ideas.ted.com Open in urlscan Pro
2a04:fa87:fffd::c000:422c  Public Scan

Form analysis
4 forms found in the DOM

GET https://ideas.ted.com/

<form role="search" method="get" class="search-form closed" action="https://ideas.ted.com/">
  <a href="#" class="search-form-link">
		<img src="https://ideas.ted.com/wp-content/themes/ted-ideas/assets/images/search.svg" alt="Search Icon" class="search-icon">
	</a>
  <label class="screen-reader-text">Search for:</label>
  <div class="search-field-group">
    <input type="search" class="search-field" placeholder="Search ..." value="" name="s" title="Search for:">
    <input type="submit" class="search-submit hidden" value="Search">
  </div>
</form>

GET https://ideas.ted.com/

<form role="search" method="get" class="search-form closed" action="https://ideas.ted.com/">
  <a href="#" class="search-form-link">
		<img src="https://ideas.ted.com/wp-content/themes/ted-ideas/assets/images/search.svg" alt="Search Icon" class="search-icon">
	</a>
  <label class="screen-reader-text">Search for:</label>
  <div class="search-field-group">
    <input type="search" class="search-field" placeholder="Search ..." value="" name="s" title="Search for:">
    <input type="submit" class="search-submit hidden" value="Search">
  </div>
</form>

Name: mc-embedded-subscribe-form — POST //ted.us1.list-manage.com/subscribe/post?u=07487d1456302a286cf9c4ccc&id=794c227a0b

<form action="//ted.us1.list-manage.com/subscribe/post?u=07487d1456302a286cf9c4ccc&amp;id=794c227a0b" method="post" id="mc-embedded-subscribe-form" name="mc-embedded-subscribe-form" class="validate" target="_blank" novalidate="">
  <input type="hidden" name="list_id" value="794c227a0b">
  <div id="mc_embed_signup_scroll">
    <input type="email" value="" name="EMAIL" class="email ted-newsletter" id="mce-EMAIL" placeholder="Sign up with your email address" required="">
    <div class="mailchimp-error"></div>
    <!-- real people should not fill this in and expect good things - do not remove this or risk form bot signups-->
    <div style="position: absolute; left: -5000px;"><input type="text" name="b_07487d1456302a286cf9c4ccc_794c227a0b" tabindex="-1" value=""></div>
    <div class="clear"><input type="submit" value="Sign Up" name="subscribe" id="mc-embedded-subscribe" class="ted-gray-button"></div>
  </div>
</form>

Name: mc-embedded-subscribe-form — POST //ted.us1.list-manage.com/subscribe/post?u=07487d1456302a286cf9c4ccc&id=794c227a0b

<form action="//ted.us1.list-manage.com/subscribe/post?u=07487d1456302a286cf9c4ccc&amp;id=794c227a0b" method="post" id="mc-embedded-subscribe-form" name="mc-embedded-subscribe-form" class="validate" target="_blank" novalidate="">
  <input type="hidden" name="list_id" value="794c227a0b">
  <div id="mc_embed_signup_scroll">
    <input type="email" value="" name="EMAIL" class="email ted-newsletter" id="mce-EMAIL" placeholder="Sign up with your email address" required="">
    <div class="mailchimp-error"></div>
    <!-- real people should not fill this in and expect good things - do not remove this or risk form bot signups-->
    <div style="position: absolute; left: -5000px;"><input type="text" name="b_07487d1456302a286cf9c4ccc_794c227a0b" tabindex="-1" value=""></div>
    <div class="clear"><input type="submit" value="Sign Up" name="subscribe" id="mc-embedded-subscribe" class="ted-gray-button"></div>
  </div>
</form>

Text Content

Menu ideas.ted.com
Ideas change everything

How can we save more lives during a refugee crisis? See it coming before it
hits.
Search for:

 * Tech
 * Business
 * Arts + Design
 * Science
 * We humans

Search for:

Tech


HOW CAN WE SAVE MORE LIVES DURING A REFUGEE CRISIS? SEE IT COMING BEFORE IT
HITS.

Jun 19, 2018 / Lauren Schenkman


SHARE THIS IDEA

 * Click to share on Facebook (Opens in new window)
 * Click to share on Twitter (Opens in new window)
 * Click to share on LinkedIn (Opens in new window)
 * Click to share on Reddit (Opens in new window)
 * Click to share on Pocket (Opens in new window)
 * Click to share on WhatsApp (Opens in new window)
 * 

Photo by UNHCR / F. Noy (CC BY-SA 2.0)


REFUGEE ADVOCATE RANA NOVACK IS USING AI TO HELP PREDICT NEW WAVES OF MIGRATION
— SO THE WORLD CAN HELP BEFORE DISASTER STRIKES.

