Every day we face issues like climate change or the safety of vaccines where we have to answer questions whose answers rely heavily on scientific information. Scientists tell us that the world is warming. Scientists tell us that vaccines are safe. But how do we know if they are right? Why should be believe the science? The fact is, many of us actually don't believe the science. Public opinion polls consistently show that significant proportions of the American people don't believe the climate is warming due to human activities, don't think that there is evolution by natural selection, and aren't persuaded by the safety of vaccines.
Svakodnevno smo suočeni s problemima kao što su klimatske promjene ili sigurnosti cjepiva gdje moramo odgovoriti na pitanja čiji se odgovori oslanjaju na znanstvene informacije. Znanstvenici govore o globalnom zatopljenju. Govore nam da su cjepiva sigurna. Kako znati da su oni u pravu? Zašto bi trebali vjerovati znanosti? Činjenica je da mnogi od nas ne vjeruju u znanost. Istraživanja javnog mišljenja pokazuju da velika većina američke popoulacije ne vjeruje da se klima mijenja zbog ljudskih aktivnosti. ne misle da postoji evolucija prirodnom selekcijom, i nisu uvjereni u sigurnost cjepiva.
So why should we believe the science? Well, scientists don't like talking about science as a matter of belief. In fact, they would contrast science with faith, and they would say belief is the domain of faith. And faith is a separate thing apart and distinct from science. Indeed they would say religion is based on faith or maybe the calculus of Pascal's wager. Blaise Pascal was a 17th-century mathematician who tried to bring scientific reasoning to the question of whether or not he should believe in God, and his wager went like this: Well, if God doesn't exist but I decide to believe in him nothing much is really lost. Maybe a few hours on Sunday. (Laughter) But if he does exist and I don't believe in him, then I'm in deep trouble. And so Pascal said, we'd better believe in God. Or as one of my college professors said, "He clutched for the handrail of faith." He made that leap of faith leaving science and rationalism behind.
Zašto bismo vjerovali znanosti? Znanstvenici ne vole govoriti o znanosti kao predmetu vjerovanja. Oni bi suprostavili znanost i vjeru smatrajući da je vjerovanje domena vjere. Vjera je zasebna stvar i različita od znanosti. Doduše religija je zasnovana na vjerovanju ili možda ishodu Paskalove oklade. Blaise Pascal bio je matematičar sedamnaestoga stoljeća koji je pokušao dati znanstveno objašnjenje na pitanje trebamo li vjerovati u Boga te njegova oklada glasi ovako: Ako Bog ne postoji, ali odlučim vjerovati u njega neću izgubiti mnogo. Možda par sati nedjeljom. (Smijeh) Ali ako On postoji i ja ne vjerujem u njega, onda sam u nevolji. Pascal je zaključio da je bolje da vjerujemo u Boga. Ili kako je jedan od mojih kolega profesora rekao, "Zgrabio se za ogradu vjere." Napravio je iskorak u vjeri ostavljajući znanost i racionalizam iza sebe.
Now the fact is though, for most of us, most scientific claims are a leap of faith. We can't really judge scientific claims for ourselves in most cases. And indeed this is actually true for most scientists as well outside of their own specialties. So if you think about it, a geologist can't tell you whether a vaccine is safe. Most chemists are not experts in evolutionary theory. A physicist cannot tell you, despite the claims of some of them, whether or not tobacco causes cancer. So, if even scientists themselves have to make a leap of faith outside their own fields, then why do they accept the claims of other scientists? Why do they believe each other's claims? And should we believe those claims?
Činjenica je za mnoge od nas da su mnoge znanstvene tvrdnje iskorak u vjeri. Ne možemo sami prosuditi znanstvene tvrdnje u većini slučajeva. Ovo također vrijedi za većinu znanstvenika izvan okvira njihovih specijalnosti. Ako bolje razmislimo, geolog nam ne može reći je li cijepljenje sigurno. Većina kemičara nije stručna u teoriji evolucije. Fizičar vam ne može reći, unatoč tvrdnjama nekih uzrokuje li pušenje rak. Ako i sami znanstvenici moraju imati vjere izvan vlastitih područja zašto onda prihvaćaju tvrdnje drugih znanstvenika? Zašto vjeruju tvrdnjama jedni drugih? Trebamo li vjerovati tim tvrdnjama?
