And often, like in
Louisiana, a lot

00:56:05.120 --> 00:56:08.505
of, say, smokestack emissions
are based on estimates.

00:56:08.505 --> 00:56:10.880
They're not even actually
based on empirical measurements

00:56:10.880 --> 00:56:13.790
that you perform yourself
as an operator of a gas

00:56:13.790 --> 00:56:17.000
facility or a refinery.

00:56:17.000 --> 00:56:19.320
So it's very alarming, because
the standard of evidence

00:56:19.320 --> 00:56:21.320
is almost meaningless.

00:56:21.320 --> 00:56:25.280
It's like, I think
we probably, maybe,

00:56:25.280 --> 00:56:28.680
emitted this much
lead last night.

00:56:28.680 --> 00:56:32.030
We're next to a community,
like a residential community.

00:56:32.030 --> 00:56:34.260
So it's very troubling.

00:56:34.260 --> 00:56:36.440
I mean, part of
this is asymmetry is

00:56:36.440 --> 00:56:39.660
cost as well as expertise.

00:56:39.660 --> 00:56:43.430
And I think the equipment to
measure gas, if it's cheaper,

00:56:43.430 --> 00:56:45.480
it makes a lot of this easier.

00:56:45.480 --> 00:56:48.860
But it's not the whole
equation, for sure.

00:56:48.860 --> 00:56:54.107
One example I wanted to share
actually that I forgot was--

00:56:54.107 --> 00:56:55.690
so a lot of the
community groups we've

00:56:55.690 --> 00:56:59.960
worked with in places
affected by oil and gas

00:56:59.960 --> 00:57:02.870
will grab sample measurements.

00:57:02.870 --> 00:57:06.710
So they take a bucket,
and they use a vacuum,

00:57:06.710 --> 00:57:11.259
and they suck air into a
gas bag inside the bucket.

00:57:11.259 --> 00:57:12.800
And then they mail
that entire bucket

00:57:12.800 --> 00:57:15.730
to a lab to get a
certified test done

00:57:15.730 --> 00:57:18.570
of analysis of the contents.

00:57:18.570 --> 00:57:21.800
And what is nice about this is
that it allows these community

00:57:21.800 --> 00:57:24.410
groups to choose, based
on their deep knowledge

00:57:24.410 --> 00:57:27.020
of the patterns-- like, do
the facilities typically emit

00:57:27.020 --> 00:57:27.520
at night?

00:57:27.520 --> 00:57:30.690
Do they emit at certain times,
certain days of the week?

00:57:30.690 --> 00:57:31.580
Are there signals?

00:57:31.580 --> 00:57:34.940
Like, is there a flare up that
you see, or is there an alarm,

00:57:34.940 --> 00:57:36.320
stuff like that
that enables them

00:57:36.320 --> 00:57:42.440
to structure when they take the
samples in order to sort of,

00:57:42.440 --> 00:57:45.952
like, catch the emission
at the right moment.

00:57:45.952 --> 00:57:48.410
What's nice about it also is
that it's a standardized test.

00:57:48.410 --> 00:57:50.750
So they can send it
to different labs.

00:57:50.750 --> 00:57:53.460
They're sort of, in a
sense, made it a service

00:57:53.460 --> 00:57:59.960
that these labs provide,
as opposed to the people

00:57:59.960 --> 00:58:02.360
collecting the sample being
the service part of it.

00:58:02.360 --> 00:58:03.900
So it's sort of inverting
that in a nice way.

00:58:03.900 --> 00:58:05.330
And the thing that was
really remarkable to me

00:58:05.330 --> 00:58:07.288
is that several of these
communities that we've

00:58:07.288 --> 00:58:13.620
spoken with and worked with
will actually not trust labs--

00:58:13.620 --> 00:58:15.540
one of them didn't
trust in state labs.

00:58:15.540 --> 00:58:17.540
And one of them just
doesn't trust a lot of labs

00:58:17.540 --> 00:58:19.790
in general, because
they feel that there

00:58:19.790 --> 00:58:22.580
may be some of these
labs do work for

00:58:22.580 --> 00:58:26.220
and accept money from
oil and gas companies.

00:58:26.220 --> 00:58:29.960
And so what they did, which
was really remarkable to me,

00:58:29.960 --> 00:58:31.441
is they faked samples.

00:58:31.441 --> 00:58:33.440
They made positive and
negative control samples.

00:58:33.440 --> 00:58:35.190
And then they sent
those to labs at a cost

00:58:35.190 --> 00:58:36.860
of hundreds of
dollars per sample,

00:58:36.860 --> 00:58:39.470
in order to test the labs.

00:58:39.470 --> 00:58:43.490
And only after confirming that
these labs would correctly

00:58:43.490 --> 00:58:47.180
report different levels of
preprepared positive and

00:58:47.180 --> 00:58:49.640
negative samples, did
they then use that lab

00:58:49.640 --> 00:58:52.170
for their own real sampling.

00:58:52.170 --> 00:58:54.170
And you can imagine that
if community groups are

00:58:54.170 --> 00:58:59.060
already under resourced and
find it difficult to marshal

00:58:59.060 --> 00:59:02.150
their resources to
do testing at all,

00:59:02.150 --> 00:59:07.480
it's not trivial to spend all
that money to establish trust.

00:59:07.480 --> 00:59:10.550
But I thought it was a really
interesting example of science

00:59:10.550 --> 00:59:12.320
being done on
scientists, you know?

00:59:12.320 --> 00:59:14.910
And I think it's a positive--
it's actually a positive thing,

00:59:14.910 --> 00:59:16.520
you know?