Transcript for Judea Pearl: Causal Reasoning, Counterfactuals, Bayesian Networks, and the Path to AGI

Oh, the first mystery. That's a good one. Yeah, I remember that. I had the fever for three days when I learned about the carton and a little geometry. And I find out that you can do all the construction in geometry using algebra. And I couldn't get over it. I simply couldn't get out of bed.

Well, it connects algebra with the geometry. okay so the cut had the idea that geometrical construction and geometrical theorems and assumptions can be articulated in the language of algebra which means All the proof that we did in high school, trying to prove that the three by sectors meet at one point and that, okay, all these can be proven by just shuffling around notation. Yeah, that was the connection.

Both are beautiful, they have almost the same power. But there's a visual element, a geometry being of visual, it's more transparent. But once you get over to algebra, then the linear equation is a straight line, this translation is easily absorbed. And to pass a tangent to a circle, you have the basic theorems and you can do it with algebra. But the transition from one to another was really, I thought that the curve was the greatest mathematician of all times.

It's a little bit. I mean, we got a very solid background in mathematics because our tissues were geniuses. Our tissues came from Germany in the 1930s running away from Hitler. They left their careers in Heidelberg and Berlin and came to teach high school in Israel. And we were the beneficiary of that experiment. And they taught us math a good way.

the people, the people behind the axioms, their cousins and their nieces and their faces. And how they jump from the bathtub when they scream you rika and then naked in town.

No, we just got the glimpse of that history together with the theorem. So every exercise in math was connected with the person.

I get a BS and engineering and a technical one. And then I moved here for graduate work and I got engineering in addition to physics in radgales. And it combined very nicely with my thesis which I did and I'll see a lot about all these in superconductivity.

It's how to choose. No. I enjoy doing physics. I even have a vortex name on my name. So I have an investment in immortality.

Vortex is in superconductivity. And it's superconductivity. You have permanent comments, swirling around. One way or the other, you can have a store one or zero for computer. That was we worked on in the 1960s, I was EA. And I discovered a few nice phenomena with the Vortexes. It's pushed out of the room. How do they move vortex? It's the old vortex, right? You came to Google it. Right? I didn't know about it, but the physicist picked up on my thesis. on my PhD disease and it became popular. I mean, things for him to put conductors became important for high-temperature superconductors. So they call it parallel vortex without my knowledge. It has carried only about 15 years ago.

We know it is stochastic, right?

Yes. We think because we have the Heisenberg consultant, the principal, and we have some experiments to confirm that.

Why is your book? Yeah, it's a puzzle. It's a puzzle that you have the dice of flipping machine. Oh, God. And the result of the flipping propaganda with the speed faster, the speed of light. We can't explain it, okay? But it only governs microscopic phenomena.

No, the illusion, anyway.

The world is a deterministic and as far as the new one firing is concerned, it's a deterministic to feel the approximation.

Free will is also a nice exercise. Free will is a solution. We AI people are going to solve.

Once we put it in a place. It will look like a machine. A machine that acts as though it has free will. It communicates with other machines as though they have free will. And you wouldn't be able to tell the difference between a machine that doesn't have free will.

And faking it is having it. That's what tool and test is about. Faking intelligence is intelligent because it's not easy to fake. It's very hard to fake and you can only fake if you have it.

It's a degree of uncertainty that an agent has about the world.

Is it appropriate? Is 90% the end? It's absolutely different kind of knowledge and it is 10%.

It's still solid knowledge by if you tell me that 90% assurance is smoking will give you lung cancer in five years versus 10%. It's a piece of useful knowledge.

And now, to predict things with a certain probability and computing those probabilities are very useful. But the whole idea of prediction and you need prediction to be able to survive. If you cannot predict the future then you're just crossing the street will be extremely fearful.

I started with the probability.

Correlation occurs when two things vary together over a very long time. It's one we have measured and gave. Or when you have a bunch of variables that are very guisively, then we call it we have a correlation here. And usually, when we think about correlation, we really think causally. things and cannot be called unless there is a reason for them to vary together. Why should they vary together? If they don't see each other, why should they vary together?

