Hans Rosling No more boring data TEDTalks
Summary
TLDRThe speaker, with a background in studying hunger in Africa, shares his experience teaching global development to Swedish students. He highlights the surprising lack of knowledge among top students about global health, even comparing their performance to that of chimpanzees in a quiz. The speaker introduces a software tool that visualizes global data, showing significant improvements in child mortality and family planning across various countries. He emphasizes the importance of accessible and searchable public data to foster a deeper understanding of global development and challenges the audience to rethink their perceptions of 'developing' and 'developed' countries.
Takeaways
- 😯 The speaker, after 20 years of studying hunger in Africa, began teaching global health at the Karolinska Institute, where they discovered students' knowledge of global development was lacking.
- 📊 A pretest revealed that Swedish students knew less about global child mortality rates than would be expected by chance, highlighting a need for better global education.
- 🌍 The speaker developed software to visualize global data, showing the world's countries as bubbles with size representing population and axes for fertility rate and life expectancy.
- 📉 Over time, there's been a significant shift in global health and development, with many countries improving life expectancy and reducing family sizes.
- 🌐 The concept of 'developing countries' is challenged as the world's economic and health distribution is more nuanced than a simple rich-poor divide.
- 💸 The world's income distribution is not a gap but a spectrum, with most people falling in the middle, challenging the notion of a stark divide between rich and poor.
- 📈 Asia, particularly countries like China and Vietnam, has seen tremendous social and economic changes, with significant improvements in life expectancy and family planning.
- 🌱 The speaker emphasizes the importance of context when discussing global development, as there is vast variation within regions like Africa and South Asia.
- 🔍 There's a call for making publicly funded statistical data more accessible and searchable to facilitate better understanding and utilization of global information.
- 🌟 The speaker concludes with optimism about the potential for technology, such as affordable computers and improved data access, to contribute to global flattening and development.
Q & A
What was the speaker's initial task?
-The speaker's initial task was to teach global development to Swedish undergraduate students, particularly at the Karolinska Institute.
What did the speaker discover from the pretest given to students?
-The speaker discovered that Swedish top students statistically knew significantly less about the world than chimpanzees would by random chance.
What was the main issue the speaker identified with the students' knowledge?
-The main issue was not ignorance, but rather preconceived ideas and misconceptions about global health and development.
How did the speaker visualize the data on child mortality and fertility rates?
-The speaker used a software that displayed data with bubbles representing countries, where the size of the bubble indicated population, and axes represented fertility rates and life expectancy at birth.
What significant change has occurred in global health since 1962?
-Since 1962, there has been a significant change in global health where many countries have moved towards having smaller families and longer life expectancies.
What was the 'miracle' mentioned in the context of Bangladesh?
-The 'miracle' referred to the significant improvement in Bangladesh's health and family planning in the 1980s, leading to a notable upward shift in the country's position on the fertility and life expectancy graph.
How did the speaker compare the development of Vietnam and the United States?
-The speaker compared Vietnam and the United States by showing how Vietnam moved towards smaller families and longer life expectancies, similar to the United States, but at a different pace and time.
What is the main challenge the speaker sees in discussing global development?
-The main challenge is the vast differences within regions, such as Africa, which makes it difficult to generalize solutions or strategies for development.
Why did the speaker start the nonprofit venture called Gapminder?
-The speaker started Gapminder to liberate publicly-funded data and make it searchable and easily understandable through visual animations, thereby allowing for more informed discussions and decisions on global development.
What is the speaker's vision for the future of global data accessibility?
-The speaker envisions a future where publicly-funded data is freely accessible, searchable, and easily visualized, enabling a deeper understanding of global trends and development.
Outlines
🌍 Global Health Education and Preconceived Ideas
The speaker reflects on their experience teaching global development to Swedish undergraduate students, drawing from their 20 years of research on hunger in Africa. They initiated a global health course at the Karolinska Institute, but were surprised by the students' lack of knowledge on global health issues, as revealed by a pretest. The students' incorrect assumptions about child mortality rates in various countries were compared to the performance of chimpanzees, highlighting a need for better communication of global data. The speaker then introduces a software tool that visualizes global health data, showing how countries have evolved in terms of life expectancy and fertility rates since 1962. The tool challenges the outdated 'us versus them' mentality and emphasizes the importance of context-specific solutions in global health.
