TEDGlobal 2013
Alessandro Acquisti: What will a future without secrets look like?
Alesandro Akvisti (Alessandro Acquisti): Kako će izgledati budućnost bez tajni?
Filmed:
Readability: 4.8
1,423,103 views
Granica između privatnog i javnog života u poslednjoj deceniji je nejasna - i u stvarnom životu i na internetu. Alesandro Akvisti je tu da nam objasni šta to znači i zbog čega je važno. U govoru koji je pomalo zastrašujući i tera na razmišljanje, prikazuje detalje jednog skorašnjeg i jednog istraživanja u toku, uključujući i projekat koji pokazuje koliko je lako povezati fotografiju nepoznate osobe sa njenim izuzetno osetljivim ličnim podacima.
Alessandro Acquisti - Privacy economist
What motivates you to share your personal information online? Alessandro Acquisti studies the behavioral economics of privacy (and information security) in social networks. Full bio
What motivates you to share your personal information online? Alessandro Acquisti studies the behavioral economics of privacy (and information security) in social networks. Full bio
Double-click the English transcript below to play the video.
00:12
I would like to tell you a story
0
641
2354
Želim da vam ispričam jednu priču
00:14
connecting the notorious privacy incident
1
2995
3176
koja povezuje čuveni incident
u vezi sa privatnošću,
u vezi sa privatnošću,
00:18
involving Adam and Eve,
2
6171
2769
koji uključuje Adama i Evu,
00:20
and the remarkable shift in the boundaries
3
8940
3446
sa neverovatnim promenama u granicama
00:24
between public and private which has occurred
4
12386
2686
između privatnog i javnog života
koje su se desile u poslednjih 10 godina.
00:27
in the past 10 years.
5
15072
1770
00:28
You know the incident.
6
16842
1298
Svi znate za taj incident.
00:30
Adam and Eve one day in the Garden of Eden
7
18140
3330
Adam i Eva, jednoga dana u Raju
00:33
realize they are naked.
8
21470
1843
shvate da su nagi.
00:35
They freak out.
9
23313
1500
Polude.
00:36
And the rest is history.
10
24813
2757
A ostatak priče pripada istoriji.
00:39
Nowadays, Adam and Eve
11
27570
2188
Danas bi Adam i Eva
00:41
would probably act differently.
12
29758
2361
verovatno drugačije reagovali.
00:44
[@Adam Last nite was a blast! loved dat apple LOL]
13
32119
2268
[@Adam Sinoć je bila ludnica!
jabuka je super LOL]
jabuka je super LOL]
00:46
[@Eve yep.. babe, know what happened to my pants tho?]
14
34387
1873
[@Eva Aha..
dušo, znaš li gde su mi pantalone?
dušo, znaš li gde su mi pantalone?
00:48
We do reveal so much more information
15
36260
2636
Mnogo više informacija o sebi
00:50
about ourselves online than ever before,
16
38896
3334
otkrivamo na internetu,
nego ikad ranije,
nego ikad ranije,
00:54
and so much information about us
17
42230
1704
i sve više i više informacija o nama
00:55
is being collected by organizations.
18
43934
2224
prikupljaju razne organizacije.
00:58
Now there is much to gain and benefit
19
46158
3282
Mnogo toga možemo da dobijemo
01:01
from this massive analysis of personal information,
20
49440
2446
od ove masivne analize ličnih podataka,
01:03
or big data,
21
51886
1946
ili "velikih podataka",
01:05
but there are also complex tradeoffs that come
22
53832
2638
ali odavanjem svoje privatnosti
01:08
from giving away our privacy.
23
56470
3098
stupamo u kompleksnu razmenu.
01:11
And my story is about these tradeoffs.
24
59568
4023
Priča koju vam pričam
je upravo o toj razmeni.
je upravo o toj razmeni.
01:15
We start with an observation which, in my mind,
25
63591
2584
Počinjemo sa opservacijom koja je,
po meni,
po meni,
01:18
has become clearer and clearer in the past few years,
26
66175
3327
postala sve jasnija u poslednjih
nekoliko godina,
nekoliko godina,
01:21
that any personal information
27
69502
2097
da bilo koja lična informacija
01:23
can become sensitive information.
28
71599
2285
lako može postati osetljiva informacija.
01:25
Back in the year 2000, about 100 billion photos
29
73884
4125
2000. godine je slikano
oko 100 milijardi fotografija
oko 100 milijardi fotografija
01:30
were shot worldwide,
30
78009
1912
širom sveta,
01:31
but only a minuscule proportion of them
31
79921
3065
ali je samo mali deo njih
01:34
were actually uploaded online.
32
82986
1883
postavljen na internet.
01:36
In 2010, only on Facebook, in a single month,
33
84869
3361
2010, samo na Fejsbuk
tokom jednog meseca
tokom jednog meseca
01:40
2.5 billion photos were uploaded,
34
88230
3270
postavljeno je 2,5 milijarde fotografija,
01:43
most of them identified.
35
91500
1882
a većina njih je bila sa identifikacijom.
