Translator: Nadine Hennig Reviewer: Mile Živković
Disasters are inevitable.
Somewhere there's going to be a disaster
and, intrinsically, we're going to be moved to help out.
How do we help out?
Send money, send goods, provide our skills, our expertise.
Volunteers are a crucial part of the disaster-response process.
But their unannounced spontaneous arrival
on a disaster scene, if it goes unmanaged, can also create a difficult situation.
How else can we contribute
without being present even at the disaster scene?
Well, it turns out, the information age
has already changed the way we respond to disasters.
When we think back to the 2010 Haiti earthquake,
there was no good map available over the affected area.
People, volunteers, from the OpenStreetMap community,
started tracing roads from available satellite imagery,
and quickly put together a high-resolution map
that was being used by responding organizations in that event.
And that was just the beginning.
With every new major disaster, there has been a new form of technology,
a new milestone and leveraging of crowdsourcing and social media
to help respond to disasters.
This is a picture of the Kathmandu Living Lab,
setting up their first situation room in a car park
with buildings still rattling behind them from aftershocks.
Kathmandu Living Labs mobilized a platform called "Quake Map",
and they massively crowdsourced what's needed, where it's needed
and who can provide this information.
The Nepali army and many other organizations
were using crowdsourced information in their own response and organization.
So as crowdsourcing and social media
have proven to be a successful paradigm in disaster response,
the question is: How can we use all this information?
How can we make sense of this plethora of data
and information and use it for decision-making?
The other way of phrasing that:
Is there is a role for experts to put to test the scientific model,
to bring their research to try to analyze this information
as it's becoming available from an event?
And can they do it quickly enough to actually support decision-makers?
The challenge in all of this is delivering the right information
to the right person at the right time.
The old scientific model is constantly challenged
by this fast-paced environment
when we publish our findings
months or years after an event has already passed.
But there is a new frontier for science enabled by open access
and availability of high-resolution data, and enabled by new forms of collaboration.
We started an experiment
at the Center for Disaster Management and Risk Reduction Technology
- CEDIM - in 2011.
We started an experiment thinking:
Can we put scientific method and our own know-how and research tool
to rapidly start analyzing data as it was becoming available
in order to make sense of information, and then quickly generate reports
days after the event where we produce our findings?
Anytime there is a major disaster,
there are 30 or so scientists at the CEDIM center
and a subset of these come together as a task force.
We then work intensively, gathering data, making sense of it,
and produce our reports days after the event
with subsequent updates.
We've now analyzed a number of events since 2011.
But to give you a better feeling
for how a forensic disaster analysis approach works in near real time,
let me take you through one example of the work we did,
after the 2015 Nepal earthquake.
There was a tremendous amount of information that was becoming available
after the Nepal earthquake.
Maps of damaged and destroyed buildings,
maps of spontaneous shelter sites,
were all being put together, crowdsourced and made available,
shared globally on OpenStreetMap.
The bars show the number of spontaneous shelter sites
that were popping up
as soon as the satellite imagery became available for these to be mapped.
It started with two thousand spontaneous shelter sites of five to fifty tents.
And after the second earthquake, there was a fear of aftershocks
driving people towards leaving their homes and staying in tents.
And by the end of the first month,
there were 16,000 spontaneous shelter sites.
I'll tell you why this is interesting for us.
We were in Nepal, one year before the earthquake,
and we had this research project with a shelter demand model
where we tried to look at what would be the capacity of Kathmandu city
to house and accommodate displaced persons.
And we ran a scenario earthquake to see where would people be displaced
and how many people would be displaced.
And when we looked at this data, our model utterly failed.
The reason is that we were looking at designated open spaces -
spaces the government created and said,
"These are going to be managed sites that people are going to come to
after a major earthquake."
And it turns out people did not like going to those open spaces.
They preferred much more to stay close to their homes in their neighborhoods,
social ties and livelihoods, and set up these spontaneous shelter sites
scattered all around the city and other parts of Kathmandu
in small spaces that were available anywhere near their damaged buildings.
So we wanted to understand that;
that had implications in our model.
Four of us went to the field, six weeks after the earthquake,
developed this shelter survey
to look at decision factors among households,
and how they seek shelter.
And as we're talking to organizations,
we came across the International Organization for Migration (IOM),
and they had very similar questions.
The monsoon was coming up.
They knew already, people reacted to the aftershocks,
and they expected,
there would be another wave of spontaneous sheltering in the monsoon
with a fear of landslides.
They were very interested to see a group of researchers is following this.
We sat down with them
and actually integrated some of their questions into our survey.
And in this way, when we did our analysis,
we were able to feedback into that mechanism
and help them with some of their operations on the ground.
We happened to meet IOM and happened to be in Nepal,
and understand that our research has value to actual decision-makers on the ground.
But what's missing?
We are able to produce all kinds of reports right after the earthquake.
Two days, we produced our initial report of our findings of the earthquake,
and before the second earthquake on 12th May, we produced two more reports.
We went into the field in June, came back with our shelter survey
and looked at that and presented that and gave it to the organizations
that we were involved with in the field.
And then we transitioned from a task force more into a research team
and followed up a more in-depth investigation.
