TEDIndia 2009
Hans Rosling: Asia's rise -- how and when
Hanss Roslings: Āzijas izaugsme, kā un kad
Filmed:
Readability: 3.8
2,087,444 views
Hanss Roslings bija students, kas viesojās Indijā, kad viņš pirmo reizi atskārta, ka Āzijai bija visa nepieciešamā jauda, lai atgūtu savu vietu kā pasaules dominējošajai ekonomiskajai varai. TEDIndia konferencē viņš attēlo globālo ekonomisko izaugsmi kopš 1858. gada un prognozē precīzu datumu, kad Indija un Ķīna apsteigs ASV.
Hans Rosling - Global health expert; data visionary
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus. Full bio
In Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus. Full bio
Double-click the English transcript below to play the video.
00:17
Once upon a time,
0
2000
2000
Reiz sensenos laikos,
00:19
at the age of 24,
1
4000
2000
kad man bija 24 gadi,
00:21
I was a student at St. John's Medical College in Bangalore.
2
6000
5000
es biju students Sv. Džona medicīnas institūtā, Bengalūru.
00:26
I was a guest student during one month
3
11000
3000
Es bija viesstudents viena mēneša
00:29
of a public health course.
4
14000
2000
sabiedrības veselības kursa laikā.
00:31
And that changed my mindset forever.
5
16000
3000
Un tas uz mūžu mainīja manu dzīves priekšstatu.
00:34
The course was good, but it was not the course content
6
19000
3000
Kurss bija labs, taču ne tā saturs bija tas, kas
00:37
in itself that changed the mindset.
7
22000
2000
mainīja manu dzīves priekšstatu.
00:39
It was the brutal realization,
8
24000
2000
Tā bija nākamajā rītā piedzīvotā
00:41
the first morning,
9
26000
2000
skarbā atklāsme,
00:43
that the Indian students were better than me.
10
28000
3000
ka indiešu studenti bija par mani labāki.
00:46
(Laughter)
11
31000
1000
(Smiekli)
00:47
You see, I was a study nerd.
12
32000
2000
Saprotiet, es biju zubris.
00:49
I loved statistics from a young age.
13
34000
2000
Mani jau no bērnības aizrāva statistika.
00:51
And I studied very much in Sweden.
14
36000
2000
Studējot Zviedrijā, es ļoti daudz mācījos.
00:53
I used to be in the upper quarter of all courses I attended.
15
38000
4000
Visus apmeklētajos kursos es biju labāko starpā.
00:57
But in St. John's, I was in the lower quarter.
16
42000
4000
Bet Sv. Džona institūtā es biju viens no sliktākajiem.
01:01
And the fact was that Indian students
17
46000
2000
Lieta tāda, ka indiešu studenti
01:03
studied harder than we did in Sweden.
18
48000
3000
mācījās vairāk nekā mēs Zviedrijā.
01:06
They read the textbook twice,
19
51000
2000
Viņi mācību grāmatu izlasīja divreiz,
01:08
or three times or four times.
20
53000
2000
trīsreiz vai pat četrreiz.
01:10
In Sweden we read it once and then we went partying.
21
55000
3000
Mēs Zviedrijā to izlasījām vienreiz un tad devāmies ballēties.
01:13
(Laugher)
22
58000
2000
(Smiekli)
01:15
And that, to me,
23
60000
3000
Tā man,
01:18
that personal experience
24
63000
2000
šī personīgā pieredze
01:20
was the first time in my life
25
65000
3000
bija pirmā reize manā mūžā,
01:23
that the mindset I grew up with
26
68000
2000
kad priekšstats, ar ko uzaugu,
01:25
was changed.
27
70000
3000
mainījās.
01:28
And I realized that perhaps
28
73000
2000
Es sapratu, ka, iespējams,
01:30
the Western world will not continue
29
75000
2000
Rietumu pasaule mūžīgi
01:32
to dominate the world forever.
30
77000
3000
pasaulē nedominēs.
01:35
And I think many of you have the same sort of personal experience.
31
80000
4000
Man šķiet, ka daudziem no jums ir līdzīga veida personīgā pieredze.
01:39
It's that realization of someone you meet
32
84000
3000
Tā ir šī atskārsme, kas, satiekot kādu cilvēku,
01:42
that really made you change your ideas about the world.
33
87000
2000
patiesi liek jums mainīt savas domas par pasauli.
01:44
It's not the statistics, although I tried to make it funny.
34
89000
4000
Runa nav par statistiku, lai arī es to centos padarīt smieklīgu.
01:48
And I will now,
35
93000
4000
Un nu es
01:52
here, onstage,
36
97000
2000
šeit, uz skatuves,
01:54
try to predict when that will happen --
37
99000
3000
mēģināšu prognozēt, kad tas notiks,
01:57
that Asia will regain
38
102000
5000
ka Āzija atgūs
02:02
its dominant position
39
107000
2000
savu dominējošo pozīciju
02:04
as the leading part of the world,
40
109000
2000
kā vadošā pasaules daļa,
02:06
as it used to be, over thousands of years.
41
111000
4000
kā tas reiz bija tūkstošiem gadu.
