TED Residency
Jeff Kirschner: This app makes it fun to pick up litter
Džefs Kiršners: Ar šo lietotni ir prieks uzlasīt atkritumus
Filmed:
Readability: 4.2
1,385,758 views
Uzturēt tīru zemeslodi ir liels darbs. Ar "Litterati" - lietotni, kas identificē, savāc un ģeogrāfiski atzīmē pasaules atkritumus, TED rezidents Džefs Kiršners ir radījis kopienu, kas ar pūļpakalpojuma palīdzību attīra zemeslodi. Apsekojis atkritumus vairāk kā 100 valstīs, Kiršners cer izmantot savāktos datus, lai strādātu ar zīmoliem un organizācijām pie atkritumu apturēšanas, pirms tos nomet zemē.
Jeff Kirschner - Entrepreneur
Jeff Kirschner created a global community that's eradicating litter one piece at a time. Full bio
Jeff Kirschner created a global community that's eradicating litter one piece at a time. Full bio
Double-click the English transcript below to play the video.
00:13
This story starts with these two --
0
1015
2993
Stāsts sākas ar šiem abiem:
00:16
my kids.
1
4032
1258
maniem bērniem.
00:17
We were hiking in the Oakland woods
2
5314
1682
Mēs bijām pārgājienā pa Oklendas mežiem,
00:19
when my daughter noticed
a plastic tub of cat litter in a creek.
a plastic tub of cat litter in a creek.
3
7020
4134
kad mana meita strautā pamanīja
plastmasas toveri kaķu izkārnījumiem.
plastmasas toveri kaķu izkārnījumiem.
00:23
She looked at me and said,
4
11647
1662
Viņa palūkojās uz mani un teica:
00:25
"Daddy?
5
13333
2507
"Tēti?
00:27
That doesn't go there."
6
15864
1650
Tam te nav jābūt."
00:29
When she said that,
it reminded me of summer camp.
it reminded me of summer camp.
7
17538
2422
Viņas teiktais man atgādināja
vasaras nometni.
vasaras nometni.
00:31
On the morning of visiting day,
8
19984
1498
Apmeklējumu dienas rītā,
00:33
right before they'd let our anxious
parents come barreling through the gates,
parents come barreling through the gates,
9
21506
3663
tieši pirms vārtu atvēršanas
un trauksmaino vecāku iebrukšanas,
un trauksmaino vecāku iebrukšanas,
nometnes direktors teica:
00:37
our camp director would say,
10
25193
1369
"Aši! Katrs uzlasa pa pieciem
zemē nomestiem atkritumiem."
zemē nomestiem atkritumiem."
00:38
"Quick! Everyone pick up
five pieces of litter."
five pieces of litter."
11
26586
2309
00:40
You get a couple hundred kids
each picking up five pieces,
each picking up five pieces,
12
28919
3040
Pārsimt bērnu, katrs uzlasa
pa pieciem atkritumiem,
pa pieciem atkritumiem,
00:43
and pretty soon, you've got
a much cleaner camp.
a much cleaner camp.
13
31983
2573
un ātri vien nometne kļūst daudz tīrāka.
00:46
So I thought,
14
34580
1159
Tā nu es nodomāju,
kāpēc gan neizmantot pūļpakalpojuma
modeli, lai uzkoptu visu zemeslodi.
modeli, lai uzkoptu visu zemeslodi.
00:47
why not apply that crowdsourced
cleanup model to the entire planet?
cleanup model to the entire planet?
15
35763
4537
00:52
And that was the inspiration
for Litterati.
for Litterati.
16
40324
2951
Un tas bija Litterati iedvesmas avots.
00:55
The vision is to create
a litter-free world.
a litter-free world.
17
43299
3349
Vīzija ir radīt pasauli
bez zemē nomestiem atkritumiem.
bez zemē nomestiem atkritumiem.
00:58
Let me show you how it started.
18
46672
1508
Lūk, kā tas sākās.
01:00
I took a picture of a cigarette
using Instagram.
using Instagram.
19
48204
3386
Es ar Instagram palīdzību
uzņēmu izsmēķa attēlu.
uzņēmu izsmēķa attēlu.
01:04
Then I took another photo ...