So what I'd like to argue is yes, we should, but not for the reason that most of us think. Most of us were taught in school that the reason we should believe in science is because of the scientific method. We were taught that scientists follow a method and that this method guarantees the truth of their claims. The method that most of us were taught in school, we can call it the textbook method, is the hypothetical deductive method. According to the standard model, the textbook model, scientists develop hypotheses, they deduce the consequences of those hypotheses, and then they go out into the world and they say, "Okay, well are those consequences true?" Can we observe them taking place in the natural world? And if they are true, then the scientists say, "Great, we know the hypothesis is correct."
Željela bih raspraviti o tome da trebamo vjerovati ali ne iz razloga što većina od nas misli. Većina je u školi učila da su razlog zašto bismo trebali vjerovati u znanost - znanstvene metode. Učili su nas da se znanstvenici drže metoda i da one jamče istinitost njihovih tvrdnji. Metoda koju je većina naučila u školi zvat ćemo ju udžbenička metoda, hipotetska deduktivna metoda. Prema standardnom modelu, iz udžbenika, znanstvenici razvijaju hipotezu, zaključuju posljedice tih hipoteza i zatim ih predstavljaju svijetu govoreći: „Jesu li ovi zaključci istiniti?“ Možemo li ih promatrati u sklopu stvarnog svijeta? Ako su istinite, znanstvenici će reći: „Odlično, znamo da je hipoteza točna.“
So there are many famous examples in the history of science of scientists doing exactly this. One of the most famous examples comes from the work of Albert Einstein. When Einstein developed the theory of general relativity, one of the consequences of his theory was that space-time wasn't just an empty void but that it actually had a fabric. And that that fabric was bent in the presence of massive objects like the sun. So if this theory were true then it meant that light as it passed the sun should actually be bent around it. That was a pretty startling prediction and it took a few years before scientists were able to test it but they did test it in 1919, and lo and behold it turned out to be true. Starlight actually does bend as it travels around the sun. This was a huge confirmation of the theory. It was considered proof of the truth of this radical new idea, and it was written up in many newspapers around the globe.
Postoje mnogi poznati primjeri u povijesti znanosti o znanstvenicima koji su napravili upravo to. Jedan od najpoznatijih primjera dolazi iz rada Alberta Einsteina. Kada je Einstein formulirao opću teoriju relativnosti jedan od zaključaka njegove teorije bio je da prostor-vrijeme nisu samo praznina već sadrži materiju. Ova je materija zakrivljena u prisutnosti tijela velike mase kao što je Sunce. Ako je ova teorija istinita to bi značilo da svijetlost kako putuje od Sunca bi trebala biti zakrivljena oko Sunca. To je bila zapanjujuća teorija i trebalo je nekoliko godina da znanstvenici budu u mogućnosti testirati ju, učinili su to 1919., te se ispostavila istinitom. Zvjezdana svjetlost zavija kako putuje oko Sunca. To je bila velika potvrda teoriji. Smatrala se dokazom za istinitost te radikalne nove ideje, i izašla je u mnogim novinama u cijelom svijetu.
Now, sometimes this theory or this model is referred to as the deductive-nomological model, mainly because academics like to make things complicated. But also because in the ideal case, it's about laws. So nomological means having to do with laws. And in the ideal case, the hypothesis isn't just an idea: ideally, it is a law of nature. Why does it matter that it is a law of nature? Because if it is a law, it can't be broken. If it's a law then it will always be true in all times and all places no matter what the circumstances are. And all of you know of at least one example of a famous law: Einstein's famous equation, E=MC2, which tells us what the relationship is between energy and mass. And that relationship is true no matter what.
