TED2006
Michael Shermer: Why people believe weird things
Maikls Šērmers: Kāpēc cilvēki tic dīvainām lietām
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Kāpēc cilvēki uz siermaizēm redz Jaunavu Mariju vai dziesmā „Stairway to Heaven” saklausa dēmoniskus dziesmas vārdus? Izmantojot video un mūziku, skeptiķis Maikls Šērmers parāda, kā mēs pārliecinām paši sevi kaut kam noticēt un neņemt vērā faktus.
Michael Shermer - Skeptic
Michael Shermer debunks myths, superstitions and urban legends -- and explains why we believe them. Along with publishing Skeptic Magazine, he's author of Why People Believe Weird Things and The Mind of the Market. Full bio
Michael Shermer debunks myths, superstitions and urban legends -- and explains why we believe them. Along with publishing Skeptic Magazine, he's author of Why People Believe Weird Things and The Mind of the Market. Full bio
Double-click the English transcript below to play the video.
00:24
I'm Michael Shermer,
director of the Skeptics Society,
director of the Skeptics Society,
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Sveiki, esmu Maikls Šērmers,
Skeptics Society vadītājs,
Skeptics Society vadītājs,
00:27
publisher of "Skeptic" magazine.
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žurnāla Skeptic izdevējs.
00:28
We investigate claims of the paranormal,
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Mēs izmeklējam paranormālus,
00:30
pseudo-science, fringe groups and cults,
and claims of all kinds between,
and claims of all kinds between,
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pseidozinātniskus, margināļu un kultu,
kā arī visādus citādus apgalvojumus,
kā arī visādus citādus apgalvojumus,
00:34
science and pseudo-science
and non-science and junk science,
and non-science and junk science,
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kas izteikti zinātnes,
pseidozinātnes, štruntīgas zinātnes,
pseidozinātnes, štruntīgas zinātnes,
00:37
voodoo science, pathological science,
bad science, non-science,
bad science, non-science,
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burvju zinātnes, pataloģiskās zinātnes,
sliktas zinātnes, nezinātnes vārdā,
sliktas zinātnes, nezinātnes vārdā,
00:40
and plain old non-sense.
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un vecās labās muļķības arī.
00:42
And unless you've been on Mars recently,
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Ja vien pēdējo laiku
neesat pavadījuši uz Marsa,
neesat pavadījuši uz Marsa,
00:44
you know there's a lot of that out there.
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zināt, ka tādu mums ir daudz.
00:46
Some people call us debunkers,
which is kind of a negative term.
which is kind of a negative term.
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Daži mūs dēvē par apgāzējiem,
kam ir visai negatīva pieskaņa.
kam ir visai negatīva pieskaņa.
00:49
But let's face it, there's a lot of bunk.
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Taču būsim reāli, ir daudz ko apgāzt,
00:51
We are like the bunko squads
of the police departments out there --
of the police departments out there --
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un mēs esam kā policijas nodaļas
apgāzēju komanda, kas to likvidē.
apgāzēju komanda, kas to likvidē.
00:55
well, we're sort of like
the Ralph Naders of bad ideas,
the Ralph Naders of bad ideas,
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Mēs esam kā slikto ideju Ralfs Neiders,
00:58
(Laughter)
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(Smiekli)
01:00
trying to replace bad ideas
with good ideas.
with good ideas.
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mēģinot sliktās idejas aizstāt ar labajām.
01:02
I'll show you an example of a bad idea.
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Parādīšu jums sliktas idejas piemēru.
01:04
I brought this with me,
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Es paņēmu līdzi šo.
01:05
this was given to us
by NBC Dateline to test.
by NBC Dateline to test.
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Šo mums iedeva pārbaudīt NBC Dateline.
01:09
It's produced by the Quadro
Corporation of West Virginia.
Corporation of West Virginia.
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To Rietumvirdžīnijā ražo
Quadro Corporation.
Quadro Corporation.
01:13
It's called the Quadro 2000 Dowser Rod.
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To sauc par Quadro 2000 Dowser Rod.
01:16
(Laughter)
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(Smiekli)
01:17
This was being sold to high-school
administrators for $900 apiece.
administrators for $900 apiece.
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Šo te vidusskolu administratoriem
pārdeva par 900 ASV dolāriem gabalā.
pārdeva par 900 ASV dolāriem gabalā.
01:22
It's a piece of plastic with a Radio
Shack antenna attached to it.
Shack antenna attached to it.
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Tas ir plastmasas gabals,
kam piestiprināta Radio Shack antena.
kam piestiprināta Radio Shack antena.
01:27
You could dowse for all sorts of things,
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Ar rīksti var meklēt visu ko,
01:29
but this particular one was built
to dowse for marijuana
to dowse for marijuana
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bet tieši šī ir izgatavota,
lai meklētu marihuānu
lai meklētu marihuānu
01:32
in students' lockers.
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skolēnu skapīšos.
01:33
(Laughter)
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(Smiekli)
01:36
So the way it works
is you go down the hallway,
is you go down the hallway,
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Tā darbojas šādi, jūs ejat pa gaiteni,
01:39
and you see if it tilts
toward a particular locker,
toward a particular locker,
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līdz tā noliecas uz kāda skapīša pusi,
01:42
and then you open the locker.
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un tad jūs atverat šo skapīti.
01:44
So it looks something like this.
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Tas izskatās apmēram šādi.
01:45
I'll show you.
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Es parādīšu.
