In the coming years, artificial intelligence is probably going to change your life, and likely the entire world. But people have a hard time agreeing on exactly how. The following are excerpts from a World Economic Forum interview where renowned computer science professor and AI expert Stuart Russell helps separate the sense from the nonsense.
U godinama koje slede, veštačka inteligencija će vam verovatno promeniti život, a sasvim izvesno i čitav svet. Međutim, ljudi se baš i ne slažu tačno na koji način. Slede isečci iz intervjua sa Svetskog ekonomskog foruma u kojima cenjeni profesor računarske nauke i ekspert za VI Stjuart Rasel pomaže da odvojimo smisao od besmislica.
There’s a big difference between asking a human to do something and giving that as the objective to an AI system. When you ask a human to get you a cup of coffee, you don’t mean this should be their life’s mission, and nothing else in the universe matters. Even if they have to kill everybody else in Starbucks to get you the coffee before it closes— they should do that. No, that’s not what you mean. All the other things that we mutually care about, they should factor into your behavior as well.
Velika je razlika između traženja od ljudskog bića da uradi nešto i navođenja istog cilja sistemu VI. Kada tražite od ljudskog bića da vam donese šolju kafe, ne smatrate da bi to trebalo da bude njihova životna misija i da je samo to bitno u univerzumu. Čak i ako moraju da ubiju svakoga u kafeu da vam donesu kafu pre zatvaranja - trebalo bi to da urade. Ne, ne mislite tako. Sve ostalo do čega nam je međusobno stalo trebalo bi takođe da utiče na vaše ponašanje.
And the problem with the way we build AI systems now is we give them a fixed objective. The algorithms require us to specify everything in the objective. And if you say, can we fix the acidification of the oceans? Yeah, you could have a catalytic reaction that does that extremely efficiently, but it consumes a quarter of the oxygen in the atmosphere, which would apparently cause us to die fairly slowly and unpleasantly over the course of several hours.
A problem s tim kako trenutno gradimo sisteme VI je to što im dajemo fiksiran cilj. Algoritmi od nas zahtevaju da sve definišemo u cilju. A ako kažete, možemo li da popravimo zakiseljavanje okeana? Da, možete da imate katalitičku reakciju koja to izuzetno uspešno postiže, ali bi potrošila četvrtinu kiseonika u atmosferi, zbog čega bismo očito umirali krajnje sporo i neprijatno tokom nekoliko sati.
So, how do we avoid this problem? You might say, okay, well, just be more careful about specifying the objective— don’t forget the atmospheric oxygen. And then, of course, some side effect of the reaction in the ocean poisons all the fish. Okay, well I meant don’t kill the fish either. And then, well, what about the seaweed? Don’t do anything that’s going to cause all the seaweed to die. And on and on and on.
Dakle, kako da izbegnemo ovaj problem? Mogli biste reći, u redu, samo budite pažljiviji kod definisanja cilja - ne zaboravite atmosferski kiseonik. A onda, naravno, neka nuspojava reakcije u okeanu potruje svu ribu. U redu, mislio sam nemoj ni ribu da ubiješ. A onda, dakle, šta je sa morskom travom? Nemoj da uradiš ništa što bi uzrokovalo izumiranje morske trave. I tako dalje, i tako dalje.
And the reason that we don’t have to do that with humans is that humans often know that they don’t know all the things that we care about. If you ask a human to get you a cup of coffee, and you happen to be in the Hotel George Sand in Paris, where the coffee is 13 euros a cup, it’s entirely reasonable to come back and say, well, it’s 13 euros, are you sure you want it, or I could go next door and get one? And it’s a perfectly normal thing for a person to do. To ask, I’m going to repaint your house— is it okay if I take off the drainpipes and then put them back? We don't think of this as a terribly sophisticated capability, but AI systems don’t have it because the way we build them now, they have to know the full objective. If we build systems that know that they don’t know what the objective is, then they start to exhibit these behaviors, like asking permission before getting rid of all the oxygen in the atmosphere.
A razlog zašto ne moramo to da radimo s ljudima je što ljudi često znaju da ne znaju sve stvari do kojih nam je stalo. Ako zatražite od ljudskog bića da vam donese šolju kafe, a nalazite se u hotelu Žorž Sand u Parizu gde šolja kafe košta 13 evra, sasvim je razumno da se vratite i kažete: „Košta 13 evra, jesi li siguran da je želiš ili da je kupim u susednoj radnji?” I to je sasvim normalno za nekoga da uradi. Da pita: „Prekrečiću ti kuću - je li u redu da skinem oluke i da ih potom vratim?” Ovo ne smatramo naročito prefinjenom sposobnošću, ali sistemi VI je nemaju, jer zbog toga kako ih trenutno gradimo moraju u potpunosti da znaju cilj. Ako bismo gradili sisteme koji znaju da ne znaju šta je cilj, onda bi počeli da ispoljavaju ova ponašanja, poput traženja dozvole pre nego se reše celokupnog kiseonika u atmosferi.
In all these senses, control over the AI system comes from the machine’s uncertainty about what the true objective is. And it’s when you build machines that believe with certainty that they have the objective, that’s when you get this sort of psychopathic behavior. And I think we see the same thing in humans.
U svakom smislu, kontrola nad sistemom VI dolazi iz nesigurnosti mašine po pitanju njenog istinskog cilja. A kada gradite mašine koje veruju sa sigurnošću da imaju cilj, tada dobijate psihopatsko ponašanje. A smatram da isto to vidimo i kod ljudi.