📊 Income Distribution and Social Change
This paragraph discusses the distribution of global income and the social changes that have occurred since the 1960s. The speaker debunks the myth of a disappearing gap between the rich and the poor, showing that while there is still a significant income disparity, the majority of the world's population falls in the middle. They highlight the dramatic social changes in Asia, particularly in Vietnam, where family planning and market economy reforms led to significant improvements in life expectancy and family size, paralleling developments in the United States. The speaker also touches on the importance of contextualizing economic discussions, as the same strategies for wealth distribution and social welfare do not apply uniformly across different regions and countries.
🌐 Variability in Development Across Regions
The speaker explores the variability in development within different regions of the world, emphasizing that generalizations about entire continents can be misleading. They discuss the diversity within Africa, South Asia, and the Arab states, pointing out that each region contains a wide range of economic and social conditions. The speaker also compares the development trajectories of South Korea and Brazil, illustrating how countries can move in different directions despite similar starting points. They argue for a more nuanced understanding of global development, where health and education investments are as important as economic growth, using the example of the United Arab Emirates to show how investments in health can lead to significant improvements in child survival rates.
💡 Unlocking the Potential of Public Data
In this paragraph, the speaker advocates for the liberation of publicly-funded data to better inform and educate the public about global trends. They criticize the lack of accessibility and searchability of statistical data, which is often hidden away in databases. The speaker shares their experience founding Gapminder, a nonprofit venture aimed at making global data more accessible and understandable through visualization. They envision a future where data is freely available and easily searchable, allowing for the creation of informative and engaging visualizations that can help policymakers, educators, and the general public better understand and address global challenges.
🎨 The Value of Creative Ideas and Vision
The final paragraph shifts focus to the importance of nurturing creative ideas and artistic vision. While it is not directly related to the previous discussions on global health and data accessibility, it serves as a metaphor for the potential of harnessing data and technology to create meaningful change. The speaker suggests that just as artistic visions can be transformed into great works, so too can innovative ideas in data visualization and global health education lead to significant advancements in our understanding and approach to global issues.
Mindmap
Keywords
💡Global Development
💡Child Mortality
💡Preconceived Ideas
💡Fertility Rate
💡Life Expectancy
💡Industrialized Countries
💡Developing Countries
💡Gapminder
💡Data Visualization
💡Income Distribution
💡Publicly Funded Data
Highlights
The speaker took on the task of teaching global development to Swedish undergraduate students after spending 20 years studying hunger in Africa.
Swedish top students scored significantly less on a world knowledge pretest compared to chimpanzees, revealing preconceived ideas rather than ignorance.
The speaker used data visualization to show global trends, with each bubble representing a country and metrics such as fertility rate and life expectancy displayed on the axes.
In 1962, the world was divided between industrialized countries with small families and long lives, and developing countries with large families and short lives.
The visualization showed that countries like China, India, and Latin American nations improved in both health and family size over the years.
Bangladesh's 'miracle' in the 1980s was highlighted, where family planning significantly improved health and reduced family sizes.
The speaker showcased how Vietnam, through family planning and economic reform, achieved the same life expectancy and family size in 2003 as the U.S. had in 1974.
There is no longer a clear gap between rich and poor countries; instead, most people fall somewhere in the middle of the global income distribution.
The speaker emphasized the importance of using accurate global data, showing significant variability within regions like Sub-Saharan Africa and Latin America.
The role of publicly funded data was highlighted, but much of it remains inaccessible to the public, with databases locked behind passwords and paywalls.
Gapminder, a nonprofit founded by the speaker, aims to make global data more accessible and understandable through innovative visual tools.
A significant finding was that health improvements often precede wealth increases, as demonstrated by comparing countries like South Korea and Brazil.
The speaker demonstrated how income distribution in China has shifted since 1970, with China's income now overlapping with the U.S., highlighting the country's rapid growth.
The speaker argued that data visualization is a crucial tool for understanding complex global patterns, making it easier for students, policymakers, and the public to engage with data.
The presentation concluded by emphasizing the need to make publicly funded data more freely accessible and the role of technology, such as the $100 laptop, in bridging digital and educational divides.