02:10
And I will do that
42
115000
2000
To es paveikšu,
02:12
by trying to predict precisely
43
117000
3000
mēģinot precīzi prognozēt,
02:15
at what year
44
120000
2000
kurā gadā
02:17
the average income per person
45
122000
2000
Indijā un Ķīnā vidējie cilvēka
02:19
in India, in China, will reach that of the West.
46
124000
3000
ienākumi sasniegs Rietumu apmērus.
02:22
And I don't mean the whole economy,
47
127000
2000
Es nedomāju visu tautsaimniecību,
02:24
because to grow an economy
48
129000
2000
jo, lai palielinātu Indijas tautsaimniecību
02:26
of India to the size of U.K. --
49
131000
2000
līdz Apvienotās Karalistes apmēriem,
02:28
that's a piece of cake, with one billion people.
50
133000
3000
ar vienu miljardu cilvēku tas ir tīrais nieks.
02:31
But I want to see when will the average pay, the money
51
136000
4000
Bet es vēlos redzēt, kad vidējā alga, nauda
02:35
for each person, per month,
52
140000
2000
uz katru cilvēku mēnesī
02:37
in India and China,
53
142000
2000
Indijā un Ķīnā
02:39
when will that have reached that of U.K. and the United States?
54
144000
4000
sasniegs Apvienotās Karalistes un ASV apmērus?
02:43
But I will start with a historical background.
55
148000
3000
Bet vispirms es sākšu ar priekšvēsturi.
02:46
And you can see my map if I get it up here. You know?
56
151000
3000
Jūs redzat karti, kas tūlīt parādīsies.
02:49
I will start at 1858.
57
154000
3000
Es sākšu ar 1858. gadu.
02:52
1858 was a year of great technological
58
157000
4000
1858. gadā Rietumi piedzīvoja
02:56
advancement in the West.
59
161000
2000
lielu tehnoloģisko attīstību.
02:58
That was the year when Queen Victoria
60
163000
3000
Tas bija gads, kad Karaliene Viktorija
03:01
was able, for the first time, to communicate
61
166000
2000
varēja pirmoreiz sazināties
03:03
with President Buchanan,
62
168000
2000
ar prezidentu Bjūkenenu
03:05
through the Transatlantic Telegraphic Cable.
63
170000
3000
caur Transatlantijas telegrāfa kabeli.
03:08
And they were the first to "Twitter" transatlantically.
64
173000
3000
Viņi bija pirmie, kuri „tviteroja” pāri Atlantijas okeānam.
03:11
(Laughter)
65
176000
1000
(Smiekli)
03:12
(Applause)
66
177000
4000
(Aplausi)
03:16
And I've been able, through this wonderful Google and Internet,
67
181000
3000
Pateicoties brīnišķīgajam Google un Internetam, man ir izdevies
03:19
to find the text of the telegram
68
184000
2000
atrast telegrammas tekstu,
03:21
sent back from President Buchanan to Queen Victoria.
69
186000
4000
ko Karalienei Viktorijai atsūtīja prezidents Bjūkenens.
03:25
And it ends like this: "This telegraph
70
190000
3000
Tā beidzas šādi: „Šī telegramma
03:28
is a fantastic instrument to diffuse religion,
71
193000
2000
ir brīnišķīgs rīks, ar ko izplatīt ticību,
03:30
civilization, liberty and law throughout the world."
72
195000
4000
civilizāciju, brīvību un likumību visā pasaulē.”
03:34
Those are nice words. But I got sort of curious
73
199000
3000
Tie ir jauki vārdi. Bet es kļuvu ziņkārīgs par to,
03:37
of what he meant with liberty, and liberty for whom.
74
202000
4000
ko tieši viņš domāja ar brīvību, brīvību kam.
03:41
And we will think about that
75
206000
2000
Un mēs par to padomāsim,
03:43
when we look at the wider picture of the world in 1858.
76
208000
4000
skatoties uz 1858. gada pasaules kopainu.
03:47
Because 1858
77
212000
2000
Jo 1858. gads
03:49
was also watershed year
78
214000
3000
bija arī pagrieziena punkts
03:52
in the history of Asia.
79
217000
2000
Āzijas vēsturē.
03:54
1858 was the year
80
219000
2000
1858. gads bija gads,
03:56
when the courageous uprising
81
221000
2000
kad varonīgo sacelšanos
03:58
against the foreign occupation of India
82
223000
3000
pret Indijas svešzemju okupantiem
04:01
was defeated by the British forces.
83
226000
2000
sakāva britu spēki.
04:03
And India was up to 89 years more of foreign domination.
84
228000
5000
Un Indijā vēl 89 gadus valdīja svešzemnieki.
04:08
1858 in China
85
233000
2000
1858. gadā Ķīnā
04:10
was the victory in the Opium War by the British forces.
86
235000
4000
britu karaspēks svinēja uzvaru Opiju karos.
04:14
And that meant that foreigners, as it said in the treaty,
87
239000
3000
Tas nozīmēja, ka svešzemnieki, kā tas bija minēts līgumā,
04:17
were allowed to trade freely in China.
88
242000
2000
drīkstēja brīvi tirgoties Ķīnā.
04:19
It meant paying with opium for Chinese goods.
89
244000
4000
Tas nozīmēja maksāt par ķīniešu precēm ar opiju.
