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 se suočavamo sa problemima poput klimatskih promena ili bezbednosti vakcina gde moramo da odgovorimo na pitanja čiji odgovori su zasnovani na naučnim informacijama. Naučnici nam govore da se svet zagreva. Naučnici nam govore da su vakcine bezbedne. Kako da znamo da li su u pravu? Zašto da verujemo nauci? Zapravo, mnogi od nas ne veruju nauci. Istraživanja javnog mnjenja dosledno pokazuju da znatan deo Amerikanaca ne veruje da su klimatske promene izazvane čovekovim delovanjem, ne veruje u evoluciju putem prirodne selekcije, i nije uveren u bezbednost vakcina.
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 onda da verujemo nauci? Naučnici ne vole da govore o nauci kao o predmetu verovanja. Zapravo, suprotstavili bi nauku veri i rekli bi da verovanje pripada veri. A vera je jasno odvojena i drugačija od nauke. Rekli bi čak da je religija zasnovana na veri ili možda proračunu Paskalove opklade. Blez Paskal je bio matematičar iz 17. veka koji je pokušao da uvede naučno mišljenje u pitanje da li da veruje u boga ili ne i evo kako je išla njegova opklada: Ako bog ne postoji, a ja odlučim da verujem u njega, neću mnogo izgubiti. Možda nekoliko sati nedeljom. (Smeh) Ali ako on postoji, a ja ne verujem u njega, u velikom sam problemu. Tako je Paskal rekao da je bolje da verujemo u boga. Kako je rekao jedan od mojih profesora: "Posegnuo je za rukohvatom vere." Odlučio je da posegne za verom ostavljajući nauku i racionalizam za sobom.
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?
Međutim, činjenica je da, za većinu nas, naučna saznanja predstavljaju posezanje za verom. Uglavnom ne možemo sami da procenimo naučna saznanja. To je slučaj i sa većinom naučnika van njihovih uskih struka. Ako malo razmislite, geolog ne može da vam kaže da li je neka vakcina bezbedna. Većina hemičara nisu stručnjaci za teoriju evolucije. Fizičar ne može da vam kaže, šta god neki od njih govorili, da li duvan izaziva rak ili ne. Ako i sami naučnici moraju da imaju poverenja u ono što nije iz njihove oblasti, zašto prihvataju tvrdnje drugih naučnika? Zašto veruju u ono što drugi tvrde? I da li bi trebalo mi u to da verujemo?
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."
Ja smatram da bi trebalo u to da verujemo, ali ne zbog razloga na koji većina nas misli. Uglavnom su nas učili u školi da treba da verujemo u nauku zbog naučnog metoda. Učili su nas da naučnici prate određeni metod i da taj metod garantuje istinitost njihovih tvrdnji. Metod kome su nas uglavnom učili u školi, nazovimo ga udžbenički metod, jeste hipotetički deduktivni metod. Prema standardnom, udžbeničkom modelu, naučnici razvijaju hipoteze, dedukuju posledice tih hipoteza, pa odu u stvarni svet i kažu: "Jesu li te posledice tačne?" Možemo li ih uočiti u prirodi? Ako su tačne, naučnici kažu: "Super, znamo da je hipoteza tačna."
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.
Mnogo je poznatih primera u istoriji nauke gde naučnici upravo to i rade. Jedan od najpoznatijih primera vezan je za delo Alberta Ajnštajna. Kada je Ajnštajn razvio opštu teoriju relativnosti, jedna od posledica njegove teorije bila je da prostor-vreme nije samo praznina već da je sačinjeno od neke materije. Ta materija je iskrivljena u prisustvu ogromnih predmeta poput Sunca. Ako je ova teorija tačna, znači da svetlost kad prolazi pored Sunca treba da se iskrivi oko njega. Bila je to iznenađujuća pretpostavka i bilo je potrebno nekoliko godina da je naučnici ispitaju, ispitali su je 1919. i zapravo se ispostavila tačnom. Svetlost sa zvezda se zaista krivi dok putuje oko Sunca. Bila je to važna potvrda ove teorije. Smatrana je dokazom istinitosti te nove radikalne ideje i o tome se pisalo u novinama širom sveta.
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 model naziva deduktivno-nomološki model, uglavnom zato što naučnici vole da zakomplikuju stvari. Ali i zato što se u savršenim slučajevima radi o zakonima. Nomološki znači da je povezano sa zakonima. U savršenom slučaju hipoteza nije puka ideja: reč je o prirodnom zakonu. Zašto je važno da bude prirodni zakon? Zato što, ako je zakon, ne može biti prekršena. Ako je zakon, uvek će biti istinita, bilo kad i bilo gde, kakve god da su okolnosti. Svi znate bar jedan primer poznatog zakona: Ajnštajnova čuvena jednačina, E=MC2, koja objašnjava odnos između energije i mase. Taj odnos je uvek istinit.