20
52222
1867
Tad es uzņēmu vēl vienu attēlu...
01:06
and another photo ...
21
54113
1557
un vēl vienu...
01:07
and another photo.
22
55694
1167
un vēl vienu.
Un es ievēroju divas īpatnības:
01:08
And I noticed two things:
23
56885
1286
01:10
one, litter became artistic
and approachable;
and approachable;
24
58195
3472
pirmkārt, atkritumi kļuva
mākslinieciski un baudāmi;
mākslinieciski un baudāmi;
01:14
and two,
25
62244
1151
otrkārt, pēc dažām dienām
manā telefonā bija 50 attēlu,
manā telefonā bija 50 attēlu,
01:15
at the end of a few days,
I had 50 photos on my phone
I had 50 photos on my phone
26
63419
2515
un es biju savācis visus šos atkritumus
01:17
and I had picked up each piece,
27
65958
1587
un sapratu, ka fiksēju to,
kā es pozitīvi ietekmēju zemeslodi.
kā es pozitīvi ietekmēju zemeslodi.
01:19
and I realized that I was keeping a record
28
67569
2385
01:21
of the positive impact
I was having on the planet.
I was having on the planet.
29
69978
3151
01:25
That's 50 less things that you might see,
30
73153
2188
Tas ir par 50 lietām mazāk,
kas nekritīs acīs
kas nekritīs acīs
01:27
or you might step on,
31
75365
1243
vai nemētāsies pa kājām,
01:28
or some bird might eat.
32
76632
1458
vai ko neapēdīs kāds putns.
01:30
So I started telling people
what I was doing,
what I was doing,
33
78769
2652
Tā nu es sāku stāstīt cilvēkiem, ko daru,
01:33
and they started participating.
34
81445
2356
un viņi sāka līdzdarboties.
01:36
One day,
35
84831
1693
Kādu dienu
01:38
this photo showed up from China.
36
86548
2528
pārādījās šis foto no Ķīnas.
01:42
And that's when I realized
37
90039
1271
Un tad es sapratu,
ka Litterati ir kas vairāk
nekā glīti attēli.
nekā glīti attēli.
01:43
that Litterati was more
than just pretty pictures;
than just pretty pictures;
38
91334
3266
01:46
we were becoming a community
that was collecting data.
that was collecting data.
39
94624
3369
Mēs kļuvām par kopienu, kas vāc datus.
01:50
Each photo tells a story.
40
98869
1890
Katram attēlam ir stāsts.
01:53
It tells us who picked up what,
41
101279
2193
Tas stāsta, kurš atkritumu ir pacēlis,
01:55
a geotag tells us where
42
103496
2011
ģeobirka pastāsta – kur,
01:57
and a time stamp tells us when.
43
105531
2030
un laika zīmogs – kad.
02:00
So I built a Google map,
44
108006
2429
Es izveidoju Google karti
02:02
and started plotting the points
where pieces were being picked up.
where pieces were being picked up.
45
110459
4053
un sāku atzīmēt punktus,
kur atkritumi uzlasīti.
kur atkritumi uzlasīti.
02:06
And through that process,
the community grew
the community grew
46
114536
3918
Šajā procesā kopiena auga
02:10
and the data grew.
47
118478
1639
un datu apjoms arī.
02:12
My two kids go to school
right in that bullseye.
right in that bullseye.
48
120806
3461
Mani bērni iet uz skolu tieši šeit centrā.
02:17
Litter:
49
125125
1211
Atkritumi:
02:18
it's blending into
the background of our lives.
the background of our lives.
50
126360
2704
tie kļūst par mūsu dzīves fonu.
02:21
But what if we brought it
to the forefront?
to the forefront?
51
129088
2099
Bet ja nu mēs tos izvirzītu priekšplānā?
02:23
What if we understood exactly
what was on our streets,
what was on our streets,
52
131211
2912
Ja nu mēs precīzi saprastu,
kas mētājas uz mūsu ielām,
kas mētājas uz mūsu ielām,
02:26
our sidewalks
53
134147
1389
ietvēm
02:27
and our school yards?
54
135560
1538
un skolu pagalmos?
02:29
How might we use that data
to make a difference?
to make a difference?