04:23
And 1858 in Japan
90
248000
2000
1858. gads Japānai
04:25
was the year when Japan had to sign the Harris Treaty
91
250000
3000
bija gads, kad tai bija jāparaksta Harisa līgums
04:28
and accept trade on favorable condition for the U.S.
92
253000
4000
un jāpieņem ASV labvēlīgi tirgošanās nosacījumi.
04:32
And they were threatened by those black ships there,
93
257000
4000
Viņus apdraudēja, lūk, šie melnie kuģi,
04:36
that had been in Tokyo harbor over the last year.
94
261000
2000
kas jau kopš iepriekšējā gada atradās Tokijas ostā.
04:38
But, Japan, in contrast to India and China,
95
263000
4000
Bet Japāna, atšķirībā no Indijas un Ķīnas,
04:42
maintained its national sovereignty.
96
267000
3000
saglabāja savu nacionālo suverenitāti.
04:45
And let's see how much difference that can make.
97
270000
3000
Tūlīt redzēsim, cik daudz tas maina.
04:48
And I will do that by bringing these bubbles
98
273000
3000
To mēs redzēsim, pārceļot atpakaļ šos burbuļus
04:51
back to a Gapminder graph here,
99
276000
2000
uz šo te Gapminder grafiku,
04:53
where you can see each bubble is a country.
100
278000
3000
kur, kā jau jūs redzat, katrs burbulis ir valsts.
04:56
The size of the bubble here is the population.
101
281000
3000
Burbuļa izmērs ir tās iedzīvotāju skaits.
04:59
On this axis, as I used to have income per person in comparable dollar.
102
284000
5000
Uz šīs ass, kā jau ierasts, ir ienākumi uz vienu cilvēku dolāros.
05:04
And on that axis I have life expectancy, the health of people.
103
289000
4000
Un uz šīs ass man ir dzīvildze, cilvēku veselība.
05:08
And I also bring an innovation here.
104
293000
2000
Es esmu arī līdzi paņēmis jaunievedumu.
05:10
I have transformed the laser beam
105
295000
3000
Es esmu pārvērtis lāzera rādītāju
05:13
into an ecological, recyclable version here, in green India.
106
298000
5000
par ekoloģisku, pārstrādājamu rādītāju šeit "zaļajā" Indijā.
05:18
(Applause)
107
303000
4000
(Aplausi)
05:22
And we will see, you know.
108
307000
3000
Un mēs redzēsim.
05:25
Look here, 1858, India was here,
109
310000
3000
Skat, 1858. gads, Indija bija šeit,
05:28
China was here, Japan was there,
110
313000
2000
Ķīna bija šeit, Japāna bija tur,
05:30
United States and United Kingdom
111
315000
2000
Savienotās Valstis un Apvienotā Karaliste
05:32
was richer over there.
112
317000
2000
bija bagātākas tur.
05:34
And I will start the world like this.
113
319000
3000
Sākšu pasauli no šīs vietas.
05:37
India was not always like this level.
114
322000
2000
Indijā vienmēr nebija tāds līmenis.
05:39
Actually if we go back into the historical record,
115
324000
2000
Īstenībā, ja mēs atgriežamies vēl senākā vēsturē,
05:41
there was a time hundreds of years ago
116
326000
2000
pirms vairākiem simtiem gadu bija laiks,
05:43
when the income per person in India and China
117
328000
2000
kad ienākumi uz vienu iedzīvotāju Indijā un Ķīnā
05:45
was even above that of Europe.
118
330000
2000
bija pat lielāki nekā Eiropā.
05:47
But 1850 had already been many, many years of foreign domination,
119
332000
4000
Bet 1850. gadā Indijā jau daudzus jo daudzus gadus bija pastāvējusi svešzemju pārvalde,
05:51
and India had been de-industrialized.
120
336000
3000
un tā bija krietni deindustrializēta.
05:54
And you can see that the countries who were growing
121
339000
2000
Jūs redzat, ka tās valstis, kuru tautsaimniecības
05:56
their economy was United States and United Kingdom.
122
341000
2000
attīstījās, bija Savienotās Valstis un Apvienotā Karaliste.
05:58
And they were also, by the end of the century, getting healthy,
123
343000
3000
Tajās gadsimta beigās arī sāka uzlaboties veselība,
06:01
and Japan was starting to catch up.
124
346000
2000
Japāna tās sāka panākt.
06:03
India was trying down here.
125
348000
2000
Indija mocījās šeit lejā.
06:05
Can you see how it starts to move there?
126
350000
2000
Vai redzat, kā tā sāk pārvietoties uz to pusi?
06:07
But really, really natural sovereignty was good for Japan.
127
352000
4000
Dabiskā suverenitāte patiešām Japānai nāca par labu.
06:11
And Japan is trying to move up there.
128
356000
2000
Japāna ķepurojās augšup.
06:13
And it's the new century now. Health is getting better,
129
358000
2000
Nu ir jauns gadsimts. Uzlabojas veselība,
06:15
United Kingdom, United States.
130
360000
2000
Apvienotā Karaliste, Savienotās Valstis.
06:17
But careful now -- we are approaching the First World War.
131
362000
3000
Nu gan uzmanīgi, mēs tuvojamies Pirmajam pasaules karam.