Yes. Hidden in our intuition is a notion of causation because we cannot grasp any other logic except causation.

Conditional probability of how things vary when one of them stays the same. Now staying the same means that I have chosen to look only those incidents where the guy has the same value as previous one. It's my choice as an experimenter. So things that are not correlated before could become correlated. like, for instance, if I have two coins which are uncorrelated and I choose only those flipping experiments in which a bell rings and a bell rings when at least one of them is a tail. Then subtly I see correlation between the two coins because I only look at the cases where the bell ring See, it's my design, it's my ignorance, essentially, with my audacity to ignore certain incidents. I suddenly create a correlation where it doesn't exist physically.

I don't look at the flaws of world works like that. But the flaws come if we try to impose causal logic on correlation, it doesn't work too well.

It's a majority of naive science. The decisions now, if you condition on a third variable, you can destroy or create correlations among two other variables. They know it. It's in a data. It's nothing surprising. That's why they all dismiss a simple paradox. We know it. It's not anything.

Who is trying to get causation from correlation?

Which discipline you have in mind? I'll tell you if they are absolute. Is they are outdated or they are about to get outdated? Oh, yes. Tell me which one do you have?

It's okay, what is the SEM? Stock liquid?

Everything starts with the question.

do they follow sleep or do they tend to follow sleep more frequently more frequently and the car not driving it's not driving it's a good question okay and so you measure you put people in the car because it's real world you can't conduct an experiment where you control everything why can't you can you could turn the automatic module on and off

And then maybe determine often there will be a very trial.

Okay, so that you have now uncontrolled experience. We call it observational study. Yeah. And we form the correlation. detected that we have to infer causal relationship whether it was the automatic piece has caused them to fall asleep. So that is an issue that is about 120 years old. I should only go 100 years old. And oh, maybe it no, actually I should say it's 2000 years old because we have this experiment by Daniel, but the Babylonian king that wanted the exile, the people from Israel that were taken in exile to Babylon, to serve the king. He wanted to serve them King's fool, which was meet in Daniel as a good Jew, couldn't eat a non-cossure fool, so he asked them to eat vegetarian fool, but the King overseers said, I'm sorry, but if the King sees it, you know, performance, false below, date of other kids, now he is going to kill me. And then you say, let's make an experiment. Let's take four of us from Jerusalem, okay, give us the detailed food. Let's take the other guys to eat the King's food and about a week's time, we'll test our performance. And you know the answer, of course, he did experiment and they were so much better than the others. And the kings nominated them to super position in his case. So it was a first experiment. So there was a very simple, it's also the same research questions. We want to know a vegetarian food, assist or obstruct your mental ability. Okay, so the question is very old. Even the Mokritos said, if I could discover one cause of things, I would rather discover one cause and be a king of Persia. The task of discovering causes was in the mind of ancient people from many, many years ago. But the mathematics of doing this was only developed in the 1920s. So, science has left us often. Science has not provided us with a mathematics to capture the idea of x causes y and y does not cause x. Because all the equations of physics are symmetric algebraic, the equality sign goes both ways.

Beautiful. So, where did you say that? Conditional probability estimate? None of the machine learning people leveled you.

We start asking ourselves questions. What are the factors that would determine the value of X? X could be blood pressure, death, angry, anger,

I suppose this is everything which has to do with causality, comes from a theory. The difference is only, what kind, how you interrogate the theory that you have in your mind.