Ponekad se ova teorija ili ovaj model nazivaju deduktivno-nomologični model, ponajprije zato što znanstvenici vole komplicirati stvari. Ali i zato što je u idealnom slučaju riječ o zakonu. Nomologičan znači imati veze sa zakonom. U idealnom slučaju, hipoteza nije samo ideja nego i prirodni zakon. Zašto je bitno da je prirodni zakon? Jer ako je zakon, ne smije biti prekršen. Ako je zakon onda je uvijek istinit. u svako doba i na svakom mjestu bez obzira na okolnosti. Svi znate barem jedan primjer poznatog zakona: Einsteinovu slavnu jednadžbu E=MC2, koja nam pokazuje vezu između energije i mase. A ta je veza istinita u svakom slučaju.
Now, it turns out, though, that there are several problems with this model. The main problem is that it's wrong. It's just not true. (Laughter) And I'm going to talk about three reasons why it's wrong. So the first reason is a logical reason. It's the problem of the fallacy of affirming the consequent. So that's another fancy, academic way of saying that false theories can make true predictions. So just because the prediction comes true doesn't actually logically prove that the theory is correct. And I have a good example of that too, again from the history of science. This is a picture of the Ptolemaic universe with the Earth at the center of the universe and the sun and the planets going around it. The Ptolemaic model was believed by many very smart people for many centuries. Well, why? Well the answer is because it made lots of predictions that came true. The Ptolemaic system enabled astronomers to make accurate predictions of the motions of the planet, in fact more accurate predictions at first than the Copernican theory which we now would say is true. So that's one problem with the textbook model. A second problem is a practical problem, and it's the problem of auxiliary hypotheses. Auxiliary hypotheses are assumptions that scientists are making that they may or may not even be aware that they're making. So an important example of this comes from the Copernican model, which ultimately replaced the Ptolemaic system. So when Nicolaus Copernicus said, actually the Earth is not the center of the universe, the sun is the center of the solar system, the Earth moves around the sun. Scientists said, well okay, Nicolaus, if that's true we ought to be able to detect the motion of the Earth around the sun. And so this slide here illustrates a concept known as stellar parallax. And astronomers said, if the Earth is moving and we look at a prominent star, let's say, Sirius -- well I know I'm in Manhattan so you guys can't see the stars, but imagine you're out in the country, imagine you chose that rural life — and we look at a star in December, we see that star against the backdrop of distant stars. If we now make the same observation six months later when the Earth has moved to this position in June, we look at that same star and we see it against a different backdrop. That difference, that angular difference, is the stellar parallax. So this is a prediction that the Copernican model makes. Astronomers looked for the stellar parallax and they found nothing, nothing at all. And many people argued that this proved that the Copernican model was false.
Ispostavilo se da postoji nekoliko problema kod ovog modela. Glavni problem je da je netočna. Jednostavno nije istinita. (Smijeh) A ja ću ispričati tri razloga zašto je netočna. Prvi je razlog logičan. Problem je u pogrešci potvrđivanja posljedičnog. To je maštoviti način, akademski način da se kaže kako pogrešna teorija može imati istinita predviđanja. Samo zato što se predviđanje obistinilo ne znači da logično dokazuje ispravnost teorije. Imam za to dobar primjer, ponovno iz povijesti znanosti. Ovo je slika Ptolemejevog sustava sa Zemljom u središtu svemira te Suncem i planetima koji se gibaju oko nje. U Ptolomejev su sustav vjerovali mnogi učeni ljudi kroz stoljeća. Zašto? Odgovor je zato što je imao mnoga predviđanja koja su se obistinila. Ptolemejev sustav omogućio je astronomima da naprave točna predviđanja o gibanjima planeta, isprva mnogo točnija predviđanja od Kopernikove teorije koju danas smatramo istinitom. To je jedan od problema udžbeničkog modela. Drugi problem je praktične prirode, a to su pomoćne hipoteze. Pomoćne su hipoteze pretpostavke koje znanstvenici stvaraju a da ih jesu ili nisu pri tom svjesni. Jedan važan primjer ovoga Kopernikov je model koji je u konačnici zamijenio Ptolomejev sustav. Kada je Nikola Kopernik tvrdio, da Zemlja nije u središtu Svemira, nego je Sunce u središtu Sunčeva sustava, a Zemlja kruži oko Sunca. Znanstvenici su smatrali da ako je to istina trebali bismo moći otkriti gibanje Zemlje oko Sunca. Ovaj slajd ovdje prikazuje koncept poznat kao zvjezdana paralaksa. Znanstvenici su smatrali da ako se Zemlja giba a mi promatramo istaknutu zvijezdu, recimo, Sirius - ja sam s Manhattana pa ne vidim zvijezde ail zamislite da ste na selu da ste izabrali seoski život- promatrate zvijezdu u prosincu te ju vidimo naspram udaljenijih zvijezda u pozadini. Ako napravimo isto opažanje šest mjeseci poslije kada se Zemlja pomaknula u ovaj položaj u lipnju promatramo tu istu zvijezdu ali naspram drukčije pozadine. Ova kutna razlika naziva se zvjezdana paralaksa. I to je predviđanje nastalo na osnovi Kopernikova modela. Astronomi u potrazi za zvjezdanom paralaksom nisu pronašli ama baš ništa. Mnogi su ljudi tvrdili da ovo dokazuje da je Kopernikov model netočan.