01:45
In the same span of time,
36
93382
1880
U istom periodu,
01:47
computers' ability to recognize people in photos
37
95262
4870
mogućnost kompjutera
da prepoznaje ljude na slikama
da prepoznaje ljude na slikama
01:52
improved by three orders of magnitude.
38
100132
3608
se povećala tri puta.
01:55
What happens when you combine
39
103740
1882
Šta se dešava kad kombinujemo
01:57
these technologies together:
40
105622
1501
ove tehnologije:
01:59
increasing availability of facial data;
41
107123
2658
uvećanu dostupnost facijalnih podataka,
02:01
improving facial recognizing ability by computers;
42
109781
3648
povećanu sposobnost kompjutera
da prepoznaju lica,
da prepoznaju lica,
02:05
but also cloud computing,
43
113429
2182
ali i informacije u oblaku,
02:07
which gives anyone in this theater
44
115611
1888
što svakome u ovoj prostoriji
02:09
the kind of computational power
45
117499
1560
daje moć računara
02:11
which a few years ago was only the domain
46
119059
1886
koja je do pre nekoliko godina
bila svojstvena
bila svojstvena
02:12
of three-letter agencies;
47
120945
1782
samo agencijama
sa troslovnim akronimom;
sa troslovnim akronimom;
02:14
and ubiquitous computing,
48
122727
1378
i sveprisutno korišćenje računara,
02:16
which allows my phone, which is not a supercomputer,
49
124105
2892
koje dozvoljava mom telefonu,
koji nije superkompjuter,
koji nije superkompjuter,
02:18
to connect to the Internet
50
126997
1671
da se poveže na internet
02:20
and do there hundreds of thousands
51
128668
2334
i obavlja stotine hiljada
02:23
of face metrics in a few seconds?
52
131002
2639
prepoznavanja lica u nekoliko sekundi?
02:25
Well, we conjecture that the result
53
133641
2628
Pa, nagađamo da će rezultat
02:28
of this combination of technologies
54
136269
2064
ove kombinacije tehnologija
02:30
will be a radical change in our very notions
55
138333
2888
uneti radikalnu promenu
u našim shvatanjima
u našim shvatanjima
02:33
of privacy and anonymity.
56
141221
2257
privatnosti i anonimnosti.
02:35
To test that, we did an experiment
57
143478
1993
Da bismo to testirali,
sproveli smo eksperiment
sproveli smo eksperiment
02:37
on Carnegie Mellon University campus.
58
145471
2121
na kampusu Karnegi Melon univerziteta.
02:39
We asked students who were walking by
59
147592
2099
Zamolili smo studente u prolazu
02:41
to participate in a study,
60
149691
1779
da učestvuju u ispitivanju,
02:43
and we took a shot with a webcam,
61
151470
2562
fotografisali smo ih veb kamerom
02:46
and we asked them to fill out a survey on a laptop.
62
154032
2782
i zamolili ih da na laptopu
popune jedan upitnik.
popune jedan upitnik.
02:48
While they were filling out the survey,
63
156814
1979
Dok su to radili,
mi smo ubacili njihovu fotografiju
na računarsku mrežu u oblaku
na računarsku mrežu u oblaku
02:50
we uploaded their shot to a cloud-computing cluster,
64
158793
2797
02:53
and we started using a facial recognizer
65
161590
1727
i pokrenuli program prepoznavanja lica
02:55
to match that shot to a database
66
163317
2405
kako bismo povezali tu fotografiju
02:57
of some hundreds of thousands of images
67
165722
2393
sa bazom od stotina hiljada slika
03:00
which we had downloaded from Facebook profiles.
68
168115
3596
koje smo poskidali sa Fejsbuk profila.
03:03
By the time the subject reached the last page
69
171711
3259
Do trenutka kada je ispitanik
stigao do poslednje strane upitnika,
stigao do poslednje strane upitnika,
03:06
on the survey, the page had been dynamically updated
70
174970
3347
stranica je automatski ažurirana
03:10
with the 10 best matching photos
71
178317
2313
sa deset najpribližnijih fotografija
03:12
which the recognizer had found,
72
180630
2285
koje je program pronašao,
03:14
and we asked the subjects to indicate
73
182915
1738
i zamolili smo ispitanike da naznače
03:16
whether he or she found themselves in the photo.
74
184653
4120
ako su se prepoznali na fotografijama.
03:20
Do you see the subject?
75
188773
3699
Da li vidite ispitanika?
03:24
Well, the computer did, and in fact did so
76
192472
2845
Pa, računar je video,
03:27
for one out of three subjects.
77
195317
2149
u stvari uspeo je u jednom od tri slučaja.
03:29
So essentially, we can start from an anonymous face,
78
197466
3184
U osnovi, možemo početi od anonimnog lica,
03:32
offline or online, and we can use facial recognition
79
200650
3484
na internetu ili van njega,
i možemo koristiti prepoznavanje lica
i možemo koristiti prepoznavanje lica
03:36
to give a name to that anonymous face
80
204134
2360
da imenujemo to nepoznato lice
03:38
thanks to social media data.
