The best stats you've ever seen | Hans Rosling

Summary

The transcript details a lecture on the importance of understanding global development and the need for better data accessibility. The speaker, having spent years studying hunger in Africa, shares their experience teaching Swedish students about global health. They discuss the gap in knowledge among students and the general public about global issues, such as child mortality rates and income distribution. The lecture highlights the significant changes in Asia and the importance of context when discussing solutions for global problems. The speaker emphasizes the need for accessible, searchable public data to create visual representations that can help people understand complex global issues. They also mention the potential impact of technology, such as the $100 computer, in improving access to information and knowledge worldwide.

Takeaways

• 📚 The speaker, after 20 years of studying hunger in Africa, began teaching global development to Swedish students, highlighting the significant knowledge gap even among top students.
• 🧐 A pretest revealed that Swedish students knew less about global child mortality rates than would be expected by chance, indicating a need for better global health education.
• 🍌 The comparison of student knowledge to that of a chimpanzee choosing randomly emphasizes the extent of misinformation and preconceived notions about global development.
• 🌍 The use of software to visualize global data showed that the traditional 'West and the Rest' mindset is outdated, as developing countries have made significant progress in health and family planning.
• 📈 Life expectancy and family size have changed dramatically since 1962, with many countries moving towards smaller families and longer lives, reflecting improvements in global health and economic conditions.
• 💹 The world's income distribution has shifted, with a majority of the world's population now falling in the middle-income bracket, challenging the concept of 'developing countries'.
• 📊 By using visual data representation, it's clear that there's a strong correlation between child survival rates and economic wealth, although there are notable variations between regions.
• 🌐 The internet and technology are becoming more accessible globally, which correlates with economic growth, suggesting that technology can be a powerful tool for development.
• 🚀 The rapid development of countries like South Korea contrasted with others like Brazil shows that health improvements often precede economic growth and are crucial for sustainable development.
• 💼 There is a call to action for making publicly funded statistical data more accessible and searchable, which would allow for better understanding and utilization of this information by the public, policymakers, and businesses.
• 🌟 The founder's initiative, Gapminder, aims to liberate data and make it visually accessible, fostering a better understanding of global trends and empowering individuals to make informed decisions.

Q & A

What was the task the speaker took on ten years ago?

The speaker took on the task of teaching global development to Swedish undergraduate students, following 20 years of studying hunger in Africa with African institutions.

What was the initial concern the speaker had about the Swedish students?

The speaker was concerned that the Swedish students, having the highest grades in the Swedish college system, might already know everything he was planning to teach them about global health.

What did the speaker discover from the pretest results regarding the students' knowledge of child mortality rates?

The speaker discovered that the Swedish top students knew statistically significantly less about the world, specifically child mortality rates, than what would be expected, and even less than what a chimpanzee would guess by chance.

What problem did the speaker identify with the students' understanding of global development?

The speaker identified that the problem was not the students' ignorance, but their preconceived ideas and misconceptions about the world, particularly the outdated 'us and them' mentality that categorized countries into 'Western' and 'third world'.

How did the speaker use software to display global data on fertility rates and life expectancy?

The speaker used software to create visual representations where each bubble represented a country, with the size of the bubble indicating population, fertility rate on one axis, and life expectancy at birth on the other.

What significant change has occurred since 1962 according to the speaker's data?

Since 1962, there has been a convergence of countries towards smaller family sizes and longer life expectancies, with significant improvements in child survival and economic development, particularly in countries like China, Vietnam, and Bangladesh.

What is the current distribution of the world's income?

The world's income distribution is not a gap between the rich and the poor but rather a continuous spectrum with the richest 20% of the population earning about 74% of the total income, while the poorest 20% earn about 2%.

Why did the speaker establish the non-profit venture 'Gapminder'?

The speaker established Gapminder to link publicly funded data with design tools, making complex global data easily accessible, understandable, and searchable for a wider audience.

What is the main challenge the speaker sees with current publicly funded data?

The main challenge is that the data is not effectively used or made accessible to the public. It is often hidden in databases, not searchable, and not presented in a user-friendly format.

How does the speaker suggest we should visualize and interact with global data?

The speaker suggests that we should use design tools and software to animate and visualize data, making it searchable and easily understandable to allow for better public engagement and informed decision-making.

What does the speaker believe is the future of data accessibility and visualization?

The speaker is optimistic that in the coming years, we will be able to look at income distributions and other global data in completely new ways, with the help of better search functions and design tools that can handle large datasets.

Why is the speaker concerned about the lack of context in discussing global issues like HIV access in Africa?

The speaker is concerned because Africa, like many regions, has a wide range of economic and social conditions within it. A one-size-fits-all approach does not account for the diverse needs and situations across different countries and even within countries.