01:48
(Laughter)
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(Smiekli)
01:49
Well, it has kind of a right-leaning bias.
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Nē, nu, tai ir tieksme liekties pa labi.
01:53
Well, this is science,
so we'll do a controlled experiment.
so we'll do a controlled experiment.
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Šī ir zinātne,
tāpēc veiksim kontrolētu eksperimentu.
tāpēc veiksim kontrolētu eksperimentu.
01:56
It'll go this way for sure.
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Nu tā noteikti lieksies uz šo pusi.
01:57
(Laughter)
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(Smiekli)
02:01
Sir, do you want to empty
your pockets, please, sir?
your pockets, please, sir?
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Kungs, vai jūs, lūdzu,
neiztukšotu savas kabatas?
neiztukšotu savas kabatas?
02:04
(Laughter)
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(Smiekli)
02:06
So the question was, can it actually
find marijuana in students' lockers?
find marijuana in students' lockers?
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Jautājums bija, vai ar to tiešām
skapīšos var atrast marihuānu?
skapīšos var atrast marihuānu?
02:09
And the answer is,
if you open enough of them, yes.
if you open enough of them, yes.
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Atbilde ir ja atverat
pietiekami daudz skapīšu, jā.
pietiekami daudz skapīšu, jā.
02:12
(Laughter)
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(Smiekli)
02:13
(Applause)
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(Aplausi)
02:14
But in science, we have to keep track
of the misses, not just the hits.
of the misses, not just the hits.
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Taču zinātnē mums jāseko arī kļūmēm,
ne tikai tad, kad izdodas.
ne tikai tad, kad izdodas.
02:18
And that's probably the key lesson
to my short talk here:
to my short talk here:
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Tā, visticamāk, arī ir manas šodienas
īsās runas galvenā mācība.
īsās runas galvenā mācība.
02:21
This is how psychics work, astrologers,
tarot card readers and so on.
tarot card readers and so on.
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Šādi darbojas mediji, astrologi,
taro kāršu lasītāji un tā tālāk.
taro kāršu lasītāji un tā tālāk.
02:25
People remember the hits
and forget the misses.
and forget the misses.
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Cilvēki atceras izdošanos,
bet aizmirst kļūmes.
bet aizmirst kļūmes.
02:27
In science, we keep the whole database,
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Zinātnē mums jāuzskaita visi mēģinājumi,
02:29
and look to see if the number
of hits somehow stands out
of hits somehow stands out
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un jāpēta, vai izdošanās kaut kā izceļas
02:32
from the total number
you'd expect by chance.
you'd expect by chance.
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uz kopējā gadījumu skaita fona.
02:34
In this case, we tested it.
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Šajā gadījumā mēs to pārbaudījām.
02:35
We had two opaque boxes:
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Mums bija divas necaurredzamas kārbas:
02:37
one with government-approved THC
marijuana, and one with nothing.
marijuana, and one with nothing.
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vienā bija valsts apstiprināta
THC marihuāna, un otrā nebija nekā.
THC marihuāna, un otrā nebija nekā.
02:40
And it got it 50 percent of the time --
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Rīkstīte pareizi uzminēja 50% gadījumu,
02:42
(Laughter)
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(Smiekli)
02:43
which is exactly what you'd expect
with a coin-flip model.
with a coin-flip model.
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tieši šādu rezultātu varētu gaidīt
no monētas mešanas modeļa.
no monētas mešanas modeļa.
02:46
So that's just a fun little example
here of the sorts of things we do.
here of the sorts of things we do.
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Tas tāds jautrs piemēriņš tam,
ar ko mēs nodarbojamies.
ar ko mēs nodarbojamies.
02:50
"Skeptic" is the quarterly publication.
Each one has a particular theme.
Each one has a particular theme.
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Skeptic tiek izdots reizi ceturksnī.
Katram numuram ir sava tēma.
Katram numuram ir sava tēma.
02:54
This one is on the future of intelligence.
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Šis ir par intelekta nākotni.
02:56
Are people getting smarter or dumber?
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Vai cilvēki kļūst gudrāki vai dumjāki?
02:58
I have an opinion of this myself
because of the business I'm in,
because of the business I'm in,
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Darba pieredzes dēļ
man par to ir savs viedoklis.
man par to ir savs viedoklis.
03:01
but in fact, people, it turns out,
are getting smarter.
are getting smarter.
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Taču kā izrādās, cilvēki kļūst gudrāki.
03:03
Three IQ points per 10 years, going up.
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10 gadu laikā palielinās par 3 IQ punktiem.
03:06
Sort of an interesting thing.
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Diezgan interesanti.
03:08
With science, don't think of skepticism
as a thing, or science as a thing.
as a thing, or science as a thing.
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Nedomājiet par skepticismu
vai pat zinātni kā par lietu.
vai pat zinātni kā par lietu.
03:12
Are science and religion compatible?
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Vai zinātne un reliģija ir savietojamas?
03:13
It's like, are science
and plumbing compatible?
and plumbing compatible?
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Tas ir gluži kā jautāt
par zinātni un santehniku?
par zinātni un santehniku?
03:16
They're just two different things.
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Tās vienkārši ir divas dažādas lietas.
03:17
Science is not a thing. It's a verb.
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Zinātne nav lieta, tā ir darbība.
03:19
It's a way of thinking about things.
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Tas ir domāšanas veids.
03:21
It's a way of looking for natural
explanations for all phenomena.
explanations for all phenomena.
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Tie ir dabisku izskaidrojumu meklējumi
visām parādībām.
visām parādībām.