81
206494
2108
zahvaljujući podacima
sa društvenih medija.
sa društvenih medija.
03:40
But a few years back, we did something else.
82
208602
1872
Ali nekoliko godina ranije,
uradili smo nešto drugo.
uradili smo nešto drugo.
03:42
We started from social media data,
83
210474
1823
Počeli smo od podataka
sa društvenih medija,
sa društvenih medija,
03:44
we combined it statistically with data
84
212297
3051
pomešali ih statistički sa podacima
03:47
from U.S. government social security,
85
215348
2102
iz socijalnog osiguranja vlade SAD-a,
03:49
and we ended up predicting social security numbers,
86
217450
3324
i na kraju smo predviđali
brojeve socijalnog osiguranja,
brojeve socijalnog osiguranja,
03:52
which in the United States
87
220774
1512
koji su u Sjedinjenim Državama
03:54
are extremely sensitive information.
88
222286
2040
izuzetno osetljiva informacija.
03:56
Do you see where I'm going with this?
89
224326
2093
Da li primećujete kuda idem s ovim?
03:58
So if you combine the two studies together,
90
226419
2922
Dakle, ako spojite ta dva istraživanja,
04:01
then the question becomes,
91
229341
1512
onda pitanje postaje,
04:02
can you start from a face and,
92
230853
2720
možete li početi od lica
04:05
using facial recognition, find a name
93
233573
2311
i koristeći prepoznavanje lica,
pronaći ime
pronaći ime
04:07
and publicly available information
94
235884
2669
i javno dostupne informacije
04:10
about that name and that person,
95
238553
1932
o tom imenu i toj osobi,
04:12
and from that publicly available information
96
240485
2248
i iz tih javno dostupnih informacija
04:14
infer non-publicly available information,
97
242733
2042
izvući one koje nisu javno dostupne,
04:16
much more sensitive ones
98
244775
1606
one mnogo osetljivije,
04:18
which you link back to the face?
99
246381
1492
koje možete povezati sa tim licem?
04:19
And the answer is, yes, we can, and we did.
100
247873
1916
Odgovor je da, možemo, i to smo i uradili.
04:21
Of course, the accuracy keeps getting worse.
101
249789
2568
Naravno, preciznost se smanjuje.
04:24
[27% of subjects' first 5 SSN digits identified (with 4 attempts)]
102
252357
944
[4 pokušaja; identifikovano prvih 5 cifara
broja SO kod 27% ispitanika]
broja SO kod 27% ispitanika]
04:25
But in fact, we even decided to develop an iPhone app
103
253301
3827
Ali odlučili smo i da razvijemo aplikaciju
04:29
which uses the phone's internal camera
104
257128
2715
koja koristi ugrađenu telefonsku kameru
04:31
to take a shot of a subject
105
259843
1600
da fotografiše ispitanika
04:33
and then upload it to a cloud
106
261443
1487
i potom ubaci sliku na oblak
04:34
and then do what I just described to you in real time:
107
262930
2662
i uradi u realnom vremenu
ono što sam vam opisao:
ono što sam vam opisao:
04:37
looking for a match, finding public information,
108
265592
2088
traži podudaranje,
nalazi javne informacije,
nalazi javne informacije,
04:39
trying to infer sensitive information,
109
267680
1730
pokušava da otkrije osetljive informacije,
04:41
and then sending back to the phone
110
269410
2591
i šalje sve nazad telefonu
04:44
so that it is overlaid on the face of the subject,
111
272001
3609
tako da se prikaže preko lica ispitanika,
04:47
an example of augmented reality,
112
275610
1901
kao proširena stvarnost,
04:49
probably a creepy example of augmented reality.
113
277511
2451
verovatno jezivi primer
proširene stvarnosti.
proširene stvarnosti.
04:51
In fact, we didn't develop the app to make it available,
114
279962
3339
Zapravo, nismo razvili aplikaciju
koja bi bila dostupna,
koja bi bila dostupna,
04:55
just as a proof of concept.
115
283301
1922
nego samo kao dokaz ideje.
04:57
In fact, take these technologies
116
285223
2313
U stvari, uzmite ove tehnologije
04:59
and push them to their logical extreme.
117
287536
1837
i gurnite ih
do njihovog logičnog ekstrema.
do njihovog logičnog ekstrema.
05:01
Imagine a future in which strangers around you
118
289373
2719
Zamislite budućnost
u kojoj će vas stranci u okolini
u kojoj će vas stranci u okolini
05:04
will look at you through their Google Glasses
119
292092
2311
gledati kroz Gugl naočare,
05:06
or, one day, their contact lenses,
120
294403
2307
ili jednog dana kroz kontaktna sočiva,
05:08
and use seven or eight data points about you
121
296710
4020
i koristiti sedam ili osam podataka o vama
05:12
to infer anything else
122
300730
2582
da pronađu bilo šta
05:15
which may be known about you.
123
303312
2603
što je možda o vama poznato.
05:17
What will this future without secrets look like?
124
305915
4794
Kako će izgledati ta budućnost bez tajni?
05:22
And should we care?