06:20
And the First World War, you know,
132
365000
2000
Pirmais pasaules karš, kā jau zināt,
06:22
we'll see a lot of deaths and economical problems here.
133
367000
4000
atnesīs daudz mirušo un ekonomiskās problēmas.
06:26
United Kingdom is going down.
134
371000
2000
Apvienotā Karaliste slīd lejā.
06:28
And now comes the Spanish flu also.
135
373000
2000
Un nu nāk arī spāņu gripa.
06:30
And then after the First World War, they continue up.
136
375000
3000
Tad pēc Pirmā pasaules kara tās turpina virzīties augšup.
06:33
Still under foreign domination, and without sovereignty,
137
378000
3000
Vēl joprojām ar svešzemju pārvaldi un bez suverenitātes
06:36
India and China are down in the corner.
138
381000
2000
Indija un Ķīna atrodas apakšējā stūrī.
06:38
Not much has happened.
139
383000
2000
Nekas daudz nav mainījies.
06:40
They have grown their population but not much more.
140
385000
2000
Tām ir pieaudzis iedzīvotāju skaits, nekas vairāk.
06:42
In the 1930's now, you can see
141
387000
2000
1930-ajos gados, kā jau redzat,
06:44
that Japan is going to a period of war,
142
389000
3000
Japāna piedzīvo kara periodu
06:47
with lower life expectancy.
143
392000
2000
ar zemāku dzīvildzi.
06:49
And the Second World War was really a terrible event,
144
394000
2000
Otrais pasaules karš bija patiesi briesmīgs notikums,
06:51
also economically for Japan.
145
396000
2000
Japānai arī ekonomiskā ziņā.
06:53
But they did recover quite fast afterwards.
146
398000
2000
Bet pēc tam tā samērā ātri atkopās.
06:55
And we are moving into the new world.
147
400000
2000
Un nu mēs virzāmies uz jauno pasauli.
06:57
In 1947 India finally
148
402000
3000
1947. gadā Indija beidzot
07:00
gained its independence.
149
405000
2000
ieguva savu neatkarību.
07:02
And they could raise the Indian flag and become a sovereign nation,
150
407000
4000
Un nu viņi varēja pacelt Indijas karogu un kļūt par suverēnu nāciju,
07:06
but in very big difficulties down there.
151
411000
3000
bet atrodoties lejā, ļoti smagā situācijā.
07:09
(Applause)
152
414000
3000
(Aplausi)
07:12
In 1949 we saw the emergence of the modern China
153
417000
4000
1949. gadā mēs redzējām, kā parādās mūsdienu Ķīna,
07:16
in a way which surprised the world.
154
421000
2000
veidā, kas pārsteidza pasauli.
07:18
And what happened?
155
423000
2000
Kas notika?
07:20
What happens in the after independence?
156
425000
2000
Kas notiek pēc neatkarības iegūšanas?
07:22
You can see that the health started to improve.
157
427000
2000
Jūs redzat, ka sāka uzlaboties veselība.
07:24
Children started to go to school.
158
429000
2000
Bērni sāka iet uz skolu,
07:26
Health services were provided.
159
431000
2000
tika nodrošināti veselības pakalpojumi.
07:28
This is the Great Leap Forward, when China fell down.
160
433000
4000
Lūk, Lielais lēciens, kad Ķīna nogāzās lejā.
07:32
It was central planning by Mao Tse Tung.
161
437000
2000
Par centrālo plānošanu bija atbildīgs Mao Dzeduns.
07:34
China recovered. Then they said,
162
439000
2000
Ķīna atkopās. Tad viņi teica:
07:36
"Nevermore, stupid central planning."
163
441000
2000
„Vairs nekad, stulbā centrālā plānošana.”
07:38
But they went up here, and India was trying to follow.
164
443000
3000
Tad viņi sāka virzīties augšup un Indija centās sekot.
07:41
And they were catching up indeed.
165
446000
2000
Un viņiem tas patiešām arī izdevās.
07:43
And both countries had the better health, but still
166
448000
2000
Abās valstīs bija labāka veselība, taču tāpat
07:45
a very low economy.
167
450000
2000
ļoti zema ekonomika.
07:47
And we came to 1978, and Mao Tse Tung died,
168
452000
3000
Mēs nonācām līdz 1978. gadam, kad nomira Mao Dzeduns
07:50
and a new guy turned up from the left.
169
455000
3000
un no kreisās puses parādījās jauns puisis.
07:53
And it was Deng Xiaoping coming out here.
170
458000
3000
Tas bija Dens Sjaopins.
07:56
And he said, "Doesn't matter
171
461000
2000
Un viņš teica: „Nav nozīmes tam,
07:58
if a cat is white or black,
172
463000
2000
vai kaķis ir melns vai balts,
08:00
as long as it catches mice."
173
465000
2000
galvenais, lai tas ķer peles.”
08:02
Because catching mice
174
467000
2000
Jo peļu ķeršana bija tas,
08:04
is what the two cats wanted to do.
175
469000
3000
ar ko abi kaķi vēlējās nodarboties.
08:07
And you can see the two cats being here,
176
472000
3000
Lūk, jūs redzat abus kaķus,
08:10
China and India, wanting to catch the mices over there, you know.