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.
Međutim, postoji nekoliko problema sa ovim modelom. Glavni problem je to što je pogrešan. Prosto nije tačan. (Smeh) Govoriću o tri razloga zbog kojih je pogrešan. Prvi je logički razlog. To je problem logičke greške tvrđenja posledice. I to je moderan, naučnički način da kažemo da iz netačnih teorija mogu proisteći tačne pretpostavke. Ako se utvrdi da je pretpostavka tačna, zapravo nije logično dokazano da je teorija tačna. I za to imam dobar primer, ponovo iz istorije nauke. Ovo je slika ptolomejskog svemira sa Zemljom u središtu svemira i Suncem i planetama koji se okreću oko nje. U ptolomejski model su verovali mnogi veoma pametni ljudi vekovima. Zbog čega? Zato što su iz njega proizišle mnoge tačne pretpostavke. Zahvaljujući potlomejskom sistemu, astronomi su precizno predviđali kretanja planete, čak i tačnije u početku od Kopernikove teorije koju bismo sad prihvatili kao tačnu. To je jedan od problema udžbeničkog modela. Drugi je praktični problem, odnosno problem pomoćnih hipoteza. Pomoćne hipoteze su pretpostavke koje naučnici stvaraju, a toga možda i nisu svesni. Važan primer ovoga vezan je za Kopernikov model, koji je kasnije zamenio ptolomejski sistem. Nikola Kopernik je rekao da Zemlja zapravo nije središte svemira, Sunce je centar Sunčevog sistema, Zemlja se okreće oko Sunca. Naučnici su rekli da, ako je to tačno, trebalo bi da smo u stanju da primetimo kretanje Zemlje oko Sunca. Ovaj slajd ilustruje koncept poznat kao zvezdana paralaksa. Astronomi su rekli da, ako se Zemlja kreće i posmatramo sjajnu zvezdu, recimo, Sirijus - znam da sam na Menhetnu, tako da vi zvezde i ne vidite, ali zamislite da ste na selu, da ste izabrali ruralni život - ako pogledamo neku zvezdu u decembru videćemo u pozadini i udaljene zvezde. Ako to isto pogledamo za šest meseci, kad Zemlja dođe do ovog položaja u junu, videćemo istu zvezdu, ali sa drugačijom pozadinom. Ta razlika u uglu zove se zvezdana paralaksa. To je pretpostavka Kopernikovog modela. Astronomi su tražili zvezdanu paralaksu i nisu došli ni do čega. Mnogi su tvrdili da je to dokaz netačnosti Kopernikovog modela.
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.
Šta se onda dogodilo? Možemo da pretpostavimo da su astronomi pravili dve pomoćne hipoteze i za obe bismo sad rekli da su netačne. Prva je bila pretpostavka o veličini Zemljine orbite. Astronomi su pretpostavljali da je Zemljina orbita velika u odnosu na udaljenost od zvezda. Danas bismo pre nacrtali ovakvu sliku, ovu je uradila NASA i vidi se da je Zemljina orbita prilično mala. Zapravo je mnogo manja nego što je ovde prikazano. Stoga je zvezdana paralaksa veoma mala i jako ju je teško uočiti.
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 nas dovodi do drugog razloga zbog kog pretpostavka nije funkcionisala, a to je pretpostavka naučnika da su njihovi teleskopi dovoljno precizni da uoče paralaksu. Ispostavilo se da to nije tačno. Tek su u 19. veku naučnici mogli da uoče zvezdanu 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.
Postoji i treći problem. To je prosto činjenični problem, nauka se dobrim delom ne uklapa u udžbenički model. Nauka dobrim delom uopšte nije deduktivna, već je induktivna. To znači da naučnici ne polaze nužno od teorija i hipoteza, često polaze od opažanja događaja u svetu. Najpoznatiji primer za ovo jedan je od najvećih naučnika svih vremena, Čarls Darvin. Kada je Darvin kao mladić pošao na putovanje brodom Bigl, nije imao nikakvu hipotezu ili teoriju. Jedino je znao da želi da radi kao naučnik i počeo je da prikuplja podatke. Znao je uglavnom da mrzi medicinu jer mu je kad ugleda krv bilo toliko loše da je potražio drugo zanimanje. Tako je počeo da prikuplja podatke. Prikupio je mnogo toga, između ostalog i čuvene zebe. Kada je pronašao te zebe, ubacio ih je u vreću i nije ni pretpostavljao šta to znači. Mnogo godina kasnije u Londonu Darvin je ponovo analizirao svoje podatke i počeo da razvija objašnjenje, odnosno teoriju 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.
