Erik Hersman: How texting helped Kenyans survive crisis

15,552 views ・ 2009-04-22

TED


Please double-click on the English subtitles below to play the video.

Prevodilac: Jelena Nedjic Lektor: Ilija Bilic
00:12
So I'm here to tell you a story of success from Africa.
0
12160
4000
Ovde sam da bih vam ispričao priču o uspehu u Africi.
00:16
A year and a half ago,
1
16160
3000
Pre godinu i po dana,
00:19
four of the five people who are full time members
2
19160
2000
četiri od pet članova
00:21
at Ushahidi,
3
21160
2000
Ushahidija,
00:23
which means "testimony" in Swahili,
4
23160
3000
što znači svedočantsvo na Svahili jeziku,
00:26
were TED Fellows.
5
26160
2000
su bili TED stipendisti.
00:28
A year ago in Kenya we had post-election violence.
6
28160
3000
Pre godinu dana u Keniji je došlo do nasilja nakon izbora.
00:31
And in that time we prototyped and built,
7
31160
3000
U tom periodu smo napravili prototip i izumeli
00:34
in about three days, a system that would allow
8
34160
2000
u roku od 3 dana sistem koji omogućava
00:36
anybody with a mobile phone
9
36160
2000
svakome ko ima mobilni telefon
00:38
to send in information and reports on what was happening around them.
10
38160
3000
da pošalje obaveštenje i izveštaj o tome šta se dešava u njegovoj okolini.
00:41
We took what we knew about Africa,
11
41160
2000
Iskoristili smo ono što znamo o Africi,
00:43
the default device,
12
43160
2000
i naš osnovni uređaj,
00:45
the mobile phone, as our common denominator,
13
45160
2000
mobilni telefon, kao imenilac naše radnje,
00:47
and went from there.
14
47160
2000
i odatle smo počeli.
00:49
We got reports like this.
15
49160
3000
Dobili smo izveštaje slične ovima.
00:56
This is just a couple of them from January 17th, last year.
16
56160
3000
Ovo je samo nekoliko primera od 17. januara prošle godine.
01:02
And our system was rudimentary. It was very basic.
17
62160
3000
Naš sistem je bio rudimentaran. Krajnje jednostavan.
01:05
It was a mash-up that used data that we collected from people,
18
65160
3000
To je bio remiks podataka do kojih smo došli od ljudi,
01:08
and we put it on our map.
19
68160
2000
i stavili smo ih na mapu.
01:10
But then we decided we needed to do something more.
20
70160
2000
Shvatili smo da treba da uradimo više od toga.
01:12
We needed to take what we had built
21
72160
2000
Bilo je neophodno da na osnovu onoga što smo napravili
01:14
and create a platform out of it so that it could be used elsewhere in the world.
22
74160
3000
stvorimo platformu koja bi omogućila upotrebu izuma ma gde u svetu.
01:17
And so there is a team of developers
23
77160
3000
Imamo tim koji se bavi usavršavanjem sistema
01:20
from all over Africa, who are part of this team now --
24
80160
3000
iz svih regiona Afrike, oni su deo ovog tima sada,
01:23
from Ghana, from Malawi, from Kenya.
25
83160
2000
od Gane preko Malavija do Kenije.
01:25
There is even some from the U.S.
26
85160
4000
Čak je poneko iz Sjedinjenih Država.
01:29
We're building for smartphones, so that it can be used in the developed world,
27
89160
3000
Radimo na pametnim telefonima, kako bi sistem mogao da se koristi i u razvijenim zemljama,
01:32
as well as the developing world.
28
92160
2000
i u zemljama u razvoju.
01:34
We are realizing that this is true.
29
94160
2000
Shvatamo da je ovo istina.
01:36
If it works in Africa then it will work anywhere.
30
96160
2000
Ako funkcioniše u Africi, radiće bilo gde.
01:38
And so we build for it in Africa first
31
98160
3000
To smo pre svega napravili za Afriku,
01:41
and then we move to the edges.
32
101160
2000
i odatle se širimo dalje.
01:43
It's now been deployed in the Democratic Republic of the Congo.
33
103160
3000
Uspostavljamo sada sistem u Demokratskoj Republici Kongo.
01:46
It's being used by NGOs all over East Africa,
34
106160
3000
Koriste ga NVO u celoj Istočnoj Africi,
01:49
small NGOs doing their own little projects.
35
109160
3000
male NVO koje se bave svojim malim projektima.
01:52
Just this last month it was deployed by
36
112160
2000
Upravo je ovog meseca Al-Džazira
01:54
Al Jazeera in Gaza.
37
114160
3000
uspostavila sistem u Gazi.
01:57
But that's actually not what I'm here to talk about.
38
117160
2000
Ali ne želim o tome da pričam danas.
01:59
I'm here to talk about the next big thing,
39
119160
2000
Hoću da pričam o narednom velikom fenomenu,
02:01
because what we're finding out is that
40
121160
2000
jer shvatamo da imamo mogućnost
02:03
we have this capacity to report
41
123160
2000
da iz prve ruke, od svedoka, saznamo
02:05
eyewitness accounts of what's going on in real time.
42
125160
4000
o svemu što se dešava u toku samog dešavanja.
02:09
We're seeing this in events like Mumbai recently,
43
129160
3000