125
310709
1964
I da li bi trebalo da nas je briga?
05:24
We may like to believe
126
312673
1891
Možda nam se sviđa da verujemo
05:26
that the future with so much wealth of data
127
314564
3040
da će ta budućnost sa obiljem podataka
05:29
would be a future with no more biases,
128
317604
2514
biti nepolarizovana budućnost,
05:32
but in fact, having so much information
129
320118
3583
ali zapravo,
posedovanje toliko informacija
posedovanje toliko informacija
05:35
doesn't mean that we will make decisions
130
323701
2191
ne znači da ćemo donositi
objektivnije odluke.
objektivnije odluke.
05:37
which are more objective.
131
325892
1706
05:39
In another experiment, we presented to our subjects
132
327598
2560
U jednom drugom eksperimentu,
ispitanicima smo predstavili
ispitanicima smo predstavili
05:42
information about a potential job candidate.
133
330158
2246
informacije o potencijalnom
kandidatu za posao.
kandidatu za posao.
05:44
We included in this information some references
134
332404
3178
Tu smo uključili i neke
05:47
to some funny, absolutely legal,
135
335582
2646
zabavne, potpuno legalne,
05:50
but perhaps slightly embarrassing information
136
338228
2465
ali možda donekle
ponižavajuće informacije
ponižavajuće informacije
05:52
that the subject had posted online.
137
340693
2020
koje je subjekat postavio na internet.
05:54
Now interestingly, among our subjects,
138
342713
2366
Zanimljivo je da su neki ispitanici
05:57
some had posted comparable information,
139
345079
3083
postavili slične informacije,
06:00
and some had not.
140
348162
2362
a drugi nisu.
06:02
Which group do you think
141
350524
1949
Šta mislite, koja grupa
06:04
was more likely to judge harshly our subject?
142
352473
4552
je bila sklonija
da oštro prosuđuje o našem subjektu?
da oštro prosuđuje o našem subjektu?
06:09
Paradoxically, it was the group
143
357025
1957
Paradoksalno, ona grupa
06:10
who had posted similar information,
144
358982
1733
koja je postavila slične informacije,
06:12
an example of moral dissonance.
145
360715
2942
to je primer moralne disonance.
06:15
Now you may be thinking,
146
363657
1750
Možda mislite
06:17
this does not apply to me,
147
365407
1702
da se to ne odnosi na vas,
06:19
because I have nothing to hide.
148
367109
2162
jer nemate šta da krijete.
06:21
But in fact, privacy is not about
149
369271
2482
Ali u stvari, kod privatnosti
06:23
having something negative to hide.
150
371753
3676
se ne radi o tome
da krijete nešto negativno.
da krijete nešto negativno.
06:27
Imagine that you are the H.R. director
151
375429
2354
Zamislite da ste direktor
odeljenja za ljudske resurse
odeljenja za ljudske resurse
06:29
of a certain organization, and you receive résumés,
152
377783
2947
u nekoj organizaciji i primate biografije,
06:32
and you decide to find more information about the candidates.
153
380730
2473
i odlučite da pronađete
više informacija o kandidatima.
više informacija o kandidatima.
06:35
Therefore, you Google their names
154
383203
2460
Ukucate njihova imena u Gugl,
06:37
and in a certain universe,
155
385663
2240
i u nekom univerzumu,
06:39
you find this information.
156
387903
2008
pronađete ovu informaciju.
06:41
Or in a parallel universe, you find this information.
157
389911
4437
Ili u nekom paralelnom univerzumu,
pronađete ovu informaciju.
pronađete ovu informaciju.
06:46
Do you think that you would be equally likely
158
394348
2717
Da li mislite da biste podjednako
bili skloni
bili skloni
06:49
to call either candidate for an interview?
159
397065
2803
da pozovete jednog
od ova dva kandidata na razgovor?
od ova dva kandidata na razgovor?
06:51
If you think so, then you are not
160
399868
2282
Ako to mislite, onda se razlikujete
06:54
like the U.S. employers who are, in fact,
161
402150
2582
od poslodavaca u SAD-u,
koji su u stvari
koji su u stvari
06:56
part of our experiment, meaning we did exactly that.
162
404732
3307
deo našeg eksperimenta,
znači da smo upravo to uradili.
znači da smo upravo to uradili.
07:00
We created Facebook profiles, manipulating traits,
163
408039
3182
Napravili smo profile na Fejsbuku,
izmislili osobine,
izmislili osobine,
07:03
then we started sending out résumés to companies in the U.S.,
164
411221
2851
a potom smo počeli da šaljemo biografije
kompanijama u SAD,
kompanijama u SAD,
07:06
and we detected, we monitored,
165
414072
1908
i pratili smo
07:07
whether they were searching for our candidates,
166
415980
2393
da li proveravaju naše kandidate
07:10
and whether they were acting on the information
167
418373
1832
i da li reaguju na informacije
koje nalaze na društvenim medijima.
koje nalaze na društvenim medijima.
07:12
they found on social media. And they were.
168
420205
1938
I reagovali su.