03:24
I mean, what's more likely:
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Kas ir ticamāk,
03:25
that extraterrestrial intelligences
or multi-dimensional beings
or multi-dimensional beings
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ārpuszemes saprāta
vai daudzdimensiju būtņu
vai daudzdimensiju būtņu
03:29
travel across vast distances
of interstellar space
of interstellar space
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ceļošana starpzvaigžņu telpas plašumos,
03:31
to leave a crop circle in Farmer Bob's
field in Puckerbrush, Kansas
field in Puckerbrush, Kansas
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lai atstātu riņķus zemnieka Boba
labības laukā, Pakerbrašā, Kanzasā,
labības laukā, Pakerbrašā, Kanzasā,
03:34
to promote skeptic.com, our web page?
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reklamējot mūsu tīmekļa lapu skeptic.com?
03:36
Or is it more likely that a reader
of "Skeptic" did this with Photoshop?
of "Skeptic" did this with Photoshop?
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Vai to drīzāk ar Photoshop paveica
kāds no Skeptic lasītājiem?
kāds no Skeptic lasītājiem?
03:41
And in all cases we have to ask --
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Mums visos gadījumos jājautā,
03:42
(Laughter)
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(Smiekli)
03:44
What's the more likely explanation?
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kāds ir visticamākais izskaidrojums?
03:46
Before we say something
is out of this world,
is out of this world,
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Pirms sakām,
ka kaut kas nav no šīs pasaules,
ka kaut kas nav no šīs pasaules,
03:48
we should first make sure
that it's not in this world.
that it's not in this world.
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vispirms jāpārliecinās,
ka tā nav šajā pasaulē.
ka tā nav šajā pasaulē.
03:51
What's more likely:
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Kas ir ticamāk,
03:52
that Arnold had extraterrestrial help
in his run for the governorship,
in his run for the governorship,
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ka Arnolds saņēma ārpuszemes palīdzību,
kandidējot uz senatora amatu?
kandidējot uz senatora amatu?
03:56
or that the "World Weekly News"
makes stuff up?
makes stuff up?
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vai World Weekly News
savas ziņas vienkārši izdomā?
savas ziņas vienkārši izdomā?
03:58
(Laughter)
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(Smiekli)
04:00
The same theme is expressed nicely
here in this Sidney Harris cartoon.
here in this Sidney Harris cartoon.
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Šī pati tēma ir skaisti parādīta
šajā Sidneja Herisa karikatūrā.
šajā Sidneja Herisa karikatūrā.
04:04
For those of you in the back,
it says here: "Then a miracle occurs.
it says here: "Then a miracle occurs.
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Tiem, kas sēž aizmugurē,
tur rakstīts: „Tad notiek brīnums.
tur rakstīts: „Tad notiek brīnums.
04:08
I think you need to be more
explicit here in step two."
explicit here in step two."
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Tev 2. darbībā būtu jābūt izsmeļošākam.”
04:10
This single slide completely dismantles
the intelligent design arguments.
the intelligent design arguments.
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Šis slaids viens pats pilnībā atbruņo
visus apzinātās radīšanas argumentus.
visus apzinātās radīšanas argumentus.
04:15
There's nothing more to it than that.
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Nekā vairāk tur nav.
04:17
(Applause)
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(Aplausi)
04:18
You can say a miracle occurs,
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Var teikt, ka notiek brīnums.
04:19
it's just that it doesn't explain
anything or offer anything.
anything or offer anything.
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Tikai tas mums neko nepasaka un nedod.
04:22
There's nothing to test.
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Tur nav, ko pārbaudīt.
04:23
It's the end of the conversation
for intelligent design creationists.
for intelligent design creationists.
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Tās ir beigas sarunai
ar apzinātās radīšanas kreacionistiem.
ar apzinātās radīšanas kreacionistiem.
04:27
And it's true, scientists sometimes throw
terms out as linguistic place fillers --
terms out as linguistic place fillers --
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Tā ir tiesa, zinātnieki reizēm svaidās
ar jēdzieniem kā aizpildītājvārdiem
ar jēdzieniem kā aizpildītājvārdiem
04:32
dark energy or dark matter,
something like that --
something like that --
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— tumšā enerģija,
tumšā matērija, kas tamlīdzīgs —
tumšā matērija, kas tamlīdzīgs —
04:34
until we figure out what it is,
we'll call it this.
we'll call it this.
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kamēr nesapratīsim,
kas tas ir, sauksim to šādi.
kas tas ir, sauksim to šādi.
04:37
It's the beginning of the causal
chain for science.
chain for science.
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Zinātnei tas ir cēloņu ķēdes sākums.
04:39
For intelligent design creationists,
it's the end of the chain.
it's the end of the chain.
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Apzināta radīšanas kreacionistiem
tās ir ķēdes beigas.
tās ir ķēdes beigas.
04:43
So again, we can ask this:
what's more likely?
what's more likely?
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Atkal varam vaicāt, kas ir ticamāk,
04:46
Are UFOs alien spaceships, or perceptual
cognitive mistakes, or even fakes?
cognitive mistakes, or even fakes?
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vai NLO ir citplanētiešu kosmosa kuģi,
uztveres kļūdas vai pat viltojumi?
uztveres kļūdas vai pat viltojumi?
04:50
This is a UFO shot from my house
in Altadena, California,
in Altadena, California,
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Lūk, NLO attēls, kas uzņemts
manās mājās Altadenā, Kalifornijā,
manās mājās Altadenā, Kalifornijā,
04:53
looking down over Pasadena.