177
475000
3000
Ķīna un Indija, kas vēlējās noķert tur esošās peles.
08:13
And they decided to go not only for health and education,
178
478000
3000
Un viņi nolēma ne tikai tiekties pēc veselības un izglītības,
08:16
but also starting to grow their economy.
179
481000
2000
bet arī sākt attīstīt savu tautsaimniecību.
08:18
And the market reformer was successful there.
180
483000
2000
Un tirgus reformētājs guva panākumus.
08:20
In '92 India follows with a market reform.
181
485000
3000
1992. gadā Indija seko un arī veic tirgus reformu.
08:23
And they go quite closely together,
182
488000
2000
Tās virzās uz priekšu samērā cieši kopā,
08:25
and you can see that the similarity with India and China,
183
490000
2000
jūs redzat, ka Indijas un Ķīnas līdzība
08:27
in many ways, are greater than the differences with them.
184
492000
3000
daudzējādā ziņā ir lielāka nekā to atšķirības.
08:30
And here they march on. And will they catch up?
185
495000
2000
Tās turpina soļot uz priekšu. Vai tās mūs panāks?
08:32
This is the big question today.
186
497000
2000
Tas arī ir šīs dienas lielais jautājums.
08:34
There they are today.
187
499000
2000
Lūk, kur tās atrodas pašlaik.
08:36
Now what does it mean that the --
188
501000
2000
Tātad, tas nozīmē, ka
08:38
(Applause)
189
503000
3000
(Aplausi)
08:41
the averages there -- this is the average of China.
190
506000
3000
vidējie rādītāji, lūk, vidējais Ķīnā.
08:44
If I would split China, look here,
191
509000
2000
Paskat, ja es sadalu Ķīnu,
08:46
Shanghai has already catched up.
192
511000
3000
Šanhaja jau ir mūs panākusi.
08:49
Shanghai is already there.
193
514000
2000
Šanhaja jau ir tur.
08:51
And it's healthier than the United States.
194
516000
4000
Un tā ir veselīgāka nekā Savienotās Valstis.
08:55
But on the other hand, Guizhou, one of the poorest
195
520000
3000
Taču no otras puses, Guidžou, viena no nabadzīgākajām
08:58
inland provinces of China, is there.
196
523000
3000
Ķīnas iekšzemes provincēm ir šeit.
09:01
And if I split Guizhou into urban and rural,
197
526000
4000
Un, ja es sadalu Guidžou pilsētas un lauku daļās,
09:05
the rural part of Guizhou goes down there.
198
530000
3000
Guidžou lauku daļa ir, lūk, šeit lejā.
09:08
You see this enormous inequity in China,
199
533000
3000
Jūs redzat Ķīnā pastāvošo briesmīgo nevienlīdzību,
09:11
in the midst of fast economic growth.
200
536000
2000
tās straujās tautsaimniecības attīstības laikā.
09:13
And if I would also look at India,
201
538000
2000
Ja mēs paskatāmies uz Indiju,
09:15
you have another type of inequity, actually, in India.
202
540000
3000
mums ir vēl viens nevienlīdzības veids.
09:18
The geographical, macro-geographical difference is not so big.
203
543000
5000
Šī ģeogrāfiskā, makroģeogrāfiskā atšķirība nav nemaz tik liela.
09:23
Uttar Pradesh, the biggest of the states here,
204
548000
2000
Utarpradēša, lielākais no štatiem,
09:25
is poorer and has a lower health than the rest of India.
205
550000
3000
ir nabadzīgāks un ar sliktāku veselību, nekā pārējā Indija.
09:28
Kerala is flying on top there,
206
553000
3000
Kerala plivinās tur augšā,
09:31
matching United States in health,
207
556000
2000
un veselības ziņā ir līdzvērtīga ASV,
09:33
but not in economy.
208
558000
2000
bet ne ekonomikas.
09:35
And here, Maharashtra, with Mumbai,
209
560000
2000
Un, lūk, Mahārāštra ar Mumbaju
09:37
is forging forward.
210
562000
2000
laužas uz priekšu.
09:39
Now in India, the big inequities are within the state,
211
564000
3000
Indijas gadījumā, lielā nevienlīdzība ir štata iekšienē,
09:42
rather than between the states.
212
567000
2000
nevis starp tiem.
09:44
And that is not a bad thing, in itself.
213
569000
3000
Un tā pati par sevi nav slikta lieta.
09:47
If you have a lot inequity, macro-geographical inequities
214
572000
4000
Ja jums ir liela nevienlīdzība, makroģeogrāfisko nevienlīdzību
09:51
can be more difficult in the long term to deal with,
215
576000
3000
ilgtermiņā risināt ir daudz grūtāk,
09:54
than if it is in the same area where you have a growth center
216
579000
3000
nekā tad, ja viss notiek vienā apgabalā, kur izaugsmes centrs
09:57
relatively close to where poor people are living.
217
582000
3000
atrodas samērā tuvu nabadzīgo dzīves vietām.
10:00
No, there is one more inequity. Look there, United States.
218
585000
3000
Nē, ir vēl kāda nevienlīdzība. Rau, Savienotās Valstis.
10:03
(Laughter)
219
588000
1000
(Smiekli)
10:04
Oh, they broke my frame.