So what happened? Well, in hindsight we can say that astronomers were making two auxiliary hypotheses, both of which we would now say were incorrect. The first was an assumption about the size of the Earth's orbit. Astronomers were assuming that the Earth's orbit was large relative to the distance to the stars. Today we would draw the picture more like this, this comes from NASA, and you see the Earth's orbit is actually quite small. In fact, it's actually much smaller even than shown here. The stellar parallax therefore, is very small and actually very hard to detect.
Pa što se dogodilo? Gledajući unatrag možemo reći da su astronomi stvarali dvije pomoćne hipoteze, od kojih obje danas smatramo netočnima. Prva je bila pretpostavka o veličini Zemljine orbite. Astronomi su pretpostavljali da je Zemljina orbita velika s obzirom na udaljenost od zvijezda. Danas bismo nacrtali ovakvu sliku, koja je iz NASE, i vidi se da je Zemljina orbita zapravo vrlo mala. Ustvari mnogo manja nego što je ovdje prikazano. Stoga je zvjezdana paralaksa vrlo mala i jako ju je teško otkriti.
And that leads to the second reason why the prediction didn't work, because scientists were also assuming that the telescopes they had were sensitive enough to detect the parallax. And that turned out not to be true. It wasn't until the 19th century that scientists were able to detect the stellar parallax.
To vodi do drugog razloga zašto predviđanje nije uspjelo, jer su znanstvenici također pretpostavljali da su teleskopi koje posjeduju dovoljno osjetljivi da otkriju paralaksu. To se ispostavilo netočnim. Sve do devetnaestog stoljeća znanstvenici nisu mogli otkriti zvjezdanu paralaksu.
So, there's a third problem as well. The third problem is simply a factual problem, that a lot of science doesn't fit the textbook model. A lot of science isn't deductive at all, it's actually inductive. And by that we mean that scientists don't necessarily start with theories and hypotheses, often they just start with observations of stuff going on in the world. And the most famous example of that is one of the most famous scientists who ever lived, Charles Darwin. When Darwin went out as a young man on the voyage of the Beagle, he didn't have a hypothesis, he didn't have a theory. He just knew that he wanted to have a career as a scientist and he started to collect data. Mainly he knew that he hated medicine because the sight of blood made him sick so he had to have an alternative career path. So he started collecting data. And he collected many things, including his famous finches. When he collected these finches, he threw them in a bag and he had no idea what they meant. Many years later back in London, Darwin looked at his data again and began to develop an explanation, and that explanation was the theory of natural selection.