Mass migrations are part of our modern reality: The number of people forcibly
displaced from their homes, by war or persecution, ballooned to 68.5 million
people in 2017, according to the UN. Many of these people stay somewhere in
their home countries, but a large group — some 25.4 million people by 2017 —
have been forced to leave their countries altogether, officially becoming
refugees. And “a reactionary response is just not the smartest way to deal with
it,” says refugee advocate Rana Novack (TED@IBM Talk: How we’ll predict the next
refugee crisis). That’s why she’s helping to develop a computational model in
order to predict migrations between countries in a given year. If it works, the
software could provide a potentially life-saving advantage to policy makers,
humanitarian groups and national governments: the ability to plan ahead for a
refugee crisis — before it happens.

In September 2015, Alan Kurdi, a three-year-old Syrian boy, became the symbol of
the refugee crisis after a photo of his tiny body, lying dead on a Turkish
beach, was published worldwide. For Novack, the tragic image epitomizes the
failure of the international response to refugees. The Kurdi family had fled
war-torn Syria for Turkey. Refugees couldn’t legally work there, and while the
family hoped to immigrate to Canada, strict laws made it unlikely they’d be
granted asylum in that nation. But without a safe or legal way to move somewhere
they could work, they put their lives in the hands of human traffickers and
tried to reach Greece in an inflatable boat. It capsized, and Alan and his
five-year-old brother drowned, joining the over 3,600 other refugees who died
while trying to cross the eastern Mediterranean in 2015. The world was shocked,
but Novack wasn’t. “How could this come as a surprise?” she remembers thinking.
“We didn’t leave them any other choice.”

Novack was familiar with this kind of desperation. The US-born daughter of
Syrian immigrants, she was scrambling at the time to help her extended family in
Syria relocate to a safe place. But when she called humanitarian organizations
for advice, she was told point-blank: Her family members, like more than four
million other Syrians in 2015, would have to cross the border on their own
before they could get emergency assistance in a refugee camp. In other words,
while the agencies knew that a massive crisis was unfolding in Syria, they had
no plan; individuals and families had to make a potentially illegal, expensive,
life-threatening border crossing before they could get any help. This made no
sense to Novack. Working in business development at IBM, she knew about modern
computing’s ability to predict future scenarios, even complex ones. “The idea of
being able to predict a crisis, to proactively respond — it’s not rocket
science,” she says. “Think of a hurricane or a flood. We can do these things for
natural disasters, so why can’t we do these things for manmade disasters?”

Businesses already use sophisticated models to predict human behavior. “If they
can tell me what kind of shirt I want to buy, there must be a way for us to
predict the refugee crisis,” she recalls thinking. She began talking to the
engineers around her. A team came together, including IBM researcher Rahul Nair,
who was studying how people move within cities in order to design smarter bus
networks. As Novack put it: “There’s a measurable set of circumstances. We can
study them and we can analyze them. And we can better support these people.”

Many factors influence whether an individual will decide to flee their country,
and where they’ll go if they do. Geographers call them “push-pull factors.” Push
factors, such as unemployment, conflict and violence, are the ones that pressure
people to leave their home countries. Pull factors, which include perceived
economic opportunity or an existing immigrant community, might attract migrants
to a particular nation. To capture these factors, the team compiled and parsed
international news on migration going back to 2010, as well as development and
economic data from sources like the World Bank going back to the 1960s. Another
factor: the distance between countries, which is a quantity that encompasses
more than simply mileage. As Nair points out, while migrants often try to stay
closer at first — large numbers of Syrian refugees went to Lebanon, for example
— migrants from Francophone Africa are drawn to France, whereas West Indians are
likely to go to Britain, where strong communities exist because of past
colonization. For each pair of linked countries, the team also fed in data
representing physical distance, language and colonial links.

Computational models learn from past data to create a complex mathematical
relationship between causes and effects. The process is known as supervised
machine learning. The team gave its model the inputs — the historical data on
these push, pull and distance factors for 189 countries — and the output — the
last 15 years of migration numbers as sourced from the UNHCR. By analyzing these
inputs and outputs, the model figured out a mathematical relationship between
them so that, given push, pull and distance factors, it could calculate
migration numbers for the year ahead. Just as a business algorithm might produce
a long-range sales forecast, their strategic model predicts the average number
of migrants between any two of 189 countries in the world over a coming year.
Since many other forces can have a major impact on migration — such as when
Hungary closed its border with Croatia in October 2015 — the team included the
ability to add scenarios like a policy change or border closure to see how
migration numbers are affected.

Once the team developed their model based on historical data, they tested it:
Could it have predicted the 2015 European refugee crisis? When they input the
push, pull and distance factors that were known at the time, the model then
calculated refugee flows in 2015. When the team checked these numbers against
real data for 2015, the average error rate was about 1,000 people per year per
country. This means the model doesn’t work for small migrations, says Nair — for
example, the number of Irish people going to Australia. But in mass migrations,
such as the 5.6 million people who have left Syria since 2011, the model could
be accurate enough to help make decisions.