You need the human expert to specify the initial model. Initial model could be very qualitative. Just who listens to whom? By whom listen to I mean one variable listens to the other. So I say okay the tide is listening to the moon. and not to the rooster crawl. And so far, this is our understanding of the world in which we live, scientific understanding of reality. We have to start there because if we don't know how to handle cause an effect relationship, when we do have a model and we certainly do not know how to handle it, when we don't have a model. So let's start first in AI slogan is representation first, discovery second. But if I give you all the information that you need, can you do anything useful with it? That is the first representation. How do you represent it? I give you all the knowledge in the world. How do you represent it? When you represent it, I ask, can you infer x or y or z? Can you answer certain queries? Is it complex? Is it polynomial? It's all the computer science exercises. We do, once you give me a representation for my knowledge. Then you can ask me, now I understand how to represent things, how do I discover them? It's a second thing.

In certain areas, it's easy because we have only four or five major variables. and epidemiologists or economists can put them down, what the minimum wage, an unemployment policy, XYZ, and start collecting data and quantify the parameters that were left uncontified with the initial knowledge. Okay, that's the routine work that you find in experimental psychology, in economics, everywhere, in the health science, that's the routine things. But I should emphasize, you should start with the research question. What do you want to estimate? Once you have that, you have a language of expressing what you want to estimate. You think it's easy?

You're talking about the task of an existing knowledge from an expert.

It essentially is the same thing. You have to start with some knowledge and you're trying to enrich it. But you don't enrich it by asking for more rules. You enrich it by asking for the data, for to look at the data and quantifying and ask queries that you couldn't answer when you started. You couldn't because the question is quite complex, and it's not within the capability of ordinary cognition, of ordinary person, or ordinary expert even, to answer.

Even in simple terms, suppose we are, and start with easy one. What's the effect of drug on recovery? What did the aspirin that caused my headache to be cured or what did the television program or the good news I received? This is already a difficult question because it's find the cause from effect. The easy one is find the effects from cause.

I didn't construct a module. I just said it's important question. And the first exercise is express it mathematically. What do you want to do? Like, if I tell you what will be the effect of taking this drug, you have to say that in mathematics. How do you say that? Yes. Can you write down the question? Not the answer. I want to find the effect of the drug on my headache. Right, right down. Right, right, it does.

Do operator. What do you do?

Yeah.

Yeah. So we have a do operator. So do calculus connected on the do operator itself, connect the operation of doing to something that we can see.

Let's put it into the ethics process. And then the way that we interpreted the mechanism by which we take your query and we translate into something that we can work with is by giving it semantics, saying that you have a model of the world and you cut off all the incoming arrow into X. And you're looking now in the modified mutilated model, you ask for the probability of why. That is interpretation of doing X, because by doing things, you've liberated them from all influences that acted upon them earlier, and you subject them to the tyranny of your muscles.

So you're now, there's one level of questions. Yeah. Answered questions about what will happen if you do things.

Now the question is, if we cannot one experiments, right, then we have to rely on observational studies.

Who imagine how the experiment will look like, even though we cannot physically and technology conducted? I'll give you an example. What is the effect of blood pressure on mortality? I cannot go down into your vein and change your blood pressure, but I can ask the question. which means I can even have a model of your body. I can imagine the effect of how the blood pressure change will affect your mortality. How I go into the model and I conduct this surgery about the blood pressure even though physically I can do I cannot do it.

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No, but physically, yes. But hypothetically, no, hypothetically, no. If we have a model, that is what the model is for. So you conduct surgeries on a model, you take it apart, put it back, that's ideal for model. It's ideal of thinking come to factually imagining and that's ideal for creativity.

I construct the model. I can still not answer it. I have to see if I have enough information in the model that would allow me to find out the effects of intervention from a non-interventional study, from the end of study.

We need to have assumptions about who affect whom. If the graph had a certain property, the answer is yes, you can get it from observational study. If the graph is too machibushi-bushi, the answer is no, you cannot. Then you need to find either different kind of observation that you haven't considered or one experiment.

Correct. But you don't have to encode more than what you know. God forbid, if you put the like economists not doing that. They call identifying assumption. They put assumptions, even they don't prevail in the world. They put assumptions all they can identify things.

Because if you don't know, you say it's possible. It's possible that X affects the traffic tomorrow. When it's possible, you put down an error which says it's possible. Every error in the graph says it's possible.