Stoga postoji i treći problem. Treći je problem činjenične prirode, mnogo toga u znanosti ne prati udžbenik. Većina toga u znanosti nije deduktivno, nego je induktivno. Pri tome mislim da znanstvenici ne moraju nužno započeti s teorijama i hipotezama, ponekad počinju s opažanjima stvari koje se događaju u svijetu. Slavan primjer za ovo je najpoznatiji znanstvenik ikad, Charles Darwin. Kada je Darwin kao mladić otišao na putovanje brodom Beagle, nije imao hipotezu niti teoriju. Znao je samo da želi imati karijeru znanstvenika pa je počeo prikupljati podatke. Znao je da mrzi medicinu jer mu je bilo mučno pri pogledu na krv zato je trebao alternativnu karijeru. Počeo je prikupljati podatke. Prikupio je mnogo toga uključujući i poznate zebe. Nakon što ih je prikupio stavio ih je u vreću bez ideje što bi one mogle značiti. Nekoliko godina kasnije u Londonu Darwin je pregledao podatke ispočetka i razvio objašnjenje, a to objašnjenje bila je teorija prirodne selekcije.
Besides inductive science, scientists also often participate in modeling. One of the things scientists want to do in life is to explain the causes of things. And how do we do that? Well, one way you can do it is to build a model that tests an idea.
Osim induktivne znanosti, znanstvenici se često koriste modeliranjem. Jedna od stvari koje znanstvenici žele raditi u životu je objasniti uzroke stvari. A kako to učiniti? Jedan je način izgraditi model za testiranje ideje.
So this is a picture of Henry Cadell, who was a Scottish geologist in the 19th century. You can tell he's Scottish because he's wearing a deerstalker cap and Wellington boots. (Laughter) And Cadell wanted to answer the question, how are mountains formed? And one of the things he had observed is that if you look at mountains like the Appalachians, you often find that the rocks in them are folded, and they're folded in a particular way, which suggested to him that they were actually being compressed from the side. And this idea would later play a major role in discussions of continental drift. So he built this model, this crazy contraption with levers and wood, and here's his wheelbarrow, buckets, a big sledgehammer. I don't know why he's got the Wellington boots. Maybe it's going to rain. And he created this physical model in order to demonstrate that you could, in fact, create patterns in rocks, or at least, in this case, in mud, that looked a lot like mountains if you compressed them from the side. So it was an argument about the cause of mountains.
Ovo je slika Henryja Cadella škotskog geologa iz 19. stoljeća. Vidi se da je Škot jer nosi lovačku kapu i gumene čizme. (Smijeh) Cadell je htio odgovoriti na pitanje kako nastaju planine? Jedna od stvari koje je uočio jest da ako pogledamo planinu kao što je Apalačko gorje često se mogu pronaći stijene koje su oblikovane na određen način što je predlagalo da su zapravo bile komprimirane sa strane. Ova ideja kasnije je imala veliku ulogu u raspravi o pomicanju kontinenata. On je sagradio model, ludi izum s polugama i drvima, a evo i njegovih kolica, kanti i velikog čekića. Ne znam zašto nosi gumene čizme. Možda će padati kiša. Stvorio je fizički model kako bi pokazao da možemo napraviti obrasce u stijenama ili kao u ovom slucaju u blatu, koji su izgledali kao planine ako ih komprimiramo sa strane. To je bio dokaz o oblikovanju planina.
Nowadays, most scientists prefer to work inside, so they don't build physical models so much as to make computer simulations. But a computer simulation is a kind of a model. It's a model that's made with mathematics, and like the physical models of the 19th century, it's very important for thinking about causes. So one of the big questions to do with climate change, we have tremendous amounts of evidence that the Earth is warming up. This slide here, the black line shows the measurements that scientists have taken for the last 150 years showing that the Earth's temperature has steadily increased, and you can see in particular that in the last 50 years there's been this dramatic increase of nearly one degree centigrade, or almost two degrees Fahrenheit.
Danas mnogi znanstvenici vole raditi u zatvorenom, pa ne grade stvarne modele nego računalne simulacije. Ali računalne simulacije donekle su modeli. Oni su izrađeni pomoću matematike, te kao i stvarni modeli iz devetnaestog stoljeća vrlo važni za razmišljanje o uzrocima. Jedno od velikih nepoznanica su klimatske promjene i imamo mnoštvo dokaza da se Zemlja zagrijava. Crna linija na slajdu pokazuje mjerenja koja su znanstvenici dobili u proteklih 150 godina a pokazuju da se temperatura Zemlje jednoliko povećava i možemo vidjeti da u posljednjih 50 godina postoji dramatični porast od gotovo jednog Celzijevog stupnja, ili skoro dva stupnja po Farenheitu.