Outlines

00:00

😀 Teaching Global Development Insights

The speaker, with 20 years of experience studying hunger in Africa, shares their initial apprehension about teaching global health to top Swedish students. A pretest revealed that students knew less about global child mortality rates than expected, highlighting the need for better communication of global health data. The use of software visualizations to display global fertility rates and life expectancies over time illustrates the significant progress in global health, with notable improvements in countries like China and Vietnam. The speaker emphasizes the outdated concept of 'developing countries' and the importance of addressing preconceived notions.

05:01

🌍 Global Income Distribution and Social Change

This paragraph delves into the distribution of global income, challenging the perception of a clear divide between rich and poor. It presents the reality of a broad spectrum of income levels and the disproportionate share of global income held by the wealthiest. The speaker discusses the rapid social changes in Asia, particularly in Vietnam, before significant economic shifts. The paragraph also addresses the need to reevaluate the concept of 'developing countries,' given the large portion of the world's population that falls in the middle-income bracket. The use of visual data representation to compare income distributions and child survival rates between different countries and regions is emphasized as a tool for understanding global economic shifts.

10:01

📈 Variability and Development Speed Across Countries

The speaker highlights the variability within continents, such as Africa, and the importance of not generalizing the entire region as the same. There is a significant difference between countries in terms of development, health, and wealth. The paragraph contrasts the development paths of South Korea and Brazil, emphasizing the different speeds at which countries can advance economically and socially. The role of health as a precursor to wealth is discussed, with examples like the United Arab Emirates investing in health before wealth. The speaker calls for a more nuanced understanding of development that takes into account the specific contexts of individual countries and regions.

15:01

💡 The Importance of Accessible and Searchable Data

The speaker discusses the need for making global data accessible and searchable, criticizing the current state where much of this data is hidden away in databases. They share their efforts in creating Gapminder, a non-profit venture aimed at visualizing global data in an understandable format. The paragraph emphasizes the potential for public data to be used more effectively through better design and accessibility. The speaker expresses optimism for the future of data accessibility, suggesting that the new head of UN statistics is open to making data more available and searchable.

20:04

🌐 The Internet's Role in Global Development

In the final paragraph, the speaker reflects on the impact of the internet and new technologies on global development. They note the correlation between the number of internet users and GDP per capita, suggesting that internet access is a significant factor in economic growth. The paragraph ends with a call to action, encouraging the cherishing of great ideas and the protection of artistic vision, implying that innovation and creativity play a crucial role in driving progress and development.

Keywords

💡Global Development

Global development refers to the process of improving the quality of life and economic well-being of all nations, particularly those in the developing world. In the video, the speaker's experience in teaching global development to students is central to the narrative, emphasizing the importance of understanding global disparities and progress.

💡Child Mortality

Child mortality is the rate at which children die before reaching the age of five. It is a key indicator of a country's health and development. The video discusses the misconceptions students had about child mortality rates, highlighting the need for accurate data and education on global health issues.

💡Preconceived Ideas

Preconceived ideas are preexisting notions or beliefs that can influence one's understanding of new information. The video addresses the challenge of overcoming these ideas, particularly in the context of global health and development, to foster a more accurate and nuanced understanding of the world.

💡Fertility Rate

Fertility rate is the average number of children born per woman. It is a demographic measure that reflects societal trends and policy impacts. In the video, the speaker uses fertility rate as a metric to illustrate changes in societal norms and the impact of family planning initiatives across different countries.

💡Life Expectancy

Life expectancy is the average number of years a person is expected to live, often used to gauge the overall health and development level of a country. The video script discusses life expectancy in relation to economic and social changes, showing how improvements in health care and living conditions have increased life spans globally.

💡Economic Growth

Economic growth is the increase in the production of goods and services in an economy over a period of time. The video emphasizes the role of economic growth in improving living standards and the need to consider it alongside health and social indicators for a comprehensive understanding of a country's development.

💡Data Accessibility

Data accessibility refers to the ease with which data can be accessed and used by the public. The speaker in the video advocates for making publicly funded data more accessible and searchable, arguing that this would lead to better-informed decisions and a more engaged public on global issues.

💡Gapminder

Gapminder is a non-profit venture founded by the speaker to visualize global statistics. The organization aims to make complex global data more understandable through software that creates animations and visualizations. The video discusses the importance of Gapminder in bridging the gap between data and public understanding.

💡Income Distribution

Income distribution refers to the way income is divided among the members of society or different population groups. The video uses income distribution to illustrate the economic disparities and changes over time, particularly highlighting the shift from a world with a clear divide between rich and poor to one with a larger middle class.

💡Social Values

Social values are the principles and beliefs that guide the behavior and decision-making of individuals and societies. In the context of the video, the speaker discusses how social values, such as the importance of child survival, are closely linked to economic development and can be influenced by data-driven insights.