220
589000
2000
Ah, viņi salauza manu rāmi.
10:06
Washington, D.C. went out here.
221
591000
3000
Vašingtona izskrēja laukā.
10:09
My friends at Gapminder wanted me to show this
222
594000
3000
Mani Gapminder draugi gribēja, lai es jums to parādu,
10:12
because there is a new leader in Washington
223
597000
2000
jo Vašingtonā ir jauns vadītājs,
10:14
who is really concerned about the health system.
224
599000
2000
kuram patiesi rūp veselības sistēma.
10:16
And I can understand him, because Washington, D.C.
225
601000
3000
Un es viņu varu saprast, jo Vašingtona ir tik ļoti bagāta
10:19
is so rich over there
226
604000
3000
un atrodas šeit,
10:22
but they are not as healthy as Kerala.
227
607000
2000
taču tā nav tik veselīga kā Kerala.
10:24
It's quite interesting, isn't it?
228
609000
2000
Diezgan interesanti, vai ne?
10:26
(Applause)
229
611000
5000
(Aplausi)
10:31
I can see a business opportunity for Kerala,
230
616000
3000
Es Keralai saskata biznesa iespēju,
10:34
helping fix the health system in the United States.
231
619000
2000
palīdzot savest kārtībā veselības sistēmu ASV.
10:36
(Laughter)
232
621000
2000
(Smiekli)
10:38
(Applause)
233
623000
2000
(Aplausi)
10:40
Now here we have the whole world. You have the legend down there.
234
625000
3000
Lūk, mums ir visa pasaule. Apzīmējumi ir redzami zemāk.
10:43
And when you see the two giant cats here, pushing forward,
235
628000
4000
Skatoties uz diviem lielajiem kaķiem, kas spraucas uz priekšu,
10:47
you see that in between them
236
632000
2000
jūs redzat, ka starp tiem
10:49
and ahead of them,
237
634000
2000
un arī tiem priekšā
10:51
is the whole emerging economies of the world,
238
636000
2000
ir neskaitāmas pasaules jaunās ekonomikas,
10:53
which Thomas Friedman so correctly called the "flat world."
239
638000
4000
ko Tomass Frīdmans trāpīgi nodēvēja par „plakano pasauli.”
10:57
You can see that in health and education,
240
642000
2000
Jūs redzat, ka veselības un izglītības ziņā
10:59
a large part of the world population is putting forward,
241
644000
3000
liela daļa no pasaules iedzīvotājiem virzās uz priekšu,
11:02
but in Africa, and other parts,
242
647000
2000
bet Āfrikā un citās daļās,
11:04
as in rural Guizhou in China,
243
649000
2000
piemēram, Ķīnas lauku Guidžou
11:06
there is still people with low health and very low economy.
244
651000
3000
vēl joprojām ir cilvēki ar sliktu veselību un ļoti zemiem ienākumiem.
11:09
We have an enormous disparity in the world.
245
654000
2000
Mums pasaulē ir milzīga izkliede.
11:11
But most of the world in the middle are pushing forwards very fast.
246
656000
5000
Bet lielākā daļa no vidū esošās pasaules ļoti ātri virzās uz priekšu.
11:16
Now, back to my projections.
247
661000
2000
Atgriežoties pie manas prognozes.
11:18
When will it catch up? I have to go back to very conventional graph.
248
663000
5000
Kad tā mūs panāks? Man ir jāatgriežas pie ļoti klasiska grafika.
11:23
I will show income per person on this axis instead,
249
668000
3000
Šoreiz es atlikšu cilvēka ienākumus uz šīs ass,
11:26
poor down here, rich up there.
250
671000
2000
nabadzīgie lejā, bagātie augšā.
11:28
And then time here, from 1858
251
673000
2000
Un laiku šeit, no 1858. gada
11:30
I start the world.
252
675000
2000
es sākšu pasauli.
11:32
And we shall see what will happen with these countries.
253
677000
3000
Mēs redzēsim, kas notiks ar šīm valstīm.
11:35
You see, China under foreign domination
254
680000
3000
Redzat, Ķīna ar svešzemju pārvaldi
11:38
actually lowered their income and came down to the Indian level here.
255
683000
3000
pat samazināja savus ienākumus un nonāca lejā līdz Indijas līmenim.
11:41
Whereas U.K. and United States is getting richer and richer.
256
686000
4000
Kamēr Apvienotā Karaliste un Savienotās Valstis kļūst arvien bagātākas un bagātākas.
11:45
And after Second World War, United States is richer than U.K.
257
690000
3000
Un pēc Otrā pasaules kara, Savienotās Valstis ir bagātākas par Apvienoto Karalisti.
11:48
But independence is coming here.
258
693000
2000
Bet pienāk neatkarība.
11:50
Growth is starting, economic reform.
259
695000
2000
Sākas izaugsme un ekonomiskās reformas.
11:52
Growth is faster, and with projection from IMF
260
697000
3000
Izaugsme ir ātrāka, un ar SVF projekciju
11:55
you can see where you expect them to be in 2014.
261
700000
4000
jūs varat redzēt, kur pēc viņu prognozes valstis atradīsies 2014. gadā.
11:59
Now, the question is, "When will the catch up take place?"