Pored induktivne nauke, naučnici se često bave stvaranjem modela. Jedan od životnih ciljeva naučnika jeste da objasne uzrok stvari. Kako se to radi? Recimo, tako što se napravi model koji ispituje određenu ideju.
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 Henrija Kadela, škotskog geologa iz 19. veka. Jasno je da je iz Škotske jer nosi avijatičarsku kapu i gumene čizme. (Smeh) Kadel je hteo da odgovori na pitanje kako nastaju planine. Jedno od njegovih opažanja je da, ako pogledate venac poput Apalačkih planina, često ćete uočiti da su stene u njima naborane, i to na poseban način, što mu je dalo ideju da su možda sabijane sa jedne na drugu stranu. Ta ideja je kasnije odigrala ključnu ulogu u raspravama o pomeranju kontinenanta. Napravio je jedan model, suludu skalameriju sa polugama i drvetom; evo baštenskih kolica, kanti, velikog malja. Ne znam zašto je u gumenim čizmama. Možda samo što nije počela kiša. Napravio je ovaj fizički model da bi pokazao da se zaista mogu stvoriti šare u kamenu, ili u ovom slučaju u blatu, i da podsećaju na planine ako se sabijaju sa obe strane. Bio je to dokaz o poreklu 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 naučnici radije rade unutra, tako da ne prave fizičke modele koliko kompjuterske simulacije. I to je neka vrsta modela. Pravi se pomoću matematike i, poput fizičkih modela iz 19. veka, veoma je bitan za izučavanje uzroka. Jedno od najvećih pitanja u vezi sa klimatskim promenama jeste ogromna količina dokaza da se Zemlja zagreva. Na ovom slajdu crna linija pokazuje merenja koja su naučnici obavili tokom poslednjih 150 godina i koja pokazuju da temperatura Zemlje stabilno raste, a posebno se vidi da je u poslednjih 50 godina došlo do naglog porasta od skoro jednog stepena Celzijusa ili blizu dva stepena Farenhajta.
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.
Ali šta je uzrok te promene? Kako da znamo šta izaziva uočeno zagrevanje? Naučnici mogu da naprave model pomoću kompjuterske simulacije. Ovaj dijagram ilustruje kompjutersku simulaciju koja je izučavala sve one faktore za koje znamo da mogu da utiču na klimu Zemlje, čestice sulfata iz zagađenog vazduha, vulkansku prašinu iz vulkanskih erupcija, promene u Sunčevom zračenju i gasove sa efektom staklene bašte. Postavili su sledeće pitanje: koji će skup promenljivih unetih u određeni model reprodukovati ono što vidimo u stvarnosti? Stvarnost je prikazana crnom bojom. Model je prikazan svetlosivom, a odgovor je model koji uključuje, kao odgovor pod E na prijemnom, sve gore navedeno. Jedini način da reprodukujete zabeležena temperaturna merenja je sa svim ovim stvarima zajedno, uključujući emisije gasova sa efektom staklene bašte, i prevashodno možete videti da rast gasova sa efektom staklene bašte prati vrlo dramatičan rast temperature u proteklih 50 godina. I zbog toga klimatolozi kažu "ne samo da znamo da se klimatska promena dešava, znamo da su gasovi sa efektom staklene bašte veliki deo uzroka."
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.
Zato zbog svih tih različitih stvari koje naučnici rade, filozof Pol Fajerabend je rekao čuvenu: "Jedini princip u nauci koji ne sputava napredak je: Sve može da prođe." Ovaj citat je često vađen iz konteksta, jer Fajerabend nije zapravo rekao da u nauci sve može da prođe. Ono što je govorio je, zapravo pun citat je: "Ako me pritisnete da kažem koji je naučni metod, morao bih reći: Sve može da prođe." On je pokušao da kaže da naučnici rade mnogo različitih stvari. Naučnici 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.
Ako onda to preokreće pitanje: ako naučnici ne koriste samo jedan metod, kako onda odluče šta je neispravno, a šta nije? I ko će da presudi? I odgovor je, naučnici presuđuju, i sude prema dokazima. Naučnici skupljaju dokaze na mnogo različitih načina, ali kako god da ih skupe, moraju da ih stave pod lupu. I ovo je navelo sociologa Roberta Mertona da se fokusira na to pitanje kako naučnici posmatraju podatke i dokaze, i rekao je da oni to rade na način koji je nazvao "organizovani skepticizam." Time je mislio da je organizovan jer to rade kolektivno, rade kao grupa, i skepticizam, jer to rade sa pozicije nepoverenja. Drugačije rečeno, teret dokazivanja je na osobi sa novom tvrdnjom. I u ovom smislu nauka je suštinski konzervativna. Veoma je teško ubediti naučnu zajednicu da kaže: "Da, mi znamo nešto, ovo je tačno." Zato uprkos popularnosti koncepta promena paradigme, ono što nalazimo je da su zapravo, veoma velike promene u naučnom razmišljanju relativno retke u istoriji nauke.