07:14
Discrimination was happening through social media
169
422143
2101
Kroz društvene medije,
kandidati istih veština
kandidati istih veština
07:16
for equally skilled candidates.
170
424244
3073
bili su diskriminisani.
07:19
Now marketers like us to believe
171
427317
4575
Marketari bi želeli da verujemo
07:23
that all information about us will always
172
431892
2269
kako će sve informacije o nama
07:26
be used in a manner which is in our favor.
173
434161
3273
uvek biti korišćene u našu korist.
07:29
But think again. Why should that be always the case?
174
437434
3715
Razmislite još jednom.
Zašto bi to uvek bilo tako?
Zašto bi to uvek bilo tako?
07:33
In a movie which came out a few years ago,
175
441149
2664
U jednom filmu od pre nekoliko godina,
07:35
"Minority Report," a famous scene
176
443813
2553
"Suvišni izveštaj", u poznatoj sceni
07:38
had Tom Cruise walk in a mall
177
446366
2576
Tom Kruz ulazi u tržni centar
07:40
and holographic personalized advertising
178
448942
3776
i holografske personalizovane reklame
07:44
would appear around him.
179
452718
1835
se pojavljuju oko njega.
07:46
Now, that movie is set in 2054,
180
454553
3227
Radnja tog filma smeštena je u 2054,
07:49
about 40 years from now,
181
457780
1642
oko 40 godina od danas,
07:51
and as exciting as that technology looks,
182
459422
2908
i koliko god ta tehnologija
uzbudljivo izgledala,
uzbudljivo izgledala,
07:54
it already vastly underestimates
183
462330
2646
ona već izuzetno potcenjuje
07:56
the amount of information that organizations
184
464976
2140
količinu informacija koje organizacije
07:59
can gather about you, and how they can use it
185
467116
2483
mogu da skupe o vama,
i kako mogu da ih koriste
i kako mogu da ih koriste
08:01
to influence you in a way that you will not even detect.
186
469599
3398
da utiču na vas na načine
koje nećete ni primetiti.
koje nećete ni primetiti.
08:04
So as an example, this is another experiment
187
472997
2103
Kao ilustracija,
ovo je još jedan eksperiment
ovo je još jedan eksperiment
08:07
actually we are running, not yet completed.
188
475100
2273
koji sprovodimo, koji nije još završen.
08:09
Imagine that an organization has access
189
477373
2319
Zamislite da neka organizacija ima pristup
08:11
to your list of Facebook friends,
190
479692
2056
listi vaših Fejsbuk prijatelja,
08:13
and through some kind of algorithm
191
481748
1772
i preko nekakvog algoritma
08:15
they can detect the two friends that you like the most.
192
483520
3734
može da otkrije
vaša dva najdraža prijatelja.
vaša dva najdraža prijatelja.
08:19
And then they create, in real time,
193
487254
2280
I potom u realnom vremenu kreira
08:21
a facial composite of these two friends.
194
489534
2842
lice od sklopa lica ta dva prijatelja.
08:24
Now studies prior to ours have shown that people
195
492376
3069
E sad, studije pre naše su dokazale
08:27
don't recognize any longer even themselves
196
495445
2885
da u takvim sklopovima
ljudi više ne prepoznaju ni sebe,
08:30
in facial composites, but they react
197
498330
2462
ali reaguju pozitivno na njih.
08:32
to those composites in a positive manner.
198
500792
2117
08:34
So next time you are looking for a certain product,
199
502909
3415
Sledeći put kad budete tražili
neki proizvod,
neki proizvod,
08:38
and there is an ad suggesting you to buy it,
200
506324
2559
i pojavi se oglas
koji vam sugeriše da ga kupite,
koji vam sugeriše da ga kupite,
08:40
it will not be just a standard spokesperson.
201
508883
2907
to neće biti neki standardni prodavac.
08:43
It will be one of your friends,
202
511790
2313
Biće to jedan od vaših prijatelja,
08:46
and you will not even know that this is happening.
203
514103
3303
a vi nećete ni znati da se to dešava.
08:49
Now the problem is that
204
517406
2413
Problem je u tome
08:51
the current policy mechanisms we have
205
519819
2519
što trenutni mehanizmi zaštite
08:54
to protect ourselves from the abuses of personal information
206
522338
3438
protiv zloupotrebe ličnih informacija
08:57
are like bringing a knife to a gunfight.
207
525776
2984
liče na srljanje grlom u jagode.
09:00
One of these mechanisms is transparency,
208
528760
2913
Jedan od tih mehanizama
je transparentnost,
je transparentnost,
09:03
telling people what you are going to do with their data.
209
531673
3200
obaveštavanje ljudi o tome
šta ćete uraditi s njihovim podacima.
šta ćete uraditi s njihovim podacima.
09:06
And in principle, that's a very good thing.
210
534873
2106
U osnovi je to veoma dobra stvar.
09:08
It's necessary, but it is not sufficient.
211
536979
3667
Neophodna je, ali nije dovoljna.
09:12
Transparency can be misdirected.
212
540646
3698
Transparentnost može biti
pogrešno usmerena.
pogrešno usmerena.