And in a second survey and a third one just in April,
when we also attended a conference and presented our findings.
How do we bring a more effective dialogue
between researchers like us
and people who might actually benefit from our research?
Disasters focus our attention.
They provide an opportunity for people to be looking at the same picture
and media helps out with that.
People want to help. How can we leverage that?
How can we create a more effective dialogue
where people who have issues and problems after a disaster
can express those, and those that have the expertise to solve them,
can provide their knowledge and make that available?
For the remainder of the talk,
I want to provide you with three possibilities,
three ways, three existing platforms
that are there for scientists and experts to already contribute to this process.
Documentation is a big part of what we do as scientists.
It turns out
the most powerful implementation of documenting disasters to date
is Wikipedia,
with its integration of the powers of the World Wide Web
and the collective intelligence of its millions of contributors;
it's coming and approaching close to the ideal of a global memory.
148,000 disaster-related articles are in Wikipedia.
And if you type any disaster name in Google,
the first search result will be a Wikipedia page.
Incidentally, 70% of the edits
on disasters made after 2008 -
that's a year when Wikipedia got a little bit more popularity
in terms of this - are made within the first two weeks.
In other words, the place people go to find out information about disasters
has content that is generated in only two weeks.
I started looking at this
and Wikipedia entries on disasters after 2001 for big earthquakes -
earthquakes with more than a hundred fatalities.
And it's striking to see,
the Indian ocean tsunami in 2004 and Katrina hurricane in 2005
- events that are 10 years back -
are still getting upwards of a hundred thousand views.
That's a huge impact in terms of reaching the public.
What's also striking to see: There are still large earthquakes,
the 2005 Kashmir earthquake, the 2001 Gujarat earthquake.
We have a wealth of information about this in the science literature
but just a few kilobytes of text on them on Wikipedia pages.
There is certainly room to improve content on these entries in Wikipedia.
And Wikipedia cannot be just the number one place
people go to learn about information on disasters.
But it can also be
the most reliable near real-time source of disaster information.
If documentation is one pillar of science communication,
deliberation surely must be another.
Deliberation is the thoughtful process
of weighing options,
using both facts and value.
Deliberation gets complex on blogs, on Facebook-style conversation.
It's hard sometimes to see the good stuff for all the noise.
There is an innovative tool
the MIT Center for Collective Intelligence put out in the world,
called the Deliberatorium.
The trick with the Deliberatorium is that it organizes contributions by topic
rather than by the order in which they appear.
Anyone on the Deliberatorium can present an issue
and others can come up with ideas or options to address those issues;
while others look at those ideas,
they might offer arguments and information supporting that,
or arguments and information rebutting it.
The trick here is that you have to unbundle your thoughts
into points that present one issue,
one idea, one argument, and it quickly allows you
to see an argument map and find where your points can be located,
and perhaps if they've been made already,
and allows for collective intelligence to be sampled
and among a diverse distributed and large group of stakeholders
to arrive at some solution ideas.
We collaborated with Mark Klein,
the developer of the Deliberatoirum platform
and a Rockefeller challenge grant,
to look at the application of this platform in disasters.
A disaster collaboratorium where all kinds of stakeholders
can get together and express issues that are becoming relevant in real time
and seek the global intelligence, the global wisdom.
The knowledge and information of a various group of experts
that can contribute to that would be a very powerful tool.
Finally, just because you have a solution idea
that doesn't mean you've solved the problem.
Solving problems requires resources, requires effort,
and that usually means funding.
Luckily, there are over 500 different crowdfunding plateforms available
where people can present their ideas
and then seek to get funding from the crowd,
if their ideas are interesting enough.
One of these put two very big problems in disasters together
and came up with an innovative solution.
One is the issue of debris, and garbage, and concrete,
which has big environmental impact
after the damage and destruction of a disaster.
How do you deal with that?
The other is: How do you provide housing to people in a disaster,
when the price of construction material is high
and it's rare to find construction material?
And a concrete engineering expert
thought about creating a geopolymer concrete
out of this recycled material to address the sheltering issue
at low cost and high values of production.
He got funded by the crowd to test his idea
and he's looking for a second phase.
So I've talked to you about how we at CEDIM use our skills,
our methods, our analyses, to generate findings,
interpret an insight after a disaster and do it in real time, near real time.
I think, this can be scaled up to include many more.
There's just 30 of us at CEDIM
but imagine the power of the world's experts coming together
and working for limited time in this type of mode.
I also presented a few platforms, any expert can now go to,
in a way of contributing their knowledge.
What if we could cultivate a global brain with its roots deep and wide,
so that people who needed information could tap into that,
express their problems and seek solutions?
So if you're an expert or you're a scientist,
a practitioner, anyone with any knowledge or skill
that can contribute to a disaster, I want to put out a challenge,
a call to action.
If you believe in the power of collective intelligence
to solve problems with a diverse distributed large crowd,
the next event will focus the world's attention.
It's an opportunity for us to get involved.
It's an opportunity to see what would be the issues that are arising.
Maybe you're the one
who will have the right solution to the right person at the right time.
Thank you.
(Applause)