Transcripts
about 10 years ago I took on the task to
teach global development to Swedish
undergraduate students that was after
having spent about 20 years together
with African institution studying hunger
in Africa so I was sort of expected to
know a little about the world and i
started in our medical university
karolinska institute an undergraduate
course called global health but when you
get that opportunity you get little
nervous I thought these students coming
to us actually have the highest grade
you can get in Swedish college system so
I thought maybe they know everything i'm
going to teach them about so i did a
pretest when they came and one of the
question from which i learned a lot was
this one which country has the highest
child mortality of these five pairs and
I put them together so that in each pair
of country one has twice the child
mortality of the other and this means
that it's much bigger the difference
than the uncertainty of the data I won't
put yer to test here but it's turkey
which is high as their Poland Russia
Pakistan and South Africa and these were
the results of the Swedish students I
did it so I got the confidence interval
which was pretty narrow and I got happy
of course at one point eight right
answer after five possible that means
that there was a place for a professor
of international health and for my
course but one light late night when I
was compiling the report I really
realized my discovery I have shown that
Swedish top students know statistically
significantly less about the world than
the chimpanzees
because the chimpanzee would score half
right if I gave him two bananas with Sri
Lankan turkey they would be right half
of the cases but the students are not
that the problem for me was not
ignorance it was preconceived ideas I
did also an unfair unethical study of
the professor's of the Karolinska
Institute that hands out the nobel prize
in medicine and they are on par with the
chimpanzee there so this is where I
realized that there was really a need to
communicate because the data or what's
happening in the world and the child
health of every country is very well
aware so we did this software which
displays it like this every bubble here
is a country this country over here is
this is China this is India the size of
the bubble is the population and on this
axis here I put fertility rate because
my students what they said when they
looked upon the world and I asked them
what do you really think about the world
huh well I first discovered that the
textbook was Tintin mainly and and they
said the world is still we and them and
we is Western world and them is third
world and what do you mean with Western
world I said well that's long life in
small family and third world is short
life in large family so this is what I
could display here I put fertility rate
here number of children per woman one
two three four up to about eight
children per woman we have very good
data since nineteen sixty-two 1960 about
on the size of families in all countries
the error margin is narrow here I put
life expectancy at Birth from 30 years
in some countries up to about 70 years
and 1962 that was really a group of
countries here that was industrialized
countries and they had small families
and long lives and these were the
developing countries they had large
families and they had relatively short
lives now what has happened since
nineteen sixty-two we want to see the
change or the students right it's still
two types of countries or have these
developing countries got smaller
families and they live here or have they
got longer lives and live up there let's
see we stop the world and this is all UN
statistic that has been a
here we go can you see that it's China
they're moving up against better health
are improving there or the green Latin
American countries they are moving
towards smaller families your yellow
ones here are the Arabic countries and
they get larger families but they no
longer life but not larger families the
Africans are the green down here they
still remain here this is India
Indonesia is moving on pity fest and in
the 80s here you have Bangladesh still
among the African countries there but
now Bangladesh it's a miracle that
happens in the 80s the mom start to
promote family planning and they move up
into that corner and in 90s we have the
terrible HIV epidemic that takes down
the life expectancy of the African
countries and all the rest of the mall
moves up into the corner where we have
long lives and small family and we have
a completely new world
let me make a comparison directly
between United States of America and
Vietnam 1964 America had small families
and long life vietnam had large families
and short lives and this is what happens
the data during the war indicate that
even with all the death that was an
improvement of life expectancy by the
end of the year the family planning
started in Vietnam and they went for
smaller families and the United States
up there is getting for longer life
keeping family size and in the 80s now
they give up communist planning and they
go for market economy and it moves
faster even in social life and today we
have in Vietnam the same life expectancy
and the same family size here in Vietnam
19 2003 as in the United States 1974 by
the end of the war I think we all if we
don't look in the data we underestimate
the tremendous change in Asia which was
in social change before we saw the
economical change so let's move over to
another way here in which we could
display the distribution in the world of
the income this is the world
distribution of income of people one
dollar $10 or 100 dollar per day there's
no gap between rich and poor any longer
this is a myth there's a little hump ear