09:16
You can tell people what you are going to do,
213
544344
2104
Možete reći ljudima šta ćete uraditi,
09:18
and then you still nudge them to disclose
214
546448
2232
i onda ih ipak navesti da otkriju
09:20
arbitrary amounts of personal information.
215
548680
2623
proizvoljne količine ličnih informacija.
09:23
So in yet another experiment, this one with students,
216
551303
2886
U još jednom eksperimentu,
ovaj put sa studentima,
ovaj put sa studentima,
09:26
we asked them to provide information
217
554189
3058
tražili smo da daju informacije
09:29
about their campus behavior,
218
557247
1813
o svom ponašanju na kampusu,
09:31
including pretty sensitive questions, such as this one.
219
559060
2940
uključujući i dosta osetljiva pitanja,
poput ovog:
poput ovog:
[Da li ste ikad varali na ispitu?]
09:34
[Have you ever cheated in an exam?]
220
562000
621
09:34
Now to one group of subjects, we told them,
221
562621
2300
Jednoj grupi studenata smo rekli:
09:36
"Only other students will see your answers."
222
564921
2841
"Vaše odgovore će videti
samo drugi studenti".
samo drugi studenti".
09:39
To another group of subjects, we told them,
223
567762
1579
Drugoj grupi studenata smo rekli:
09:41
"Students and faculty will see your answers."
224
569341
3561
"Vaše odgovore će videti
studenti i nastavno osoblje".
studenti i nastavno osoblje".
09:44
Transparency. Notification. And sure enough, this worked,
225
572902
2591
Transparentnost. Obaveštenje.
I ovo je upalilo,
I ovo je upalilo,
09:47
in the sense that the first group of subjects
226
575493
1407
u smislu da je prva grupa studenata
09:48
were much more likely to disclose than the second.
227
576900
2568
bila spremnija da odgovori od druge.
09:51
It makes sense, right?
228
579468
1520
Ima smisla, zar ne?
09:52
But then we added the misdirection.
229
580988
1490
Ali onda amo dodali
obmanjujuće uputstvo.
obmanjujuće uputstvo.
09:54
We repeated the experiment with the same two groups,
230
582478
2760
Ponovili smo eksperiment
sa iste dve grupe,
sa iste dve grupe,
09:57
this time adding a delay
231
585238
2427
ovog puta dodajući vreme
09:59
between the time we told subjects
232
587665
2935
između trenutka kad ih obaveštavamo
10:02
how we would use their data
233
590600
2080
na koji način ćemo koristiti
njihove podatke
njihove podatke
10:04
and the time we actually started answering the questions.
234
592680
4388
i trenutka kad počinjemo
da odgovaramo na pitanja.
da odgovaramo na pitanja.
10:09
How long a delay do you think we had to add
235
597068
2561
Šta mislite, koliko vremena
smo morali da dodamo
smo morali da dodamo
10:11
in order to nullify the inhibitory effect
236
599629
4613
da bismo poništili inhibitorni efekat
10:16
of knowing that faculty would see your answers?
237
604242
3411
saznanja da će nastavno osoblje
videti vaše odgovore?
videti vaše odgovore?
10:19
Ten minutes?
238
607653
1780
Deset minuta?
10:21
Five minutes?
239
609433
1791
Pet minuta?
10:23
One minute?
240
611224
1776
Minut?
10:25
How about 15 seconds?
241
613000
2049
Kako zvuči 15 sekundi?
10:27
Fifteen seconds were sufficient to have the two groups
242
615049
2668
15 sekundi je bilo dovoljno da obe grupe
10:29
disclose the same amount of information,
243
617717
1568
otkriju istu količinu informacija,
10:31
as if the second group now no longer cares
244
619285
2746
kao da drugoj grupi više nije važno
10:34
for faculty reading their answers.
245
622031
2656
što će nastavno osoblje
čitati njihove odgovore.
čitati njihove odgovore.
10:36
Now I have to admit that this talk so far
246
624687
3336
Moram da priznam
da ovaj govor do sada
zvuči izuzetno mračno,
zvuči izuzetno mračno,
10:40
may sound exceedingly gloomy,
247
628023
2480
10:42
but that is not my point.
248
630503
1721
ali to mi nije cilj.
10:44
In fact, I want to share with you the fact that
249
632224
2699
Zapravo, želim sa vama
da podelim činjenicu
da podelim činjenicu
10:46
there are alternatives.
250
634923
1772
da postoje alternative.
10:48
The way we are doing things now is not the only way
251
636695
2499
Način na koji sada radimo
10:51
they can done, and certainly not the best way
252
639194
3037
nije jedini i sigurno nije najbolji.
10:54
they can be done.