What happens when general purpose AI hits the real economy? How do things change? Can we adapt? This is a very old point. Amazingly, Aristotle actually has a passage where he says, look, if we had fully automated weaving machines and plectrums that could pluck the lyre and produce music without any humans, then we wouldn’t need any workers.
Šta se desi kada veštačka opšta inteligencija stigne u realnu ekonomiju? Kako se stvari menjaju? Možemo li se prilagoditi? Radi se o izuzetno staroj poenti. Izvanredno je da Aristotel zapravo ima pasus gde kaže, vidite, kad bismo imali potpuno automatizovane razboje i trzalice koje bi mogle da trzaju liru i proizvode muziku bez ljudi, onda nam ne bi bili potrebni radnici.
That idea, which I think it was Keynes who called it technological unemployment in 1930, is very obvious to people. They think, yeah, of course, if the machine does the work, then I'm going to be unemployed.
Ta zamisao, koja mislim da je bila Kejnsova koji ju je 1930. godine nazvao tehnološkom nezaposlenošću je krajnje očita ljudima. Misle, da, naravno, ako mašina obavlja posao, onda ću biti nezaposlen.
You can think about the warehouses that companies are currently operating for e-commerce, they are half automated. The way it works is that an old warehouse— where you’ve got tons of stuff piled up all over the place and humans go and rummage around and then bring it back and send it off— there’s a robot who goes and gets the shelving unit that contains the thing that you need, but the human has to pick the object out of the bin or off the shelf, because that’s still too difficult. But, at the same time, would you make a robot that is accurate enough to be able to pick pretty much any object within a very wide variety of objects that you can buy? That would, at a stroke, eliminate 3 or 4 million jobs?
Setite se skladišta kojima trenutno upravljaju kompanije za e-trgovinu, ona su poluautomatizovana. Način na koji to funkcioniše je da stari magacin - gde imate tone stvari u hrpama svuda razbacane i ljudi dolaze i preturaju okolo i potom to donose i odašiljaju - postoji robot koji odlazi i uzima paletni regal u kom se nalazi stvar koja vam je potrebna, ali čovek mora da uzme predmet iz kontejnera ili sa police jer je to i dalje suviše komplikovano. Međutim, istovremeno, da li biste napravili robota koji je dovoljno precizan da može da odabere gotovo svaki predmet u širokom dijapazonu predmeta koje možete da kupite? Nešto što bi, jednim potezom, eliminisalo tri ili četiri miliona poslova?
There's an interesting story that E.M. Forster wrote, where everyone is entirely machine dependent. The story is really about the fact that if you hand over the management of your civilization to machines, you then lose the incentive to understand it yourself or to teach the next generation how to understand it. You can see “WALL-E” actually as a modern version, where everyone is enfeebled and infantilized by the machine, and that hasn’t been possible up to now.
Postoji zanimljiva priča koju je napisao E. M. Forster u kojoj je svako u potpunosti zavisan od mašina. Priča zaista govori o činjenici da ako predate upravljanje civilizacijom mašinama, gubite podsticaj da ih sami razumete ili da podučite narednu generaciju kako da ih razumeju. Možete posmatrati „Volija” zapravo kao savremenu verziju, gde su mašine svakoga oslabile i infantilizovale, a to nije bilo moguće sve do sad.
We put a lot of our civilization into books, but the books can’t run it for us. And so we always have to teach the next generation. If you work it out, it’s about a trillion person years of teaching and learning and an unbroken chain that goes back tens of thousands of generations. What happens if that chain breaks?
Veći deo naše civilizacije smo smestili u knjige, ali one ne mogu da upravljaju umesto nas. Stoga, uvek moramo da podučavamo sledeću generaciju. Ako to izračunate, radi se o oko bilion životnih dobi podučavanja i učenja i neprekidnom lancu koji ide unazad desetinama hiljada generacija. Šta se desi kada se lanac prekine?
I think that’s something we have to understand as AI moves forward. The actual date of arrival of general purpose AI— you’re not going to be able to pinpoint, it isn’t a single day. It’s also not the case that it’s all or nothing. The impact is going to be increasing. So with every advance in AI, it significantly expands the range of tasks.
Mislim da je to nešto što moramo da razumemo kako VI napreduje. Stvarni datum dolaska veštačke opšte inteligencije - ne biste mogli tačno da odredite, ne radi se o jednom danu. Takođe nije slučaj gde je sve ili ništa. Njen uticaj će da raste. Stoga sa svakim unapređenjem VI, ona značajno proširuje dijapazon zadataka.
So in that sense, I think most experts say by the end of the century, we’re very, very likely to have general purpose AI. The median is something around 2045. I'm a little more on the conservative side. I think the problem is harder than we think.
Te u tom smislu, smatram da većina stručnjaka kaže da do kraja veka, veoma, veoma je verovatno da ćemo imati veštačku opštu inteligenciju. Srednja vrednost je oko 2045. godine. Naginjem više ka konzervativnoj strani. Smatram da je problem teži nego što mislimo.
I like what John McAfee, he was one of the founders of AI, when he was asked this question, he said, somewhere between five and 500 years. And we're going to need, I think, several Einsteins to make it happen.
Sviđa mi se ono što je Džon Makafi, bio je jedan od osnivača VI, kada su ga upitali o ovome rekao, negde između pet i 500 godina. I biće nam potrebno, mislim, nekoliko Ajnštajna da to i ostvarimo.