55
137122
3247
Kā mēs šos datus varētu izmantot,
lai kaut ko uzlabotu?
lai kaut ko uzlabotu?
Tūlīt parādīšu.
02:33
Well, let me show you.
56
141189
1198
Sāksim ar pilsētām.
02:34
The first is with cities.
57
142411
1385
02:36
San Francisco wanted to understand
what percentage of litter was cigarettes.
what percentage of litter was cigarettes.
58
144418
4639
Sanfrancisko gribēja saprast, cik daudz
no nomestajiem atkritumiem ir izsmēķi.
no nomestajiem atkritumiem ir izsmēķi.
02:41
Why?
59
149081
1162
Kāpēc?
02:42
To create a tax.
60
150267
1209
Lai ieviestu nodokli.
02:44
So they put a couple of people
in the streets
in the streets
61
152073
2135
Viņi izsūtīja ielās pāris cilvēku
ar zīmuli un bloknotu,
ar zīmuli un bloknotu,
02:46
with pencils and clipboards,
62
154232
1361
lai tie staigātu apkārt
un savāktu informāciju,
un savāktu informāciju,
02:47
who walked around collecting information
63
155617
2063
02:49
which led to a 20-cent tax
on all cigarette sales.
on all cigarette sales.
64
157704
3111
kas noveda pie 20 centu nodokļa
visām pārdotajām cigaretēm.
visām pārdotajām cigaretēm.
02:53
And then they got sued
65
161787
2153
Un tad viņus iesūdzēja tiesā
02:55
by big tobacco,
66
163964
1176
lielie tabakas uzņēmumi,
02:57
who claimed that collecting information
with pencils and clipboards
with pencils and clipboards
67
165164
3216
kas apgalvoja, ka informācijas vākšana
ar zīmuli un bloknotu
ar zīmuli un bloknotu
03:00
is neither precise nor provable.
68
168404
2331
ir nedz precīza, nedz pierādāma.
03:03
The city called me and asked
if our technology could help.
if our technology could help.
69
171454
3680
Pilsētas dome piezvanīja man un jautāja,
vai mūsu tehnoloģija var palīdzēt.
vai mūsu tehnoloģija var palīdzēt.
03:07
I'm not sure they realized
70
175158
1249
Nezinu, vai viņi zināja,
ka mūsu tehnoloģija
bija mans Instagram konts.
bija mans Instagram konts.
03:08
that our technology
was my Instagram account --
was my Instagram account --
71
176431
2248
03:10
(Laughter)
72
178703
1039
(Smiekli)
03:11
But I said, "Yes, we can."
73
179766
1266
Bet es teicu: "Jā, mēs to varam."
03:13
(Laughter)
74
181056
1016
(Smiekli)
03:14
"And we can tell you
if that's a Parliament or a Pall Mall.
if that's a Parliament or a Pall Mall.
75
182096
3908
"Un mēs varam noteikt,
vai tas ir Parliament vai Pall Mall.
vai tas ir Parliament vai Pall Mall.
03:18
Plus, every photograph
is geotagged and time-stamped,
is geotagged and time-stamped,
76
186028
3425
Turkāt katram attēlam
ir ģeobirka un laika zīmogs,
ir ģeobirka un laika zīmogs,
03:21
providing you with proof."
77
189477
1381
kas sniedz pierādījumu."
03:23
Four days and 5,000 pieces later,
78
191839
3220
Pēc četrām dienām un 5000 izsmēķiem
šos datus izmantoja tiesā
šos datus izmantoja tiesā
03:27
our data was used in court
to not only defend but double the tax,
to not only defend but double the tax,
79
195083
4938
ne vien ieviestā nodokļa aizstāvēšanai,
bet arī tā dubultošanai,
bet arī tā dubultošanai,
03:32
generating an annual recurring revenue
of four million dollars
of four million dollars
80
200045
4323
radot ikgadējus nodokļu ieņēmumus
četru miljonu dolāru apmērā
četru miljonu dolāru apmērā
03:36
for San Francisco to clean itself up.
81
204392
2295
Sanfrancisko pilsētas satīrīšanai.