253
642231
2027
10:56
When someone tells you, "People don't care about privacy,"
254
644258
4171
Kada vam neko kaže
da ljudima nije stalo do privatnosti,
da ljudima nije stalo do privatnosti,
11:00
consider whether the game has been designed
255
648429
2642
razmislite o tome da je igra osmišljena
11:03
and rigged so that they cannot care about privacy,
256
651071
2724
i napravljena tako
da ne mogu da brinu o privatnosti,
da ne mogu da brinu o privatnosti,
11:05
and coming to the realization that these manipulations occur
257
653795
3262
i shvatanje da se ovakve manipulacije
dešavaju,
dešavaju,
11:09
is already halfway through the process
258
657057
1607
je već polovina pređenog puta
11:10
of being able to protect yourself.
259
658664
2258
u procesu da se zaštitite.
11:12
When someone tells you that privacy is incompatible
260
660922
3710
Kada vam neko kaže da se privatnost
ne slaže sa koristima "velikih podataka",
11:16
with the benefits of big data,
261
664632
1849
11:18
consider that in the last 20 years,
262
666481
2473
uzmite u obzir da su
u poslednjih 20 godina
u poslednjih 20 godina
11:20
researchers have created technologies
263
668954
1917
istraživači stvorili tehnologije
11:22
to allow virtually any electronic transactions
264
670871
3318
koje dozvoljavaju da se skoro svaka
elektronska transakcija izvrši
elektronska transakcija izvrši
11:26
to take place in a more privacy-preserving manner.
265
674189
3749
na način koji omogućava
bolje čuvanje privatnosti.
bolje čuvanje privatnosti.
11:29
We can browse the Internet anonymously.
266
677938
2555
Možemo anonimno da pretražujemo internet.
11:32
We can send emails that can only be read
267
680493
2678
Možemo da šaljemo imejlove
koje može da pročita
koje može da pročita
11:35
by the intended recipient, not even the NSA.
268
683171
3709
samo primalac, ali ne i NSA.
11:38
We can have even privacy-preserving data mining.
269
686880
2997
Možemo čak i da prikupljamo podatke
uz očuvanje privatnosti.
uz očuvanje privatnosti.
11:41
In other words, we can have the benefits of big data
270
689877
3894
Drugim rečima, možemo imati koristi
od "velikih podataka"
od "velikih podataka"
11:45
while protecting privacy.
271
693771
2132
uz očuvanje privatnosti.
11:47
Of course, these technologies imply a shifting
272
695903
3791
Naravno, ove tehnologije
nagoveštavaju promenu troškova i zarade
11:51
of cost and revenues
273
699694
1546
11:53
between data holders and data subjects,
274
701240
2107
između onih koji imaju
i onih koji traže podatke,
i onih koji traže podatke,
11:55
which is why, perhaps, you don't hear more about them.
275
703347
3453
što je verovatno razlog
zašto ne znate više o njima.
zašto ne znate više o njima.
11:58
Which brings me back to the Garden of Eden.
276
706800
3706
I to me vraća rajskom vrtu.
12:02
There is a second privacy interpretation
277
710506
2780
Postoji i druga interpretacija privatnosti
12:05
of the story of the Garden of Eden
278
713286
1809
u priči o rajskom vrtu,
12:07
which doesn't have to do with the issue
279
715095
2096
koja ne mora biti u vezi sa činjenicom
12:09
of Adam and Eve feeling naked
280
717191
2225
da se Adam i Eva osećaju
golo i posramljeno.
golo i posramljeno.
12:11
and feeling ashamed.
281
719416
2381
12:13
You can find echoes of this interpretation
282
721797
2781
Odjeke ove interpretacije možete naći
12:16
in John Milton's "Paradise Lost."
283
724578
2782
u "Izgubljenom raju", Džona Miltona.
12:19
In the garden, Adam and Eve are materially content.
284
727360
4197
U raju, Adam i Eva
su materijalno zadovoljni.
su materijalno zadovoljni.
12:23
They're happy. They are satisfied.
285
731557
2104
Srećni su i zadovoljni.
12:25
However, they also lack knowledge
286
733661
2293
Međutim, nedostaje im znanje
12:27
and self-awareness.
287
735954
1640
i samosvest.
12:29
The moment they eat the aptly named
288
737594
3319
U trenutku kada pojedu
prigodno nazvano, voće znanja,
12:32
fruit of knowledge,
289
740913
1293
12:34
that's when they discover themselves.
290
742206
2605
oni otkrivaju sebe.
12:36
They become aware. They achieve autonomy.
291
744811
4031
Postaju svesni. Postižu nezavisnost.
12:40
The price to pay, however, is leaving the garden.
292
748842
3126
Međutim, cena koju plaćaju
je napuštanje raja.
je napuštanje raja.
12:43
So privacy, in a way, is both the means
293
751968
3881
Dakle, privatnost je i sredstvo
12:47
and the price to pay for freedom.
294
755849
2962
i cena koja se plaća za slobodu.
12:50
Again, marketers tell us
295
758811
2770
Opet, stručnjaci kažu
12:53
that big data and social media
296
761581
3019
da "veliki podaci" i društveni mediji
12:56
are not just a paradise of profit for them,
297
764600
2979
za njih nisu samo raj profita,
12:59
but a Garden of Eden for the rest of us.
298
767579
2457
nego i Rajski vrt za nas ostale.
13:02
We get free content.
299
770036
1238
Dobijamo besplatan sadržaj.