The team also created a version of its model that produces short-term forecasts,
so NGOs can plan for refugee movements in the very near future. Like a
short-term weather forecast, this “operations model” takes recent refugee
arrival data, news and current weather for a given area, and then projects
arrivals at refugee camps on a day-by-day basis, up to three weeks out. A “flow
model” predicts the number of people in a given refugee camp who are expected to
move to another camp — in the same country or a different one — over this
period. These kinds of models could help organizations make better decisions
about moving resources and staff among the refugee camps they serve.

This data-based approach to migration gave new insights that weren’t being
captured on the ground. Typically,NGOs can only record the number of people
arriving at a camp on a given day. By looking at the larger picture, the IBM
team determined the rate at which people were moving between camps, and how long
it took for them to travel, say, from a refugee camp in Greece to one in
Austria. They saw new trends as well: for instance, high wind speeds on the
Mediterranean correlated strongly with fewer arrivals in Greece. It makes sense,
Nair says: “Smugglers and facilitators along the route would not launch their
boats on windy days.”

The IBM team is now collaborating with humanitarian organizations in Europe to
fine-tune their software. They’ve started a project with the Danish Refugee
Council (DRC), which is surveying Ethiopian refugees on their way out of the
country about why they leave. This data could help improve the IBM model’s
ability to predict the movement of refugees, because migration trends sometimes
run counter to what you might expect, according to Nair. For example, two
countries could have the same GDP, but many more people might flee from one
nation than the other. “There’s not a simple formulaic prescription for why
people would leave,” he says, and the Ethiopian survey data will allow the team
to start to tease out this complexity. While it’s still too early to report
results, the team has started combing through the DRC survey data with the goal
of mapping personal motives to the existing data on economic and
conflict-related factors. That could help them understand which pressures are
more important than others, and how exactly these larger forces interact to make
a person leave. A more detailed picture of the complex dynamics of migration
should result in a truer-to-life model and a sharper ability to predict when and
how mass movements may occur rather than being caught by surprise by a flood of
people. In the future, Nair also dreams of bringing in other sources of data,
such as their mobile phone location. “Migrants are particularly sensitive to
having phones; they keep them charged on journeys because they know that this at
least gives them a contact,” he says. The phones, like all mobile devices,
constantly share their locations with nearby cell towers; that, in turn, could
provide finer-grained information about refugee flows. But of course, says Nair,
the team would have to figure out how to do this while respecting privacy laws.

The goal is to predict the next refugee crisis before it happens. Since the
team’s strategic forecast provides refugee movements over a coming year (the
furthest ahead they can currently predict with any degree of accuracy), it’s
technically possible to set up safe ways for people to leave their countries
before they’re desperate enough to turn to smugglers and human traffickers, like
Alan Kurdi’s family did. “I think of the people putting their kids in a raft,
and every story I’ve read about people dying in the back of a truck … it was
because they were relying on a human trafficker to get them from point A to
point B,” Novack says. “If we knew the pathways that people were taking ahead of
time, then we could reinforce those pathways” and save lives. She dreams of
policy makers making proactive, positive decisions about refugees at the
national level. For example, two months after Kurdi’s death in September 2015,
Canada revised its immigration policy to bring in 10,000 Syrian refugees by the
end of that year; it has since welcomed tens of thousands more. But Novack says,
“Why do we we wait years into a crisis when thousands of people have drowned,
hundreds of thousands are killed, millions are displaced, and only then we talk
about opening our doors?”

Another good question: How can tech firms create more technology like this, tech
for the greater good, not just for profit? Novack’s team is part of IBM’s
philanthropic arm, but most humanitarian organizations can’t afford to develop
sophisticated software like this. As Novack puts it, “There’s an innovation gap
in the humanitarian sector.” She calls for tech companies to use their expertise
to help. Quite simply, as she puts it in her talk, “we have to make sure that
the people who want to do the right thing have the tools and the information
they need to succeed.”


ABOUT THE AUTHOR

Lauren Schenkman is a journalist and fiction writer. Her writing has appeared in
the New York Times Magazine, Granta, and the Hudson Review, and she was formerly
a reporter and editor at Science magazine.