03:40
Now, during that process
I learned two things:
I learned two things:
82
208001
2235
Šajā procesā es ielāgoju divas lietas:
pirmkārt, Instagram nav piemērots rīks,
03:42
one, Instagram is not the right tool --
83
210260
2554
03:44
(Laughter)
84
212838
1031
(Smiekli)
03:45
so we built an app.
85
213893
1503
tāpēc mēs izveidojām lietotni.
03:47
And two, if you think about it,
86
215420
1633
Otrkārt, ja padomā,
katrai pasaules pilsētai
ir unikāls atkritumu profils,
ir unikāls atkritumu profils,
03:49
every city in the world
has a unique litter fingerprint,
has a unique litter fingerprint,
87
217077
3617
03:52
and that fingerprint provides
both the source of the problem
both the source of the problem
88
220718
3836
un šis profils piedāvā
gan problēmas cēloni,
gan problēmas cēloni,
03:56
and the path to the solution.
89
224578
1921
gan ceļu uz tās atrisinājumu.
03:59
If you could generate a revenue stream
90
227646
2378
Ja spējat radīt nodokļu ieņēmumus,
04:02
just by understanding
the percentage of cigarettes,
the percentage of cigarettes,
91
230048
2463
vien nosakot izsmēķu īpatsvaru,
04:04
well, what about coffee cups
92
232535
2096
kā būtu ar papīra glāzēm kafijai
04:06
or soda cans
93
234655
1706
vai limonādes bundžām,
04:08
or plastic bottles?
94
236385
1414
vai plastmasas pudelēm?
04:10
If you could fingerprint San Francisco,
well, how about Oakland
well, how about Oakland
95
238501
3201
Ja var izveidot Sanfrancisko profilu,
kā būtu ar Oklendu
kā būtu ar Oklendu
04:13
or Amsterdam
96
241726
1696
vai Amsterdamu,
04:15
or somewhere much closer to home?
97
243446
2970
vai kaut kur daudz tuvāk mājām?
Un kā ar zīmoliem?
04:19
And what about brands?
98
247408
1234
04:20
How might they use this data
99
248666
1901
Kā viņi varētu izmantot šos datus,
04:22
to align their environmental
and economic interests?
and economic interests?
100
250591
4212
lai līdzsvarotu savu ietekmi uz vidi
un ekonomiskās intereses?
un ekonomiskās intereses?
04:27
There's a block in downtown Oakland
that's covered in blight.
that's covered in blight.
101
255646
3212
Kāds Oklendas centra rajons
ir piemētāts ar atkritumiem.
ir piemētāts ar atkritumiem.
04:31
The Litterati community got together
and picked up 1,500 pieces.
and picked up 1,500 pieces.
102
259325
4104
Litterati kopiena sanāca kopā
un uzlasīja 1500 vienības.
un uzlasīja 1500 vienības.
04:35
And here's what we learned:
103
263812
1340
Un, lūk, ko mēs sapratām:
04:37
most of that litter came
from a very well-known taco brand.
from a very well-known taco brand.
104
265176
3210
vairums šo atkritumu
ir no kāda labi pazīstama tako zīmola.
ir no kāda labi pazīstama tako zīmola.
04:41
Most of that brand's litter
were their own hot sauce packets,
were their own hot sauce packets,
105
269738
3577
Vairums šī zīmola atkritumu
bija asās mērces paciņas,
bija asās mērces paciņas,
04:46
and most of those hot sauce packets
hadn't even been opened.
hadn't even been opened.
106
274438
3626
un vairums no tām pat nebija atvērtas.
04:51
The problem and the path
to the solution --
to the solution --
107
279965
2715
Problēma un ceļš uz tās risinājumu –
04:54
well, maybe that brand only
gives out hot sauce upon request
gives out hot sauce upon request
108
282704
3961
varbūt šim zīmolam vajadzētu izsniegt
aso mērci tikai pēc pieprasījuma
aso mērci tikai pēc pieprasījuma
04:58
or installs bulk dispensers
109
286689
2009
vai uzstādīt traukus
mērces paņemšanai pēc vēlēšanās,
mērces paņemšanai pēc vēlēšanās,
05:00
or comes up with more
sustainable packaging.
sustainable packaging.