13:03
We get to play Angry Birds. We get targeted apps.
300
771274
3123
Možemo da igramo "Angry Birds".
Dobijamo ciljane aplikacije.
Dobijamo ciljane aplikacije.
13:06
But in fact, in a few years, organizations
301
774397
2897
Ali u stvari, za nekoliko godina,
organizacije će znati toliko o nama,
13:09
will know so much about us,
302
777294
1609
13:10
they will be able to infer our desires
303
778903
2710
da će biti u mogućnosti
da zaključe o našim željama
da zaključe o našim željama
13:13
before we even form them, and perhaps
304
781613
2204
pre nego što ih mi uobličimo,
13:15
buy products on our behalf
305
783817
2447
i možda da kupuju proizvode za nas,
13:18
before we even know we need them.
306
786264
2274
pre nego što i znamo da su nam potrebni.
13:20
Now there was one English author
307
788538
3237
Postojao je jedan engleski autor
13:23
who anticipated this kind of future
308
791775
3045
koji je predvideo ovakvu budućnost
13:26
where we would trade away
309
794820
1405
gde menjamo svoju autonomiju i slobodu
13:28
our autonomy and freedom for comfort.
310
796225
3548
za udobnost.
13:31
Even more so than George Orwell,
311
799773
2161
Čak i više nego Džordž Orvel,
13:33
the author is, of course, Aldous Huxley.
312
801934
2761
taj autor je, naravno, Oldos Haksli.
13:36
In "Brave New World," he imagines a society
313
804695
2854
U "Vrlom novom svetu"
on predstavlja društvo
on predstavlja društvo
13:39
where technologies that we created
314
807549
2171
gde nas tehnologije,
13:41
originally for freedom
315
809720
1859
koje smo stvorili pre svega za slobodu,
13:43
end up coercing us.
316
811579
2567
na kraju zarobe.
13:46
However, in the book, he also offers us a way out
317
814146
4791
Međutim, on u knjizi nudi
i izlaz iz takvog društva,
i izlaz iz takvog društva,
13:50
of that society, similar to the path
318
818937
3438
sličan putu
13:54
that Adam and Eve had to follow to leave the garden.
319
822375
3955
kojim su Adam i Eva morali da krenu
da bi izašli iz vrta.
da bi izašli iz vrta.
13:58
In the words of the Savage,
320
826330
2147
Prema rečima Divljaka,
14:00
regaining autonomy and freedom is possible,
321
828477
3069
moguće je povratiti autonomiju i slobodu,
14:03
although the price to pay is steep.
322
831546
2679
ali je cena koja se plaća visoka.
14:06
So I do believe that one of the defining fights
323
834225
5715
Verujem da će jedna od definišućih borbi
našeg vremena
našeg vremena
14:11
of our times will be the fight
324
839940
2563
biti borba
14:14
for the control over personal information,
325
842503
2387
za kontrolu naših ličnih informacija,
14:16
the fight over whether big data will become a force
326
844890
3507
borba oko pitanja da li će "veliki podaci"
biti sila slobode
14:20
for freedom,
327
848397
1289
14:21
rather than a force which will hiddenly manipulate us.
328
849686
4746
ili sila koja će u potaji
manipulisati nama.
manipulisati nama.
14:26
Right now, many of us
329
854432
2593
Trenutno, mnogi od nas
14:29
do not even know that the fight is going on,
330
857025
2753
ni ne znaju da se vodi borba,
14:31
but it is, whether you like it or not.
331
859778
2672
ali vodi se, sviđalo vam se to ili ne.
14:34
And at the risk of playing the serpent,
332
862450
2804
Uz rizik da preuzmem ulogu zmije,
14:37
I will tell you that the tools for the fight
333
865254
2897
reći ću vam da su alati te borbe ovde,
14:40
are here, the awareness of what is going on,
334
868151
3009
svest o tome šta se dešava,
14:43
and in your hands,
335
871160
1355
i u vašim rukama,
14:44
just a few clicks away.
336
872515
3740
na samo nekoliko klikova od vas.
14:48
Thank you.
337
876255
1482
Hvala.
14:49
(Applause)
338
877737
4477
(Aplauz)
ABOUT THE SPEAKER
Alessandro Acquisti - Privacy economistWhat motivates you to share your personal information online? Alessandro Acquisti studies the behavioral economics of privacy (and information security) in social networks.
Why you should listen
Online, we humans are paradoxical: We cherish privacy, but freely disclose our personal information in certain contexts. Privacy economics offers a powerful lens to understand this paradox, and the field has been spearheaded by Alessandro Acquisti and his colleagues' analyses of how we decide what to share online and what we get in return.
His team's surprising studies on facial recognition software showed that it can connect an anonymous human face to an online name -- and then to a Facebook account -- in about 3 seconds. Other work shows how easy it can be to find a US citizen's Social Security number using basic pattern matching on public data. Work like this earned him an invitation to testify before a US Senate committee on the impact technology has on civil liberties.
Read about his work in the New York Times »
Alessandro Acquisti | Speaker | TED.com