So what, though, is driving that change? How can we know what's causing the observed warming? Well, scientists can model it using a computer simulation. So this diagram illustrates a computer simulation that has looked at all the different factors that we know can influence the Earth's climate, so sulfate particles from air pollution, volcanic dust from volcanic eruptions, changes in solar radiation, and, of course, greenhouse gases. And they asked the question, what set of variables put into a model will reproduce what we actually see in real life? So here is the real life in black. Here's the model in this light gray, and the answer is a model that includes, it's the answer E on that SAT, all of the above. The only way you can reproduce the observed temperature measurements is with all of these things put together, including greenhouse gases, and in particular you can see that the increase in greenhouse gases tracks this very dramatic increase in temperature over the last 50 years. And so this is why climate scientists say it's not just that we know that climate change is happening, we know that greenhouse gases are a major part of the reason why.
Što pokreće tu promjenu? Kako možemo znati što uzrokuje primjetno zatopljenje? Znanstvenici ovo mogu prikazati pomoću računalne simulacije. Dijagram prikazuje računalnu simulaciju koja uzima u obzir različite faktore za koje znamo da utječu na klimu na Zemlji, kao što su sulfati iz onečišćenog zraka, vulkanska prašina od vulkanskih erupcija, promjene u Sunčevu zračenju, i staklenički plinovi. Postavilo se pitanje koje će raspon varijabli stavljen u mdoel prikazati ono što vidimo u stvarnom životu? Ovdje je stvarni život u crnoj boji. A ovdje u svjetlo sivoj boji, i odgovor je model koji uključuje je odgovor E na SAT-u, sve navedeno. Jedini je način na koji možemo prikazati dobivena temperaturna mjerenja ako promatramo zajedno sve navedeno, uključujući i stakleničke plinove, pa možemo vidjeti da porast stakleničkih plinova prati dramatični porast temperature u posljednjih 50 godina. Zato klimatolozi tvrde da nije samo da znamo da se klimatske promjene događaju, već su staklenički plinovi uveliko razlog za ova zbivanja.
So now because there all these different things that scientists do, the philosopher Paul Feyerabend famously said, "The only principle in science that doesn't inhibit progress is: anything goes." Now this quotation has often been taken out of context, because Feyerabend was not actually saying that in science anything goes. What he was saying was, actually the full quotation is, "If you press me to say what is the method of science, I would have to say: anything goes." What he was trying to say is that scientists do a lot of different things. Scientists are creative.
Budući da postoje različite stvari kojima se znanstvenici bave, filozof Paul Feyerabend je rekao: „Jedino načelo u znanosti koje ne koči napredak je: Sve je dopušteno.“ Ovaj je citat često bio uzet iz konteksta jer Feyerabend nije želio reći da je u znanosti sve dopušteno. Želio je zapravo reći, cijeli citat ide ovako: „Ako me natjerate da kažem koja je znanstvena metoda ja bih rekao: sve je dopušteno.““ Želio je reći Da znanstvenici rade različite stvari. Znanstvenici su kreativni.
But then this pushes the question back: If scientists don't use a single method, then how do they decide what's right and what's wrong? And who judges? And the answer is, scientists judge, and they judge by judging evidence. Scientists collect evidence in many different ways, but however they collect it, they have to subject it to scrutiny. And this led the sociologist Robert Merton to focus on this question of how scientists scrutinize data and evidence, and he said they do it in a way he called "organized skepticism." And by that he meant it's organized because they do it collectively, they do it as a group, and skepticism, because they do it from a position of distrust. That is to say, the burden of proof is on the person with a novel claim. And in this sense, science is intrinsically conservative. It's quite hard to persuade the scientific community to say, "Yes, we know something, this is true." So despite the popularity of the concept of paradigm shifts, what we find is that actually, really major changes in scientific thinking are relatively rare in the history of science.