110
288722
2552
vai ieviest videi draudzīgu iepakojumu.
05:03
How does a brand take
an environmental hazard,
an environmental hazard,
111
291298
2969
Kā lai zīmols vides apdraudējumu
05:06
turn it into an economic engine
112
294291
2006
pārvērš ekonomiskā dzinējspēkā
05:08
and become an industry hero?
113
296321
1768
un kļūst par nozares varoni?
05:11
If you really want to create change,
114
299292
2202
Ja tiešām vēlaties izmaiņas,
05:13
there's no better place to start
than with our kids.
than with our kids.
115
301518
2874
nav labāka sākumpunkta kā mūsu bērni.
05:16
A group of fifth graders picked up
1,247 pieces of litter
1,247 pieces of litter
116
304416
3403
Kāda piektklasnieku grupa
uzlasīja 1247 atkritumu vienības
uzlasīja 1247 atkritumu vienības
05:19
just on their school yard.
117
307843
1848
savā skolas pagalmā vien.
Un viņi saprata,
ka visizplatītākais atkritumu veids
ka visizplatītākais atkritumu veids
05:21
And they learned that the most
common type of litter
common type of litter
118
309715
2532
ir salmiņu plastmasas iepakojumi
no skolas ēdnīcas.
no skolas ēdnīcas.
05:24
were the plastic straw wrappers
from their own cafeteria.
from their own cafeteria.
119
312271
3234
05:27
So these kids went
to their principal and asked,
to their principal and asked,
120
315947
2529
Tad šie skolēni
aizgāja pie direktora un jautāja:
aizgāja pie direktora un jautāja:
05:30
"Why are we still buying straws?"
121
318500
1660
"Kāpēc mums jāpērk salmiņi?"
05:33
And they stopped.
122
321166
1755
Un viņi pārstāja iepirkt tos.
05:34
And they learned that individually
they could each make a difference,
they could each make a difference,
123
322945
3654
Viņi iemācījās,
ka katra individuālajai rīcībai ir nozīme,
ka katra individuālajai rīcībai ir nozīme,
05:38
but together they created an impact.
124
326623
2338
bet visi kopā viņi ietekmēja notiekošo.
05:41
It doesn't matter
if you're a student or a scientist,
if you're a student or a scientist,
125
329503
4012
Nav svarīgi,
vai esat students vai zinātnieks,
vai esat students vai zinātnieks,
05:45
whether you live in Honolulu or Hanoi,
126
333539
3135
vai dzīvojat Honolulū vai Hanojā,
05:48
this is a community for everyone.
127
336698
2441
šī kopiena der ikkatram.
05:51
It started because of two little kids
in the Northern California woods,
in the Northern California woods,
128
339974
4679
Tas sākās ar diviem bērneļiem
Ziemeļkalifornijas mežos
Ziemeļkalifornijas mežos
05:56
and today it's spread across the world.
129
344677
2814
un tagad ir izplatījies visā pasaulē.
05:59
And you know how we're getting there?
130
347938
1783
Un zināt, kā mēs pie tā nonācām?
06:02
One piece at a time.
131
350067
1878
Atkritumu pa atkritumam.
06:04
Thank you.
132
352508
1215
Paldies.
(Aplausi)
06:05
(Applause)
133
353747
3618
ABOUT THE SPEAKER
Jeff Kirschner - EntrepreneurJeff Kirschner created a global community that's eradicating litter one piece at a time.
Why you should listen
When his 4-year old daughter saw a plastic tub of cat litter in the woods, little did Jeff Kirschner realize that it would be the spark for creating Litterati -- a global movement that's "crowdsource-cleaning" the planet one piece of litter at a time.
Featured in National Geographic, Time Magazine, Fast Company and USA Today, Litterati has become a shining example of how communities are using technology and data to solve our world's most complex problems.
Kirschner has shared the Litterati story at Fortune 500 companies such as Google, Facebook and Uber, keynoted environmental summits at the Monterey Bay Aquarium and Keep America Beautiful, as well as leading schools including Stanford, MIT and the University of Michigan. He was recently a TED Resident, where he developed Litterati into an idea worth spreading.
Jeff Kirschner | Speaker | TED.com