262
704000
5000
Jautājums ir: „Kad notiks panākšana?”
12:04
Look at, look at the United States.
263
709000
2000
Skatieties, skatieties uz Savienotajām Valstīm.
12:06
Can you see the bubble?
264
711000
2000
Vai redzat burbuli?
12:08
The bubbles, not my bubbles,
265
713000
2000
Burbuļi, ne mani burbuļi,
12:10
but the financial bubbles.
266
715000
2000
bet finanšu burbuļu.
12:12
That's the dot com bubble. This is the Lehman Brothers doorstep there.
267
717000
5000
Lūk, dot com burbulis. Lūk, Lehman Brothers pie mūsu durvju sliekšņa.
12:17
You see it came down there.
268
722000
2000
Redzat, ka tas nokritās.
12:19
And it seems this is another rock coming down there, you know.
269
724000
5000
Izskatās, ka gaidāms vēl viens kritums.
12:24
So they doesn't seem to go this way, these countries.
270
729000
3000
Neizskatās, ka šīs valstis attīstītos tādā veidā.
12:27
They seem to go in a more humble growth way, you know.
271
732000
3000
Tās virzās uz priekšu pieticīgākā veidā.
12:30
And people interested in growth
272
735000
2000
Un cilvēki, kuriem interesē izaugsme,
12:32
are turning their eyes towards Asia.
273
737000
3000
sāk lūkoties Āzijas virzienā.
12:35
I can compare to Japan. This is Japan coming up.
274
740000
3000
Es varu salīdzināt ar Japānu. Lūk, Japāna, virzoties augšup.
12:38
You see, Japan did it like that.
275
743000
2000
Japāna to vienkārši ņēma un izdarīja.
12:40
We add Japan to it.
276
745000
2000
Mēs pievienojam Japānu.
12:42
And there is no doubt that fast catch up
277
747000
3000
Un nav šaubu, ka drīz vien notiks ātra
12:45
can take place.
278
750000
2000
panākšana.
12:47
Can you see here what Japan did?
279
752000
2000
Vai redzat, ko paveica Japāna?
12:49
Japan did it like this, until full catch up,
280
754000
2000
Japāna līdz panākšanai tā arī darīja
12:51
and then they follow with the other high-income economies.
281
756000
4000
un tad tā iet vienā līmenī ar citām augsto ienākumu ekonomikām.
12:55
But the real projections for those ones,
282
760000
3000
Taču to reālās prognozes
12:58
I would like to give it like this.
283
763000
5000
es gribētu veidot apmēram šādas.
13:03
Can be worse, can be better.
284
768000
2000
Varētu būt sliktāk, varētu labāk.
13:05
It's always difficult to predict, especially about the future.
285
770000
4000
Izteikt prognozes vienmēr ir grūti, it īpaši par nākotni.
13:09
Now, a historian tells me it's even more difficult to predict about the past.
286
774000
3000
Kāds vēsturnieks man apgalvo, ka grūtāk ir izteikt prognozes par pagātni.
13:12
(Laughter)
287
777000
2000
(Smiekli)
13:14
I think I'm in a difficult position here.
288
779000
3000
Šķiet, ka atrodos sarežģītā situācijā.
13:17
Inequalities in China and India
289
782000
2000
Ķīnas un Indijas nevienlīdzību
13:19
I consider really the big obstacle
290
784000
4000
es patiešām uzskatu par lielu šķērsli,
13:23
because to bring the entire population into growth and prosperity
291
788000
4000
jo, panākšana, ka visi iedzīvotāji dzīvo izaugsmē un pārticībā
13:27
is what will create a domestic market,
292
792000
2000
ir tas, kas radīs iekšējo tirgu,
13:29
what will avoid social instability,
293
794000
3000
kas novērsīs sociālo nestabilitāti,
13:32
and which will make use of the entire capacity
294
797000
3000
un dos iespēju, izmantot visu iedzīvotāju
13:35
of the population.
295
800000
2000
ražotspēju.
13:37
So, social investments in health, education and infrastructure,
296
802000
4000
Tāpēc sociālie ieguldījumi veselībā, izglītībā, infrastruktūrā
13:41
and electricity is really what is needed in India and China.
297
806000
6000
un elektrībā ir tas, kas nepieciešams Indijā un Ķīnā.
13:47
You know the climate. We have great international experts
298
812000
3000
Jūs zināt par klimatu. Mums Indijā ir lieliski starptautiskie eksperti,
13:50
within India telling us that the climate is changing,
299
815000
3000
kas apgalvo, ka klimats mainās
13:53
and actions has to be taken,
300
818000
2000
un ir jārīkojas,
13:55
otherwise China and India would be the countries
301
820000
3000
citādi Ķīna un Indija būs tās valstis,
13:58
most to suffer from climate change.
302
823000
2000
kas no klimata pārmaiņām cietīs visvairāk.
14:00
And I consider India and China the best partners in the world
303
825000
3000
Es uzskatu, ka Indija un Ķīna ir labākie partneri
14:03
in a good global climate policy.
304
828000
3000
labas globālās klimata politikas veidošanā.
14:06
But they ain't going to pay
305
831000
2000
Bet tās nemaksās
14:08
for what others, who have more money,
306
833000
2000
par to, ko pārējās valstis ar naudu
14:10
have largely created, and I can agree on that.