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 najzad dovodi do još jedne ideje: Ako naučnici kolektivno prosuđuju dokaz, ovo je navelo istoričare da se fokusiraju na pitanje konsenzusa, i da kažu da na kraju dana, ono što je nauka, ono što je naučno znanje, je konsenzus naučnih stručnjaka koji su kroz ovaj proces ogranizovanog posmatranja, kolektivnog posmatranja, presudili dokaze i došli do zaključka, bilo za ili protiv.
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."
Zato možemo razmišljati o naučničkom znanju kao o konsenzusu stručnjaka. Možemo razmišljati o nauci kao o nekoj vrsti porote, s tim da je veoma posebna vrsta porote. To nije porota vama jednakih, to je porota štrebera. To je porota muškaraca i žena sa doktoratima, i za razliku od konvencionalne porote, koja ima samo dve opcije, kriv i nije kriv, naučnička porota zapravo ima mnoštvo opcija. Naučnici mogu reći da, nešto je istinito. Naučnici mogu reći ne, to je neistinito. Ili, mogu reći, pa to bi moglo biti istina ali moramo još raditi i prikupiti još dokaza. Ili, mogu reći da bi moglo biti istina, ali ne znamo kako da odgovorimo na pitanje i odložićemo ga i možda ćemo vratiti na sto kasnije. To je ono što naučnici nazivaju zavrzlamom.
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)
Ali ovo dovodi do finalnog problema: ako je nauka ono što naučnici kažu da je, zar nije to onda samo poziv na autoritet? I zar nismo svi učeni u školi da je pozivanje na autoritet logička greška? Pa, eto ga paradoks moderne nauke, paradoks zaključka do kojeg mislim da su istoričari i filozofi i sociolozi došli, da je nauka zapravo poziv na autoritet, ali nije poziv na autoritet individue, bez obzira koliko je pametna ta individua, poput Platona ili Sokrata ili Ajnštajna. To je autoritet kolektivne zajednice. Možete razmišljati o ovome kao o mudrosti rulje, ali vrlo posebne rulje. Nauka se zaista poziva na autoritet, ali on nije zasnovan na bilo kom pojedincu, bez obzira na to koliko je ta osoba pametna. Zasnovan je na kolektivnoj mudrosti, kolektivnom znanju, kolektivnom radu, svih naučnika koji su radili na konkretnom problemu. Naučnici imaju neku vrstu kulture kolektivnog nepoverenja, tu kulturu "pokaži mi", ilustrovanu ovom finom ženom koja izlaže kolegama svoje dokaze. Naravno, ovi ljudi baš i ne izgledaju kao naučnici, jer su suviše veseli. (Smeh)
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.
OK, ovo me dovodi do moje konačne poente. Većina nas ustaje ujutru. Većina nas veruje svojim automobilima. Vidite, setila sam se da sam na Menhetnu, ovo je loša analogija, ali većina Amerikanaca koji ne žive na Menhetnu ustaju ujutru i sedaju u svoja kola upale auto, i njihova kola rade, i to rade zapanjujuće dobro. Moderni automobil se skoro nikad ne kvari.
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 automobili rade tako dobro? To nije zbog genija Henri Forda ili Karla Benca ili čak Elona Maska. To je zato što je moderni automobil proizvod preko 100 godina rada stotina i hiljada i desetina hiljada ljudi. Moderni automobil je proizvod kolektivnog rada i mudrosti i iskustva svakog čoveka i žene koji su ikada radili na automobilu, i pouzdanost tehnologije je posledica akumuliranog truda. Imamo korist ne samo od genija Benca i Forda i Maska, već i od kolektivne inteligencije i vrednog rada svih ljudi koji su radili na modernom automobilu. Isto važi i za nauku, samo što je nauka još starija. Osnova našeg poverenja u nauku je zapravo ista kao i osnova našeg poverenja u tehnologiju, i ista kao i osnova našeg poverenja u bilo šta, kao na primer, 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.
Ali to ne treba biti slepo poverenje ništa više nego što bismo imali slepo poverenje u bilo šta. Naše poverenje u nauku, kao i sama nauka, treba biti zasnovano na dokazima, i to znači da naučnici moraju postati bolji komunikatori. Moraju nam objasniti ne samo šta znaju već i kako su to saznali, i to znači da moramo postati bolji slušaoci.
Thank you very much.
Hvala vam mnogo.
(Applause)
(Aplauz)