 * AI
 * artificial intelligence
 * blog
 * Rana Novack
 * refugee crisis
 * refugees
 * Syria
 * technology
 * ted institute

Advertisement


FRESH IDEAS IN YOUR INBOX




TED TALK OF THE DAY


Al Gore

HOW TO MAKE RADICAL CLIMATE ACTION THE NEW NORMAL




TED TALK OF THE DAY


Al Gore

HOW TO MAKE RADICAL CLIMATE ACTION THE NEW NORMAL


SIGN UP FOR THE IDEAS NEWSLETTER


 * Similar
 * Popular

 * Tech
   
   
   THE EU IS GIVING CITIZENS THE "RIGHT TO REPAIR" ELECTRONICS -- HERE'S WHAT
   THAT COULD MEAN FOR THE WORLD

 * Tech
   
   
   MILLIONS OF TONS OF PLASTIC ARE TRASHED EVERY YEAR. BUT WHAT IF WE USED IT TO
   PAVE OUR ROADS?

 * Tech
   
   
   STOP THINKING OF YOUR KIDS’ GAMING TIME AS WASTED TIME; HERE’S WHY

 * Tech
   
   
   ZOOM FATIGUE IS REAL -- HERE'S WHY VIDEO CALLS ARE SO DRAINING

 * Tech
   
   
   HOW TO HELP YOUR KIDS BE RESPONSIBLE DIGITAL CITIZENS, FROM A TECH EXEC (AND
   MOM)

 * Tech
   
   
   YOU CAN HELP FIX WIKIPEDIA’S GENDER IMBALANCE -- HERE’S HOW TO DO IT

 * Tech
   
   
   WHY WE FALL FOR PHISHING EMAILS -- AND HOW WE CAN PROTECT OURSELVES

 * Tech
   
   
   A WAZE FOR WILDFIRES: LEARN HOW TECH IS ENABLING BETTER, EARLIER WILDFIRE
   DETECTION

 * We humans
   
   
   6 WAYS TO GIVE THAT AREN'T ABOUT MONEY


Business


THE WORLD’S REFUGEES NEED ALL THE HELP THEY CAN GET. HERE ARE 7 WAYS THAT
BUSINESSES CAN SUPPORT THEM


We humans


THE BEST WAY TO PREVENT TERRORIST ATTACKS? LET'S WELCOME REFUGEES.


We humans


5 WAYS THAT YOU CAN HELP REFUGEES


We humans


HOW CAN COUNTRIES HELP REFUGEES WHILE ALSO RAISING THEIR GDP? LET THEM WORK.

 * TED Talks Usage Policy
 * Privacy Policy
 * Advertising / Partnership
 * TED.com Terms of Use
 * Contact
 * Jobs
 * Press
 * Help

© TED Conferences, LLC Powered by WordPress VIP
Let’s talk cookies. Allowing the use of cookies helps us personalize your TED
experience and make data-informed decisions on how to improve TED for everyone.
Click “Accept” to agree to all cookies, or click “Settings” to review and select
which cookies you’d prefer.
Settings Accept



PRIVACY PREFERENCE CENTER

When you visit TED.com, we may store or retrieve information on your browser,
mostly in the form of cookies. You can learn more about this in our privacy
policy. We use cookies to customize your experience. We do not sell data
collected from cookies to any third party, but may provide information to
partners to help us update and maintain our website. The information does not
usually directly identify you, but it can give you a more personalized
experience. Because we respect your right to privacy, you can choose not to
allow some types of cookies. Click on the different consent preferences below to
find out more. As a reminder, blocking some types of cookies may impact your
browsing experience on TED.com.
Privacy Policy
Allow All


MANAGE CONSENT PREFERENCES

STRICTLY NECESSARY COOKIES

Always Active

These cookies are necessary for the website to function and cannot be switched
off in our systems. They are usually only set in response to actions made by you
which amount to a request for services, such as setting your privacy
preferences, logging in or filling in forms. You can set your browser to block
or alert you about these cookies, but some parts of the site will not then work.
These cookies do not store any personally identifiable information.

PERFORMANCE COOKIES

Performance Cookies

These cookies allow us to count visits and traffic sources so we can measure and
improve the performance of our site. They help us to know which pages are the
most and least popular and see how visitors move around the site. All
information these cookies collect is aggregated and therefore anonymous. If you
do not allow these cookies we will not know when you have visited our site, and
will not be able to monitor its performance.

FUNCTIONAL COOKIES

Functional Cookies

These cookies enable the website to provide enhanced functionality and
personalisation. They may be set by us or by third party providers whose
services we have added to our pages. If you do not allow these cookies then some
or all of these services may not function properly.

TARGETING COOKIES

Targeting Cookies

These cookies may be set through our site by our advertising partners. They may
be used by those companies to build a profile of your interests and show you
relevant adverts on other sites. They do not store directly personal
information, but are based on uniquely identifying your browser and internet
device. If you do not allow these cookies, you will experience less targeted
advertising.

Back Button


COOKIE LIST



Search Icon
Filter Icon

Clear
checkbox label label
Apply Cancel
Consent Leg.Interest
checkbox label label
checkbox label label
checkbox label label

Reject All Confirm My Choices