307
835000
3000
ir lielā mērā radījušas, un tam es varu piekrist.
14:13
But what I'm really worried about is war.
308
838000
3000
Bet tas, par ko es esmu uztraucies visvairāk, ir karš.
14:16
Will the former rich countries really accept
309
841000
2000
Vai bijušās bagātās valstis pieņems
14:18
a completely changed world economy,
310
843000
3000
pilnībā mainījušos pasaules ekonomiku
14:21
and a shift of power away from where it has been
311
846000
3000
un spēka samēra maiņu prom no tā pozīcijas
14:24
the last 50 to 100 to 150 years,
312
849000
2000
pēdējos 50, 100, 150 gadus
14:26
back to Asia?
313
851000
2000
un par labu Āzijai?
14:28
And will Asia be able to handle that
314
853000
2000
Un vai Āzija būs spējīga tikt galā
14:30
new position of being in charge
315
855000
2000
ar jauno vadošo pozīciju,
14:32
of being the most mighty, and the governors of the world?
316
857000
3000
esot visvarenākajai un pasaules pārvaldītājiem.
14:35
So, always avoid war,
317
860000
2000
Tātad, vienmēr izvairieties no kara,
14:37
because that always pushes human beings backward.
318
862000
3000
jo tas vienmēr kavē cilvēces attīstību.
14:40
Now if these inequalities, climate and war can be avoided,
319
865000
4000
Ja no šīm nevienlīdzībām, klimata un kariem var izvairīties,
14:44
get ready for a world in equity,
320
869000
3000
gatavojaties vienlīdzīgai pasaulei,
14:47
because this is what seems to be happening.
321
872000
3000
jo izskatās, ka tieši tas pašlaik notiek.
14:50
And that vision that I got as a young student,
322
875000
2000
Un šī vīzija, kas man 1972. gadā bijā kā jaunam studentam,
14:52
1972, that Indians can be much better than Swedes,
323
877000
6000
ka indiešiem varētu klāties daudz labāk kā zviedriem
14:58
is just about to happen.
324
883000
2000
kuru katru brīdi piepildīsies.
15:00
And it will happen precisely
325
885000
3000
Tas notiks tieši
15:03
the year 2048
326
888000
4000
2048. gadā,
15:07
in the later part of the summer, in July,
327
892000
3000
vasaras otrajā pusē, jūlijā,
15:10
more precisely, the 27th of July.
328
895000
3000
precīzāk 27. jūlijā.
15:13
(Applause)
329
898000
8000
(Aplausi)
15:21
The 27th of July, 2048
330
906000
4000
2048. gada 27. jūlijs
15:25
is my 100th birthday.
331
910000
2000
ir mana 100. dzimšanas diena.
15:27
(Laughter)
332
912000
2000
(Smiekli)
15:29
And I expect to speak
333
914000
2000
Man ir paredzēta uzstāšanās
15:31
in the first session of the 39th TED India.
334
916000
4000
39. TED India pirmajā sesijā.
15:35
Get your bookings in time. Thank you very much.
335
920000
3000
Reģistrējieties jau laikus. Liels paldies.
15:38
(Applause)
336
923000
7000
(Aplausi)
ABOUT THE SPEAKER
Hans Rosling - Global health expert; data visionaryIn Hans Rosling’s hands, data sings. Global trends in health and economics come to vivid life. And the big picture of global development—with some surprisingly good news—snaps into sharp focus.
Why you should listen
Even the most worldly and well-traveled among us have had their perspectives shifted by Hans Rosling. A professor of global health at Sweden's Karolinska Institute, his work focused on dispelling common myths about the so-called developing world, which (as he pointed out) is no longer worlds away from the West. In fact, most of the Third World is on the same trajectory toward health and prosperity, and many countries are moving twice as fast as the west did.
What set Rosling apart wasn't just his apt observations of broad social and economic trends, but the stunning way he presented them. Guaranteed: You've never seen data presented like this. A presentation that tracks global health and poverty trends should be, in a word: boring. But in Rosling's hands, data sings. Trends come to life. And the big picture — usually hazy at best — snaps into sharp focus.
Rosling's presentations were grounded in solid statistics (often drawn from United Nations and World Bank data), illustrated by the visualization software he developed. The animations transform development statistics into moving bubbles and flowing curves that make global trends clear, intuitive and even playful. During his legendary presentations, Rosling took this one step farther, narrating the animations with a sportscaster's flair.
Rosling developed the breakthrough software behind his visualizations through his nonprofit Gapminder, founded with his son and daughter-in-law. The free software — which can be loaded with any data — was purchased by Google in March 2007. (Rosling met the Google founders at TED.)
Rosling began his wide-ranging career as a physician, spending many years in rural Africa tracking a rare paralytic disease (which he named konzo) and discovering its cause: hunger and badly processed cassava. He co-founded Médecins sans Frontièrs (Doctors without Borders) Sweden, wrote a textbook on global health, and as a professor at the Karolinska Institut in Stockholm initiated key international research collaborations. He's also personally argued with many heads of state, including Fidel Castro.
Hans Rosling passed away in February 2017. He is greatly missed.
Hans Rosling | Speaker | TED.com