but there are people all the way and if
we look where the income ends up the
income this is one hundred percent of
worlds annual income and the rich is
twenty percent they take out of that
about seventy-four percent and the poor
is twenty percent they take about two
percent and this shows that the concept
developing countries is extremely
doubtful we sort of think about aid like
these people here giving aid to these
people here but in the middle we have
most a world population and they have
now twenty four percent of income we
heard it in other forms and who are who
are these these where are the different
countries
I can show you Africa this is Africa ten
percent of world population most
impoverished is osed the rich country
the country club of the UN and they are
over here on this side and quite an
overlap between Africa and OECD and this
is Latin America it has everything on
this earth from the poorest to the
richest in Latin America and on top of
that we can put East Europe we can put
East Asia and we could South Asia and
how did it look like if we go back in
time to about 1970 then there was more
of a hump and we have most who lived in
absolute poverty were Asians the problem
in the world was the poverty in Asia and
if I now let the world move forward you
will seem that wild population increase
there are hundreds of millions in Asia
are getting out of poverty and some
others get into poverty and this is the
pattern we have today and the best
projection from the World Bank is that
this will happen and we will not have a
divided world we have most people in the
middle of course it's a logarithmic
scale here but our concept of economy is
growth with percent we look upon it as a
possibility of percent increase if I
change this and I take gdp per capita
instead of family income and I turn
these individual data into regional data
of gross domestic product and I take the
region's down here the size of the
bubble is still the population and you
have the OECD there and you have
sub-saharan Africa there and we take off
the Arab states they're coming both from
Africa from Asia and we put them
separately and we can expand this axis
and I can give it a new dimension here
by adding the social values their child
survival now I have money on that axis
and I have the possibility of children
to survive there in some countries 99.7
percent of children survived 25 years of
age others only 70 and here it seems
that this is a gap between OECD Latin
America East Europe East Asia Arab
states south asia and sub-saharan africa
the linearity is very
strong between child survival and money
but let me split sub-saharan Africa
health is there and better health is up
there I can go here and I can split
sub-saharan Africa into its countries
and when it bursts the size of each
country bubble it's the size of the
population Sierra Leone the down there
now reaches up there now reaches was the
first country to get away with trade
barriers and they could sell the sugar
they could sell their textiles on equal
terms as the people in Europe and North
America there's a huge difference
between Africa and Ghana's here in the
middle in Sierra Leone a humanitarian
aid here in uganda development aid here
time to invest there you can go for
holiday and it's a tremendous variation
within africa which we very often make
that it's equal everything i can split
south asia here india's the big bubble
in the middle but huge difference
between Afghanistan and Sri Lanka and I
can spit Arab states holiday same
climate same culture same religion huge
difference even between neighbors Yemen
civil war united arab emirate money
which was quite equally and well-used
not as the memphis and that includes all
the children of the foreign workers who
are in the country data is often better
than you think many people say data is
bad there is an uncertainty margin but
we can see the difference here cambodia
singapore the differences are much
bigger than the weakness of the data
east europe soviet economy for a long
time but they come out of the ten years
very very differently and there is Latin
America today we don't have to go to
Cuba to find a healthy country in Latin
America chili will have a lower child
mortality thank you but within some few
years from now and here we have high
income countries in OECD and we get the
whole pattern here of the world which is
more or less like like this and if we
look at it how it looks the world in
1960 it starts to move 1960 this is
matzo tomb he brought health to China
and then he died and then then shopping
came and brought money to China and
brought them into the mainstream again
and we have seen how countries move in
different directions like this so it's
sort of sort of difficult to get an
example country which shows the pattern
of the world but I would like to bring
you back to about here at 1960 and i
would like to compare south korea which
is this one with with brazil which is
this one the label went away from me
here and I would like to compare Uganda
which is there and I can run it forward
like this and you can see how South
Korea is making a very very fast
advancement whereas Brazil is much
slower and if we move back again here
and we put on trails on them like this
you can see again that the speed of
development is very very different and
the countries are moving more or less in
the same rate as money and health but it
seems you can move much faster if you're
healthy first than if you are wealthy
first and to show that you can put on
the way of united arab emirate they came
from here a mineral country they catch
all the oil they got all the money but
health cannot be bought at the
supermarket you have to invest in health
you have to get kids into schooling you
have to train health staff you have to