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veroties Pasadīnas virzienā.
04:55
And if it looks a lot like a Buick
hubcap, it's because it is.
hubcap, it's because it is.
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Ja tas mazliet atgādina Buick disku,
tas ir tāpēc, ka tas arī ir Buick disks.
tas ir tāpēc, ka tas arī ir Buick disks.
04:59
You don't even need Photoshop
or high-tech equipment,
or high-tech equipment,
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Jums pat nevajag Photoshop,
nevajag modernu aprīkojumu,
nevajag modernu aprīkojumu,
05:02
you don't need computers.
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nevajag datorus.
05:03
This was shot with a throwaway
Kodak Instamatic camera.
Kodak Instamatic camera.
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Šis ir uzņemts ar vienreizlietojamo
Kodak Instamatic fotoaparātu.
Kodak Instamatic fotoaparātu.
05:06
You just have somebody off on the side
with a hubcap ready to go.
with a hubcap ready to go.
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Malā vienkārši jābūt kādam,
kurš gatavs pamest disku.
kurš gatavs pamest disku.
05:09
Camera's ready -- that's it.
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Fotoaparāts gatavībā — aiziet.
05:11
(Laughter)
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(Smiekli)
05:13
So, although it's possible
that most of these things are fake
that most of these things are fake
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Lai gan iespējams,
ka vairums no tām ir viltojumi,
ka vairums no tām ir viltojumi,
05:16
or illusions or so on,
and that some of them are real,
and that some of them are real,
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ilūzijas vai tamlīdzīgi,
bet dažas no tām ir īstas,
bet dažas no tām ir īstas,
05:20
it's more likely that all of them
are fake, like the crop circles.
are fake, like the crop circles.
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ticamāk, ka tās visas ir viltojumi,
gluži kā riņķi labības laukā.
gluži kā riņķi labības laukā.
05:23
On a more serious note, in all of science
we're looking for a balance
we're looking for a balance
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Pievēršoties kam nopietnākam,
mēs zinātnē meklējam līdzsvaru
mēs zinātnē meklējam līdzsvaru
05:27
between data and theory.
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starp datiem un teorijām.
05:28
In the case of Galileo,
he had two problems
he had two problems
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Galileja gadījumā
viņam bija divas problēmas,
viņam bija divas problēmas,
05:32
when he turned his telescope to Saturn.
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kad viņš pavērsa teleskopu pret Saturnu.
05:35
First of all, there was no
theory of planetary rings.
theory of planetary rings.
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Pirmkārt, nebija planētu gredzenu teorijas.
05:38
Second of all, his data
was grainy and fuzzy,
was grainy and fuzzy,
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Otrkārt, viņa dati
bija miglaini un neskaidri,
bija miglaini un neskaidri,
05:40
and he couldn't quite make out
what he was looking at.
what he was looking at.
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un viņš nevarēja saprast,
uz ko tieši skatās.
uz ko tieši skatās.
05:43
So he wrote that he had seen --
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Viņš rakstīja par redzēto:
05:44
"I have observed that the furthest
planet has three bodies."
planet has three bodies."
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„Es novēroju,
ka vistālākajai planētai ir trīs ķermeņi.”
ka vistālākajai planētai ir trīs ķermeņi.”
05:48
And this is what he ended up
concluding that he saw.
concluding that he saw.
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Šādi bija viņa secinājumi par redzēto.
05:51
So without a theory of planetary
rings and with only grainy data,
rings and with only grainy data,
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Tātad bez planētu gredzenu teorijas
un tikai ar neskaidriem datiem
un tikai ar neskaidriem datiem
05:54
you can't have a good theory.
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nevar radīt labu teoriju.
05:56
It wasn't solved until 1655.
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Tas netika atrisināts līdz 1655. gadam.
05:58
This is Christiaan Huygens's book
that catalogs all the mistakes
that catalogs all the mistakes
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Lūk, Kristiāna Heigensa grāmata,
kurā uzskaitītas visas kļūdas,
kurā uzskaitītas visas kļūdas,
06:01
people made trying to figure out
what was going on with Saturn.
what was going on with Saturn.
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ko cilvēki pieļāvuši, mēģinot izdomāt,
kas darās ar Saturnu.
kas darās ar Saturnu.
06:04
It wasn't till Huygens had two things:
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Heigensam bija divas lietas.
06:06
He had a good theory of planetary rings
and how the solar system operated,
and how the solar system operated,
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Viņam bija laba teorija par planētu gredzeniem
un to, kā darbojas saules sistēma.
un to, kā darbojas saules sistēma.
06:10
and he had better telescopic,
more fine-grain data
more fine-grain data
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Turklāt viņam bija labāki
un precīzāki teleskopiskie dati,
un precīzāki teleskopiskie dati,
06:13
in which he could figure out that
as the Earth is going around faster --
as the Earth is going around faster --
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kuros Heigenss varēja noteikt,
ka Zeme, saskaņā ar Keplera likumiem,
ka Zeme, saskaņā ar Keplera likumiem,
06:17
according to Kepler's Laws --
than Saturn, then we catch up with it.
than Saturn, then we catch up with it.
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riņķo ātrāk, nekā Saturns,
ka mēs to apdzenam.
ka mēs to apdzenam.
06:20
And we see the angles of the rings
at different angles, there.
at different angles, there.
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Gredzenus mēs redzam dažādos leņķos.