💡Contextualization

Contextualization is the process of understanding something within its relevant context or environment. The video emphasizes the need for contextualized solutions to global issues, as the speaker points out that there is significant variation within regions, such as Africa, and that one-size-fits-all approaches are not effective.

Highlights

The speaker taught global development to Swedish undergraduate students after 20 years of studying hunger in Africa.

A pretest revealed that Swedish students knew less about global health issues than expected, highlighting the need for better education.

The use of software to visualize global health and development data, showing the movement of countries over time in terms of fertility rates and life expectancy.

The realization that preconceived ideas, rather than ignorance, were the main challenge in understanding global development.

The comparison between the development trajectories of different countries, such as China, India, and Bangladesh, showing diverse paths to improvement.

The impact of the HIV epidemic on African countries' life expectancy, demonstrating the dynamic nature of global health challenges.

The economic transformation of Vietnam, moving from a focus on communist planning to a market economy, and its social implications.

The myth of a gap between rich and poor countries debunked, showing a more complex and overlapping global income distribution.

The importance of context in discussing solutions for global issues, as illustrated by the vast differences within African countries.

The need for better data accessibility and visualization to inform public understanding and policy-making on global development.

The creation of Gapminder, a non-profit venture aimed at linking data to design for better data visualization and public engagement.

The potential for searchable databases to revolutionize the way we access and understand public data, as advocated by the new head of UN statistics.

The demonstration of how internet usage correlates with GDP per capita, indicating the potential of technology to drive economic growth.

The call for more effective use of publicly funded data to generate hypotheses and inform global development strategies.

The importance of detailed, contextualized data to address the complexities and variations within countries, rather than relying on regional averages.

The speaker's vision for a future where data is freely accessible, searchable, and visually engaging to empower individuals and policymakers.

Transcripts

[Music]

but ten 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 institutions 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 a 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 you to test here but

it's Turkey which is high as there

Poland Russia Pakistan and South Africa

and these were the results of the

Swedish students I did that so I got the

confidence interval which was pretty

narrow and I got happy of course at one

point eight right answer out of five

possible that means that there was a

place for a professor of international

health and for my course but one life

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

Lanka and Turkey they would be right

half of the cases but the students are

not there the problem for me was not

ignorant it was preconceived ideas I did

also an unfair unethical study of the

professors 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 obviously 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 and 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 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 1 2 3

4 up to about eight children per woman

we have very good data since 1960 to

1968 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

1962 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 stopped

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 them against better

health they are improving there or the

green latin-american countries they are

moving towards smaller families your

yellow ones here or 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 pretty fast 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 Imams 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 world

moves up into the corner where we have

long lives and small family and we have

a completely new world

[Applause]

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 there 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 a 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 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 $1 $10

or $100 per day there's no gap between

rich and poor any longer this is a myth

there's a little hump here but there are

people all the way and if we look where

the income ends up the income this is

100 percent of world's annual income and

the rich is 20% they take out of that

about 74 percent and the poor is 20%

they take about 2% 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 24 percent of the

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

10% of world population most

impoverished this is oacd

the rich country the country club of the

UN and they are over here on this side

and quite an overlap between Africa and

oacd 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 seen that

wild populations 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 products

and I take the regions down here the

size of the bubble distill 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 and 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 ninety-nine point

seven percent of children survive to

five years of age others only seventy

and here it seems that this a gap

between oacd

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 help is up

there I can go here and I can split

sub-saharan Africa into its countries

and when it bursts the size of East

country bubble it's the size of the

population Sierra Leone the down there

more reaches up there

now reaches was the first country to get

away with trade barriers and they could

sell those 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 is

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 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 speed Arab states

how are they same climate same culture

same religion huge difference even

between neighbors Yemen Civil War United

Arab Emirates money which was quite

equally and well used not as the methods

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 merge 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

Chile 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 mouths a

tomb he brought health to China

and then he died and then thanks your

ping 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 for 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 a 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 countries so

if I go

look here we can see that Uganda that

today is where South Korea was 1960 if I

split Uganda there's quite a difference

within Uganda these are the quintiles of

Uganda the richest 20% of Uganda's 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 20% poorest of

Nigeria is out here and the 20% richest

of South Africa is there and yet we tend

to discuss on what solutions there

should be in Africa everything in this

world exists in Africa and you can't

discuss universal access to HIV for that

quintile up here 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

non-profit 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

gap 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 have

produced animations you can take a data

set and put it there we are liberating

you and data some few UN organizations

some countries accept 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 it's not so

equal any longer and it's appearing here

overlooking the United States almost

like a ghost isn't it it's pretty scary

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 1000

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 secondly 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 end 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 computer will be so important but

the 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 do 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