educate the population and sheikh zayed
did that in a fairly good way and in
spite of falling oil prices he brought
this country up here so we got much more
mainstream appearance of the world where
all countries tend to use their money
better than they used in the past now
this is more or less if you look at if
you look at the average data of the
countries they are like this now that's
dangerous to use average data because
there's such a lot of difference within
so if I go and look here we can see that
Uganda that today is where South Korea
was nineteen sixty if i split Uganda
there's quite a difference with in
Uganda these are the quintiles of Uganda
the richest twenty percent of your
gardens are there the poorest are down
there if i split south africa it's like
this and if i go down and look at
Nigeria where there was such a terrible
famine lost Lee it's like this the
twenty percent poorest of Nigeria is out
here and the twenty percent richest of
South Africa is there and yet we tend to
discuss on what solutions they should be
in Africa everything in this world
exists in Africa and you can't discuss
universal access to HIV for that
quintile appear with the same strategy
as down here the improvement of the
world must be highly contextualized and
it's not relevant to have it on regional
level we must be much more detailed we
find that students get very excited when
they can use this and even more
policymakers and the corporate sectors
would like to see see how the world is
changing now why doesn't this take place
why are we not using the data we have we
have data in the United Nation in the
National Statistical agencies and in
universities another non-governmental
organization because the data is hidden
down in the databases and the public is
there and the internet is there but we
have still not used it effectively all
that information was so changing in the
world does not include publicly funded
statistics there are some webpages like
this you know but they take some
nourishment down from the databases but
people put prices on them stupid
passwords and boring statistics and this
won't work
so what is needed we have the databases
it's not a new database you need we have
wonderful design tools and more and more
I added up here so we started a
nonprofit venture which we called
linking data to design we call it
Gapminder from london underground where
they warn you mind the gap so we thought
cap mind was appropriate and we started
to write software which could link the
data like this and it wasn't that
difficult it took some person years and
we are produced animations you can take
a data set and put it there we are
liberating you and data some fue UN
organizations some campus except that
their databases can go out on the world
but what we really need is of course a
search function a search function where
we can copy the data up to a searchable
format and get it out in the world and
what do we hear when we go around I've
done anthropology on the main
statistical units everyone says it's
impossible this can't be done our
information is so peculiar in detail so
that cannot be searched as other can be
searched we cannot give the data free to
the students free to the entrepreneurs
of the world but this is what we would
like to see isn't it the publicly-funded
data is down here and we would like
flowers to grow out on the net and one
of the crucial point is to make them
searchable and then people can use the
different design tool to animate it
there and I have a pretty good news for
you I have a good news that the present
new head of un statistic he doesn't say
it's impossible he only says we can't do
it and that's a quite clever guy
so we can see a lot happening in data in
the coming years we will be able to look
at income distributions in completely
new ways this is the income distribution
of China 1970 this is the income
distribution of the United States 1970
almost no overlap almost no overlap and
what has happened what has happened is
this the China is growing its not so
equal any longer and it's appearing here
overlooking the United States almost
like a ghost isn't it it's pretty scared
but I think it's very important to have
have all this information we need we
need really to see it and instead of
looking at this I would like to end up
by showing the Internet users per 1,000
and this software we access about 500
variables from all the countries quite
easily it takes some time to change for
this but on the accesses you can quite
easily get any variable you would like
to have and the thing would be to get up
the database is free to get them
searchable and with a second click to
get them into the graphic formats where
you can instantly understand them now
the statisticians doesn't like it
because they say that this will not this
will not show the the reality we have to
have statistical analytical methods but
this is hypothesis generating I n now
with a world where the internet are
coming the number of Internet users are
going up like this this is the GDP per
capita and it's a new technology coming
in but in amazingly how well it fits to
the economy of the countries that's why
the 100-dollar computer will be so
important but it's a nice tenders it's
as if the world is flattening off isn't
it these countries are lifting more than
the economy and will be very interesting
to fall of this over the year as I would
like you to be able to
with all the publicly funded data thank
you very much what if great ideas
weren't cherished what if they carried
no importance or held no value there is
a place where artistic vision is
protected where inspired design ideas
live on to become ultimate driving
machines
you
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