06:23
And that, in fact, turns out to be true.
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Šie apgalvojumi izrādījās patiesi.
06:26
The problem with having a theory is that
it may be loaded with cognitive biases.
it may be loaded with cognitive biases.
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Problēma ar kāda teorijām ir,
ka tā var būt pilna ar uztveres kļūdām.
ka tā var būt pilna ar uztveres kļūdām.
06:31
So one of the problems of explaining
why people believe weird things
why people believe weird things
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Tāpēc viena no problēmām izskaidrot,
kāpēc cilvēki tic dīvainām lietām, ir...
kāpēc cilvēki tic dīvainām lietām, ir...
06:34
is that we have things, on a simple level,
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es sākšu vienkāršā līmenī
06:36
and then I'll go to more serious ones.
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un tad nonākšu pie nopietnākām lietām.
06:38
Like, we have a tendency to see faces.
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Mums ir tieksme saskatīt sejas.
06:40
This is the face on Mars.
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Lūk, seja uz Marsa.
06:42
In 1976, where there was a whole movement
to get NASA to photograph that area
to get NASA to photograph that area
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1976. gadā tika organizēta vesela kustība,
lai NASA nofotografētu šo apgabalu,
lai NASA nofotografētu šo apgabalu,
06:46
because people thought this was monumental
architecture made by Martians.
architecture made by Martians.
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jo cilvēki domāja, ka tas ir
marsiešu arhitektūras piemineklis.
marsiešu arhitektūras piemineklis.
06:50
Here's the close-up of it from 2001.
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Lūk, ir 2001. gada tuvplāns.
06:53
If you squint, you can still see the face.
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Ja samiedzat acis,
joprojām varat redzēt seju.
joprojām varat redzēt seju.
06:56
And when you're squinting,
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Un miedzoties
06:57
you're turning that from fine-grain
to coarse-grain,
to coarse-grain,
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jūs skaidru attēlu
atkal padarāt neskaidru,
atkal padarāt neskaidru,
07:00
so you're reducing
the quality of your data.
the quality of your data.
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tātad samazināt datu kvalitāti.
07:02
And if I didn't tell you what to look for,
you'd still see the face,
you'd still see the face,
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Ja nebūtu teicis, ko meklēt,
jūs joprojām saskatītu seju,
jūs joprojām saskatītu seju,
07:05
because we're programmed
by evolution to see faces.
by evolution to see faces.
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jo evolūcija mūs ieprogrammējusi
saskatīt sejas.
saskatīt sejas.
07:08
Faces are important for us socially.
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Sejas mums ir svarīgas sociālā ziņā.
07:10
And of course, happy faces,
faces of all kinds are easy to see.
faces of all kinds are easy to see.
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Un, protams, smaidiņi.
Viegli saskatīt visvisādas sejas.
Viegli saskatīt visvisādas sejas.
07:14
You see the happy face on Mars, there.
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Re, redzams smaidiņš uz Marsa.
07:16
(Laughter)
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(Smiekli)
07:17
If astronomers were frogs,
perhaps they'd see Kermit the Frog.
perhaps they'd see Kermit the Frog.
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Ja astronomi būtu vardes,
varbūt viņi redzētu Vardi Kermitu.
varbūt viņi redzētu Vardi Kermitu.
07:20
Do you see him there? Little froggy legs.
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Redzat viņu? Varžveidīgas kājiņas.
07:22
Or if geologists were elephants?
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Vai ja ģeologi būtu ziloņi?
07:25
Religious iconography.
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Reliģiskā ikonogrāfija.
07:28
(Laughter)
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(Smiekli)
07:31
Discovered by a Tennessee baker in 1996.
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To 1996. gadā atklāja
kāds Tenisijas maiznieks.
kāds Tenisijas maiznieks.
07:33
He charged five bucks a head
to come see the nun bun
to come see the nun bun
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Viņš iekasēja piecīti no katra,
kurš gribēja redzēt mūķeņmaizīti,
kurš gribēja redzēt mūķeņmaizīti,
07:36
till he got a cease-and-desist
from Mother Teresa's lawyer.
from Mother Teresa's lawyer.
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līdz Mātes Terēzes advokāts
viņu iesūdzēja par prettiesisku rīcību.
viņu iesūdzēja par prettiesisku rīcību.
07:40
Here's Our Lady of Guadalupe and Our
Lady of Watsonville, just down the street,
Lady of Watsonville, just down the street,
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Lūk, mūsu Gvadelupas
un Vastonvilas lēdijas, tepat aiz stūra,
un Vastonvilas lēdijas, tepat aiz stūra,
07:43
or is it up the street from here?
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no šejienes varbūt pirms stūra?
07:45
Tree bark is particularly good
because it's nice and grainy, branchy,
because it's nice and grainy, branchy,
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Koka miza ir īpaši laba,
jo tā ir jauki graudaina, žuburaina,
jo tā ir jauki graudaina, žuburaina,
07:48
black-and-white splotchy and you can
get the pattern-seeking --
get the pattern-seeking --
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ar melnbaltiem plankumiem,
un varat meklēt rakstus
un varat meklēt rakstus
07:51
humans are pattern-seeking animals.
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— cilvēki ir rakstus meklējoši dzīvnieki.
07:53
Here's the Virgin Mary on the side
of a glass window in Sao Paulo.
of a glass window in Sao Paulo.
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Lūk, Jaunava Marija
uz stikla loga Sanpaulu.
uz stikla loga Sanpaulu.