Ovo povlači za sobom pitanje: Ako znanstvenici ne koriste jedinstvenu metodu kako onda odlučuju Što je točno, a što ne? Tko odlučuje? Odgovor je, znanstvenici odlučuju na temelju procjene dokaza. Znanstvenici prikupljaju dokaze na različite načine, ali kako god ih prikupili, podvrgavaju ih temeljitom ispitivanju. Ovo je navelo sociologa Roberta Mertona da se usredotoči na pitanje kako znanstvenici ispituju podatke i dokaze a to rade na način koji se zove „organizirani skepticizam“. Smatrao je to organiziranim jer znanstvenici to rade zajedno kao grupa i skeptično, jer tome pristupaju s nepovjerenjem. To znači da je težina dokaza na osobi s novim tvrdnjama. U tom smislu je znanost u suštini konzervativna. Teško je uvjeriti znanstvenu zajednicu da kaže: „Da, znamo nešto i to je istinito.“ Unatoč popularnosti koncepta o radikalnim promjenama mišljenja ipak uočavamo da su vrlo velike promjene u znanstvenom mišljenju relativno rijetke u povijesti znanosti.
So finally that brings us to one more idea: If scientists judge evidence collectively, this has led historians to focus on the question of consensus, and to say that at the end of the day, what science is, what scientific knowledge is, is the consensus of the scientific experts who through this process of organized scrutiny, collective scrutiny, have judged the evidence and come to a conclusion about it, either yea or nay.
To nas u konačnici vodi do sljedećeg: Ako znanstvenici kolektivno prosuđuju dokaze, to dovodi povjesničare na pitanje postojanja konsenzusa, a na kraju i tvrdnje da je znanost, i znanstvena spoznaja jednoglasna odluka znanstvenih stručnjaka, koji kroz proces temeljitog proučavanja, zajedničkog promatranja, procjenjuju dokaze i dolaze do zaključka o tome je li nešto jest ili nije.
So we can think of scientific knowledge as a consensus of experts. We can also think of science as being a kind of a jury, except it's a very special kind of jury. It's not a jury of your peers, it's a jury of geeks. It's a jury of men and women with Ph.D.s, and unlike a conventional jury, which has only two choices, guilty or not guilty, the scientific jury actually has a number of choices. Scientists can say yes, something's true. Scientists can say no, it's false. Or, they can say, well it might be true but we need to work more and collect more evidence. Or, they can say it might be true, but we don't know how to answer the question and we're going to put it aside and maybe we'll come back to it later. That's what scientists call "intractable."
Stoga znanstveno mišljenje možemo shvatiti kao jednoglasnu odluku stručnjaka. Također možemo promatrati znanost kao neku vrstu porote, osim sto je to posebna vrsta porote. To nije porota vaših vršnjaka, nego porota štrebera. Porota muškaraca i žena s doktoratom, i za razliku od uobičajene porote, koja ima samo dva izbora kriv ili nije kriv, znanstvena porota ima brojne izbore. Znanstvenici mogu reći da je nešto istinito. Ili mogu reći da je to neistinito. Ili da je to možda istinito Ali potrebno je još posla i prikupiti više dokaza. I mogu reći da je nešto možda istinito, ali se ne zna odgovor na pitanje pa će se ostaviti sa strane i vratiti se tomu kasnije. Za to znanstvenici kažu da je beskompromisno.