Upravo to opažamo u događajima koji su se nedavno desili u Mumbaiu,
02:12
where it's so much easier to report now
44
132160
2000
da je mnogo lakše odmah izveštavati,
02:14
than it is to consume it.
45
134160
2000
nego koristiti obaveštenja.
02:16
There is so much information; what do you do?
46
136160
2000
Postoji toliko informacija, šta raditi sa njima?
02:18
This is the Twitter reports for over three days
47
138160
3000
Ovo su izveštaji sa Tviter mreže u toku tri dana
02:21
just covering Mumbai.
48
141160
2000
koji se odnose samo na Mumbaji.
02:23
How do you decide what is important?
49
143160
2000
Kako odlučiti šta je važno?
02:25
What is the veracity level of what you're looking at?
50
145160
3000
Koliko istine ima u tim izveštajima?
02:28
So what we find is that there is this
51
148160
2000
Zaključili smo da dolazi
02:30
great deal of wasted crisis information
52
150160
2000
do velikog gubitka informacija
02:32
because there is just too much information for us to
53
152160
3000
jer smo prosto pretrpani obaveštenjima
02:35
actually do anything with right now.
54
155160
3000
da bismo mogli da ih upotrebimo u datom trenutku.
02:38
And what we're actually really concerned with
55
158160
2000
Ono što nas zaista zabrinjava su
02:40
is this first three hours.
56
160160
2000
prva tri sata dešavanja.
02:42
What we are looking at is the first three hours.
57
162160
2000
Sada analiziramo prva tri sata nakon događaja
02:44
How do we deal with that information that is coming in?
58
164160
3000
Šta radite sa informacijama koje pristižu?
02:47
You can't understand what is actually happening.
59
167160
2000
Ne možete da razumete šta se zaista dešava.
02:49
On the ground and around the world
60
169160
2000
Ljudi na samom mestu dešavanja
02:51
people are still curious,
61
171160
2000
i širom sveta su radoznali,
02:53
and trying to figure out what is going on. But they don't know.
62
173160
3000
i žele da shvate šta se dešava, ali ne znaju.
02:56
So what we built of course, Ushahidi,
63
176160
3000
Tako da smo naravno napravili Ushahidi,
02:59
is crowdsourcing this information.
64
179160
2000
a to je zbirka svih informacija.
03:01
You see this with Twitter, too. You get this information overload.
65
181160
3000
To se dešava takođe i na Tviter mreži. Dosegnete zasićenje informacijama.
03:04
So you've got a lot of information. That's great.
66
184160
2000
Imate puno informacija. To je sjajno.
03:06
But now what?
67
186160
2000
I šta sad?
03:08
So we think that there is something interesting we can do here.
68
188160
3000
Smatramo da možemo da uradimo nešto veoma zanimljivo.
03:11
And we have a small team who is working on this.
69
191160
2000
Naš mali tim se bavi baš time.
03:13
We think that we can actually create
70
193160
2000
Smatramo da možemo da napravimo
03:15
a crowdsourced filter.
71
195160
2000
filter za sve te informacije.
03:17
Take the crowd and apply them to the information.
72
197160
3000
Pružite obaveštenje grupi ljudi.
03:20
And by rating it and by rating
73
200160
2000
Ocenjivanjem informacije
03:22
the different people who submit information,
74
202160
2000
i ocenjivanjem ljudi koji obaveštavaju,
03:24
we can get refined results
75
204160
2000
možemo doći do obrađenih
03:26
and weighted results.
76
206160
2000
i procenjenih rezultata.
03:28
So that we have a better understanding
77
208160
2000
Na taj način bolje sagledavamo
03:30
of the probability of something being true or not.
78
210160
2000
verovatnoću verodostojnosti informacije.
03:32
This is the kind of innovation that is,
79
212160
3000
Ovo je tip izuma i iskreno govoreći
03:35
quite frankly -- it's interesting that it's coming from Africa.
80
215160
2000
zanimljivo je da je potekao iz Afrike.
03:37
It's coming from places that you wouldn't expect.
81
217160
3000
Proistekla je iz regiona odakle ne očekujete da će se pojaviti.
03:40
From young, smart developers.
82
220160
2000
Izneli su je mladi, pametni izumitelji.
03:42
And it's a community around it that has decided to build this.
83
222160
3000
Zajednica oko njih je odlučila da stvori ovo.
03:45
So, thank you very much.
84
225160
2000
Pa, mnogo vam hvala.
03:47
And we are very happy to be part of the TED family.
85
227160
2000
Veoma smo srećni što smo deo TED familije.
03:49
(Applause)
86
229160
1000
(Aplauz)
About this website

This site will introduce you to YouTube videos that are useful for learning English. You will see English lessons taught by top-notch teachers from around the world. Double-click on the English subtitles displayed on each video page to play the video from there. The subtitles scroll in sync with the video playback. If you have any comments or requests, please contact us using this contact form.

https://forms.gle/WvT1wiN1qDtmnspy7