07:57
Here's when the Virgin Mary made
her appearance on a cheese sandwich --
her appearance on a cheese sandwich --
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Lūk, Jaunava Marija
parādījusies uz siermaizes,
parādījusies uz siermaizes,
ko es kādā Lasvegasas kazino
pat dabūju paturēt rokā ,
pat dabūju paturēt rokā ,
08:00
which I got to actually
hold in a Las Vegas casino --
hold in a Las Vegas casino --
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protams, jo šī ir Amerika.
08:03
of course, this being America.
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08:04
(Laughter)
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(Smiekli)
08:06
This casino paid $28,500
on eBay for the cheese sandwich.
on eBay for the cheese sandwich.
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Kazino eBay par šo siermaizi
samaksāja 28 500 dolāru.
samaksāja 28 500 dolāru.
08:10
(Laughter)
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1976
(Smiekli)
08:12
But who does it really look like?
The Virgin Mary?
The Virgin Mary?
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Pēc kā tad tā patiesībā izskatās?
Jaunavas Marijas?
Jaunavas Marijas?
08:15
(Laughter)
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1979
(Smiekli)
08:17
It has that sort of
puckered lips, 1940s-era look.
puckered lips, 1940s-era look.
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Tai ir tās savilktās lūpiņas,
1940. gadu stilā.
1940. gadu stilā.
08:21
Virgin Mary in Clearwater, Florida.
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Jaunava Marija Klīrvoterā, Floridā.
08:22
I actually went to see this one.
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1976
Šo es pat aizbraucu apskatīt.
08:24
There was a lot of people there.
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Tur bija daudz cilvēku.
08:26
The faithful come in their wheelchairs
and crutches, and so on.
and crutches, and so on.
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Ticīgie ieradās savos ratiņkrēslos,
ar kruķiem, un tamlīdzīgi.
ar kruķiem, un tamlīdzīgi.
08:31
We went down and investigated.
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Mēs ieradāmies to izpētīt.
08:33
Just to give you a size, that's Dawkins,
me and The Amazing Randi,
me and The Amazing Randi,
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Lai jums būtu mērogs, lūk,
Dokinss, es un Apbrīnojamais Rendijs,
Dokinss, es un Apbrīnojamais Rendijs,
08:36
next to this two,
two and a half story-sized image.
two and a half story-sized image.
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līdzās divu, divarpus
stāvu lielajam attēlam.
stāvu lielajam attēlam.
08:38
All these candles, thousands of candles
people had lit in tribute to this.
people had lit in tribute to this.
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Visas šīs sveces, tūkstošiem sveču,
ko cilvēki bija iedeguši to godinot.
ko cilvēki bija iedeguši to godinot.
08:42
So we walked around the backside,
to see what was going on.
to see what was going on.
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Tā nu mēs aizgājām aizmugurē,
lai redzētu, kas tur notiek.
lai redzētu, kas tur notiek.
08:45
It turns out wherever there's
a sprinkler head and a palm tree,
a sprinkler head and a palm tree,
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Izrādās, ka jebkur,
kur ir smidzinātājs un palma,
kur ir smidzinātājs un palma,
08:48
you get the effect.
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var iegūt tādu efektu.
08:49
Here's the Virgin Mary on the backside,
which they started to wipe off.
which they started to wipe off.
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Lūk, Jaunava Marija otrā pusē,
ko viņi sāka slaucīt nost.
ko viņi sāka slaucīt nost.
08:53
I guess you can only have
one miracle per building.
one miracle per building.
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Laikam vienā ēkā
var būt tikai viens brīnums.
var būt tikai viens brīnums.
08:55
(Laughter)
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(Smiekli)
08:59
So is it really a miracle of Mary,
or is it a miracle of Marge?
or is it a miracle of Marge?
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Vai tas patiesi ir Marijas brīnums,
vai varbūt Mārdžas brīnums?
vai varbūt Mārdžas brīnums?
09:02
(Laughter)
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(Smiekli)
09:03
And now I'm going to finish up
with another example of this,
with another example of this,
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Es pabeigšu šo tēmu ar vēl vienu piemēru,
09:07
with auditory illusions.
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ar skaņas ilūzijām.
09:10
There's this film, "White Noise,"
with Michael Keaton,
with Michael Keaton,
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Ir tāda filma, „Baltais troksnis”
ar Maiklu Kītonu
ar Maiklu Kītonu
09:12
about the dead talking back to us.
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par to, kā mirušie ar mums sarunājas.
09:15
By the way, the whole business of talking
to the dead is not that big a deal.
to the dead is not that big a deal.
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Starp citu, visa tā runāšanas padarīšana
ar mirušajiem nav nekas īpašs.
ar mirušajiem nav nekas īpašs.
09:19
Anybody can do it, turns out.
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Izrādās, to var jebkurš.
09:20
It's getting the dead to talk
back that's the really hard part.
back that's the really hard part.
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Grūtības sagādā panākt,
ka mirušie mums atbild.
ka mirušie mums atbild.
09:23
(Laughter)
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(Smiekli)
09:24
In this case, supposedly, these messages
are hidden in electronic phenomena.
are hidden in electronic phenomena.
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Šajā gadījumā elektroniskās parādībās
ir apslēpti ziņojumi.
ir apslēpti ziņojumi.
09:28
There's a ReverseSpeech.com web page
where I downloaded this stuff.
where I downloaded this stuff.