But this leads us to one final problem: If science is what scientists say it is, then isn't that just an appeal to authority? And weren't we all taught in school that the appeal to authority is a logical fallacy? Well, here's the paradox of modern science, the paradox of the conclusion I think historians and philosophers and sociologists have come to, that actually science is the appeal to authority, but it's not the authority of the individual, no matter how smart that individual is, like Plato or Socrates or Einstein. It's the authority of the collective community. You can think of it is a kind of wisdom of the crowd, but a very special kind of crowd. Science does appeal to authority, but it's not based on any individual, no matter how smart that individual may be. It's based on the collective wisdom, the collective knowledge, the collective work, of all of the scientists who have worked on a particular problem. Scientists have a kind of culture of collective distrust, this "show me" culture, illustrated by this nice woman here showing her colleagues her evidence. Of course, these people don't really look like scientists, because they're much too happy. (Laughter)
Ovo nas vodi do zadnjeg problema: Ako je znanost ono što znanstvenici kažu da je, nije li to onda poziv na autoritet? Nisu li nas u školi učili da je poziv na autoritet logična pogreška? Ovdje stoji paradoks moderne znanosti, paradoks zaključka do kojeg su došli povjesničari,filozofi i sociolozi, da je znanost pozivanje na autoritet, ali ne autoritet pojedinca bez obzira koliko pametan bio Kao Platon, Sokrat ili Einstein. Ona je autoritet cijele zajednice. Zamislite to kao neku vrstu mudrosti gomile, ali vrlo posebne gomile. Znanost se poziva na autoritet ali se ne temelji na pojedincu bez obzira koliko on bio pametan. Temelji se na zajedničkoj mudrosti kolektivnom znanju i radu svih znanstvenika koji su radili na određenom problemu. Znanstvenici imaju neku vrstu kolektivnog nepovjerenja, "pokaži mi" kulturu, prikazana ovom ženom koja pokazuje kolegama svoje dokaze. Ovi ljudi, naravno, ne izgledaju kao znanstvenici Jer izgledaju previše sretno. (Smijeh)
Okay, so that brings me to my final point. Most of us get up in the morning. Most of us trust our cars. Well, see, now I'm thinking, I'm in Manhattan, this is a bad analogy, but most Americans who don't live in Manhattan get up in the morning and get in their cars and turn on that ignition, and their cars work, and they work incredibly well. The modern automobile hardly ever breaks down.
Ovo me vodi do konačnog zaključka. Mnogi od nas ustaju ujutro. Vjeruju svojim autima. Kad razmislimo o tome, ja sam s Manhattana, ovo je loša analogija, ali mnogi Amerikanci koji nisu s Manhattana ustaju ujutro i ulaze u auto upale auto i on radi Nevjerojatno dobro. Moderni se automobili rijetko kada pokvare
So why is that? Why do cars work so well? It's not because of the genius of Henry Ford or Karl Benz or even Elon Musk. It's because the modern automobile is the product of more than 100 years of work by hundreds and thousands and tens of thousands of people. The modern automobile is the product of the collected work and wisdom and experience of every man and woman who has ever worked on a car, and the reliability of the technology is the result of that accumulated effort. We benefit not just from the genius of Benz and Ford and Musk but from the collective intelligence and hard work of all of the people who have worked on the modern car. And the same is true of science, only science is even older. Our basis for trust in science is actually the same as our basis in trust in technology, and the same as our basis for trust in anything, namely, experience.
Zašto je to tako? Zašto auti rade tako dobro? To nije zbog genijalnosti Henryja Forda Karla Benza ili Elona Muska. Nago zato što su moderni automobili proizvod više od sto godina rada stotina i tisuća pa i desetaka tisuća ljudi. Moderni je automobil proizvod zajedničkog rada, znanja i iskustva svakog muškarca i žene koji je ikad radio na autu, a pouzdanost tehnologije rezultat je zajedničkog truda. Ne profitiramo samo od genijalnosti Benza Forda i Muska, nego i zajedničke inteligencije i teškog rada svih ljudi koji su ikad radili na modernom autu. Isto vrijedi i za znanost, samo što je puno starija. Temelj povjerenja u znanost kao i temelj povejerenja u tehnologiju, ali i temelj vjerovanja svemu ostalome je iskustvo.
But it shouldn't be blind trust any more than we would have blind trust in anything. Our trust in science, like science itself, should be based on evidence, and that means that scientists have to become better communicators. They have to explain to us not just what they know but how they know it, and it means that we have to become better listeners.
To ne bi trebalo biti slijepo vjerovanje kao ni slijepo vjerovanje u bilo što Povjerenje u znanost kao znanost po sebi trebalo bi biti utemeljeno na dokazu a to znači da bi znanstvenici trebali postati bolji komunikatori. Trebali bi objašnjavati ne samo ono što znaju nego i kako to znaju što znači da mi trebamo postati bolji slušatelji.
Thank you very much.
Hvala lijepa.
(Applause)
(Pljesak)