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Lūk, tīmekļa lapa ReverseSpeech.com,
kur lejuplādēju šo te ierakstu.
kur lejuplādēju šo te ierakstu.
09:31
This is the most famous one
of all of these.
of all of these.
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Šī dziesma ir visslavenākā no visām.
09:35
Here's the forward version
of the very famous song.
of the very famous song.
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Lūk, šī ļoti slavenā dziesma
pareizajā virzienā,
pareizajā virzienā,
09:37
(Music with lyrics)
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(Mūzika ar vārdiem)
09:39
If there's a bustle in your hedgerow
don't be alarmed now.
don't be alarmed now.
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If there's a bustle in your hedgerow
don't be alarmed now.
don't be alarmed now.
09:44
It's just a spring clean
for the May Queen.
for the May Queen.
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It's just a spring clean
for the May Queen.
for the May Queen.
09:50
Yes, there are two paths you
can go by, but in the long run,
can go by, but in the long run,
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Yes, there are two paths you
can go by, but in the long run,
can go by, but in the long run,
09:56
There's still time to change
the road you're on
the road you're on
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There's still time to change
the road you're on
the road you're on
10:03
Couldn't you just listen to that all day?
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Vai to tik nevarētu klausīties visu dienu?
10:06
All right, here it is backwards,
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Nu labi, te nu tā ir otrādi,
10:07
and see if you can hear the hidden
messages that are supposedly in there.
messages that are supposedly in there.
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pamēģiniet saklausīt slēptos ziņojumus,
kam tur it kā būtu jābūt. (Mūzika)
kam tur it kā būtu jābūt. (Mūzika)
10:12
(Music with unintelligible lyrics)
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(Mūzika ar nesaprotamiem vārdiem)
10:26
(Lyrics) Satan!
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(Vārdi) Sātans!
10:27
(Unintelligible lyrics continue)
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(Nesaprotamie vārdi turpinās)
10:41
What did you get?
Audience: Satan!
Audience: Satan!
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Ko saklausījāt?
Publika: Sātans!
Publika: Sātans!
10:43
Satan. OK, at least we got "Satan".
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Sātans. Labi, vismaz sātanu saklausījām.
10:45
Now, I'll prime the auditory
part of your brain
part of your brain
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Tagad pamācīšu jūsu smadzeņu
klausīšanās daļu,
klausīšanās daļu,
10:47
to tell you what you're supposed
to hear, and then hear it again.
to hear, and then hear it again.
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lai pateiktu, kas jums būtu jādzird,
un pēc tam noklausīsimies vēlreiz.
un pēc tam noklausīsimies vēlreiz.
10:50
(Music with lyrics)
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(Mūzika ar vārdiem)
11:17
(Music ends)
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(Mūzika beidzas)
11:18
(Laughter)
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(Smiekli)
11:19
(Applause)
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(Aplausi)
11:26
You can't miss it
when I tell you what's there.
when I tell you what's there.
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Nevar palaist garām,
ja pasaku, kam tur jābūt.
ja pasaku, kam tur jābūt.
11:28
(Laughter)
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(Smiekli)
11:32
I'm going to just end
with a positive, nice little story.
with a positive, nice little story.
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Labi, pabeigšu ar pozitīvu, jauku stāstiņu.
11:36
The Skeptics is a nonprofit
educational organization.
educational organization.
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Skeptics ir bezpeļņas
izglītības organizācija.
izglītības organizācija.
11:39
We're always looking for little
good things that people do.
good things that people do.
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Mēs vienmēr meklējam
labas lietas, ko dara cilvēki.
labas lietas, ko dara cilvēki.
11:41
And in England, there's a pop singer.
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2009
Anglijā ir popmūzikas dziedātāja.
11:43
One of the top popular singers
in England today, Katie Melua.
in England today, Katie Melua.
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3745
Šobrīd viena no vispopulārākajām
dziedātājām Anglijā ir Keitija Melua.
dziedātājām Anglijā ir Keitija Melua.
11:47
And she wrote a beautiful song.
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Viņa sarakstīja burvīgu dziesmu.
11:49
It was in the top five in 2005, called,
"Nine Million Bicycles in Beijing."
"Nine Million Bicycles in Beijing."
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2005. gadā tā bija topa pieciniekā,
dziesmu sauc Nine Million Bicycles in Beijing.
dziesmu sauc Nine Million Bicycles in Beijing.
Tas ir mīlas stāsts —
viņa ir kā Apvienotās Karalistes Nora Džonsa —
viņa ir kā Apvienotās Karalistes Nora Džonsa —
11:54
It's a love story -- she's sort
of the Norah Jones of the UK --
of the Norah Jones of the UK --
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11:57
about how she much loves her guy,
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par to, kā viņa mīl savu puisi,
11:59
and compared to nine million
bicycles, and so forth.
bicycles, and so forth.
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salīdzinot ar deviņiem miljoniem velosipēdu, utt.
12:02
And she has this one passage here.
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Viņai tur ir viens fragments.
12:04
(Music)
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(Mūzika)
12:05
(Lyrics) We are 12 billion
light-years from the edge
light-years from the edge
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(Vārdi) Mēs esam 12 miljardu
gaismas gadu no pasaules malas.
gaismas gadu no pasaules malas.
12:11
That's a guess,
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Tas ir minējums.
12:13
No one can ever say it's true,
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Neviens nekad nepateiks, vai tā ir tiesa.
12:17
But I know that I will always be with you.
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Bet zinu, ka vienmēr būšu ar tevi.
12:22
Michael Shermer: Well, that's nice.
At least she got it close.
At least she got it close.
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Maikls Šērmers: Tas ir jauki.
Vismaz viņa bija tuvu.
Vismaz viņa bija tuvu.
12:25
In America it'd be,
"We're 6,000 light years from the edge."
"We're 6,000 light years from the edge."
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Amerikā tas būtu: „Mēs esam 6000
gaismas gadu no pasaules malas”.
gaismas gadu no pasaules malas”.
12:28
(Laughter)
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(Smiekli)
12:29
But my friend, Simon Singh, the particle
physicist now turned science educator,
physicist now turned science educator,
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Mans draugs, Saimons Sings, elementārdaļiņu
fiziķis, kas nu kļuvis par zinātnes izglītotāju,
fiziķis, kas nu kļuvis par zinātnes izglītotāju,
12:33
who wrote the book
"The Big Bang," and so on,
"The Big Bang," and so on,
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viņš sarakstīja grāmatu
„Lielais sprādziens”, un tamlīdzīgi,
„Lielais sprādziens”, un tamlīdzīgi,
12:35
uses every chance he gets
to promote good science.
to promote good science.
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izmanto katru iespēju
veicināt labu zinātnes izpratni.
veicināt labu zinātnes izpratni.
12:37
And so he wrote an op-ed piece
in "The Guardian" about Katie's song,
in "The Guardian" about Katie's song,
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Tad nu viņš The Guardian
publicēja viedokli par Keitijas dziesmu,
publicēja viedokli par Keitijas dziesmu,
12:41
in which he said, well, we know exactly
how far from the edge.
how far from the edge.
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kurā rakstīja: „Vispār mēs precīzi zinām,
cik tālu esam no pasaules malas.”
cik tālu esam no pasaules malas.”
12:46
You know, it's 13.7 billion light years,
and it's not a guess.
and it's not a guess.
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Tā ir 13,7 miljardu gaismas gadu attālumā,
un tas nav minējums.
un tas nav minējums.
12:50
We know within precise
error bars how close it is.
error bars how close it is.
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Ar precīzām kļūdas robežām
mēs zinām, cik tālu tā ir.
mēs zinām, cik tālu tā ir.
Tātad varam teikt, lai arī ne pilnīgi droši,
tā ir visai tuvu patiesībai.
tā ir visai tuvu patiesībai.
12:54
So we can say, although not absolutely
true, it's pretty close to being true.
true, it's pretty close to being true.
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Gods kam gods, pēc viedokļa publicēšanas
Keitija viņam piezvanīja
Keitija viņam piezvanīja
12:58
And, to his credit, Katie called him up
after this op-ed piece came out, and said,
after this op-ed piece came out, and said,
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13:02
"I'm so embarrassed.
I was in the astronomy club.
I was in the astronomy club.
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un teica: „Man ir tāds kauns.
Es biju astronomijas kluba biedre
Es biju astronomijas kluba biedre
13:05
I should've known better."
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Man taču vajadzēja zināt.”
13:06
And she re-cut the song.
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Viņa pārtaisīja dziesmu.
13:07
So I will end with the new version.
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Tad nu es beigšu ar jauno versiju.
13:09
(Music with lyrics)
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(Mūzika ar vārdiem)
13:11
We are 13.7 billion light years
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Mēs esam 13,7 miljardus gaismas gadu
13:13
from the edge of the observable universe.
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attālumā no novērojamā Visuma malas
13:17
That's a good estimate
with well-defined error bars.
with well-defined error bars.
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Tas ir labs aprēķins
ar precīzi noteiktām kļūdas robežām.
ar precīzi noteiktām kļūdas robežām.
13:20
And with the available information,
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Un, ņemot vērā pieejamo informāciju,
13:24
I predict that I will always be with you.
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es prognozēju, ka vienmēr būšu ar tevi.
13:28
(Laughter)
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(Aplausi)
13:29
How cool is that?
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Vai nav forši?
13:30
(Applause)
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(Aplausi)
ABOUT THE SPEAKER
Michael Shermer - SkepticMichael Shermer debunks myths, superstitions and urban legends -- and explains why we believe them. Along with publishing Skeptic Magazine, he's author of Why People Believe Weird Things and The Mind of the Market.
Why you should listen
As founder and publisher of Skeptic Magazine, Michael Shermer has exposed fallacies behind intelligent design, 9/11 conspiracies, the low-carb craze, alien sightings and other popular beliefs and paranoias. But it's not about debunking for debunking's sake. Shermer defends the notion that we can understand our world better only by matching good theory with good science.
Shermer's work offers cognitive context for our often misguided beliefs: In the absence of sound science, incomplete information can powerfully combine with the power of suggestion (helping us hear Satanic lyrics when "Stairway to Heaven" plays backwards, for example). In fact, a common thread that runs through beliefs of all sorts, he says, is our tendency to convince ourselves: We overvalue the shreds of evidence that support our preferred outcome, and ignore the facts we aren't looking for.
He writes a monthly column for Scientific American, and is an adjunct at Claremont Graduate University and Chapman University. His latest book is The Believing Brain: From Ghosts and Gods to Politics and Conspiracies—How We Construct Beliefs and Reinforce Them as Truths. He is also the author of The Mind of the Market, on evolutionary economics, Why Darwin Matters: Evolution and the Case Against Intelligent Design, and The Science of Good and Evil. And his next book is titled The Moral Arc of Science.
Michael Shermer | Speaker | TED.com