The less likely you are to identify things from purely observational data. So if the whole world is bushy, And everybody affects everybody else. The answer is, you can answer it ahead of time. I cannot answer my query from observational data. I have to go to experiments.

But can the factual contains what we normally call explanations? Can you give an example if I tell you that acting one way, effects something, I didn't explain anything yet. But if I asked you, was it the aspirin that cure my headache? I'm asking for explanation, what cure my headache? And putting a finger on aspirin, provide explanation. It was aspirin. It was responsible for your headache going away. If you didn't take the aspirin, you would still have a headache.

but you have to have another important information. I took the aspirin and my headache is gone. It's very important information. Now I'm reasoning backward and I said, what did the aspirin?

That's right. So you know, that things took place, you know, Joe Kilschmore. Yeah. And Schmore would be alive. Had John not used his gun. Okay. So that is the counterfactual. It has a conflict here or clash between observed facts. He did shoot, okay? And the hypothetical predicate, which says, had he not shot. You have a clash, a logical clash. They cannot exist together. That's a counterfactual. And that is the source of our explanation of our idea of responsibility, regret, and free will.

Yes, and Philips is doing it all the time.

Physicists. Physicists. In every equation of physics, let's say you have a hook floor, and you put one kilogram on the spring, and the spring is one meter, and you say, had this weight been took kilogram, the spring would have been twice as long. It's no problem for physicists to say that. Except that mathematics is only in a form of equation. Equating the weight, proportionality constant, and the length of the string. So you don't have the asymmetry in the equation of physics, although every physicist thinks counterfactually. Ask the high school kids. Had the weight been 3 kilograms, what would be the length of this print? They can answer it immediately, because they do the counterfactual processing in their mind, and then they put it into equation, algebraic equation, and they solve it. But the robot cannot do that.

And why you just put learn? So what you tell him, can you do it? So before you go learning, you have to ask yourself, suppose I give more information. Can the robot perform a task that I ask him to perform? Can he recently say, no, it wasn't the aspirin. It was the good news you received on the phone.

Right, right.

But now we have to linger. We have to say, how do we, how do we do it? How do we build it?

Why don't you go to a learning right away? You have too much involved with learning.

Good. So yeah. That's another question. How do the babies come out with the counterfactor model of the world? And babies do that. They know how to play with the in the crib. They know which balls hits another one. And what they learn is by play for manipulation. of the world. Yes. There are simple worlds, involve only toys and balls and chimes and bears. But if you see it, it's a complex world.

And our kids do it by playful manipulation, plus parents' guidance, pure wisdom, and he'll say, They meet each other and they say, you shouldn't have taken my toy.

I don't know. I haven't experimented with the crib. Okay, not a crib picking up.

It's only complicated. I agree and I don't know how to organize it because I've been spoiled by easy problems such as cancer and death. I mean, first we have to start. No, but easy. The easy, the easy incentive you have only 20 variables. They are just very well done, not mechanics. It's easy. You just put them on the graph and they speak to you.

I'm working only in the abstract. The abstract was knowledge in, knowledge out, data in between.

I think it's a metal of combining simple models for many many sources, for many many disciplines. And many metaphors. metaphors are the basics of human intelligence and basis.

metaphors is an expert system. And it's mapping problem with which you are not familiar to a problem with which you are familiar. Like I've given a good example, the Greek believed that the sky is an opaque shell. It's not really an infinite space. It's an opaque shell and the stars are holes. Poked in the shells through which you see the eternal light. It was a metaphor why? Because they understand that you poke holes in the shells. They were not familiar with infinite space. And we are working on a share of a turtle. And if you get too close to the head, you're going to fall down to Hades. Oh, whatever. Yeah. And there's a metaphor. It's not true. But this kind of metaphor enables our estotonous to measure the radius of the earth. Because he said, come on. If we are walking on a turtle's shell, then a ray of light coming to this angle will be different. This place will be different angle that coming to this place. I know that distance, I'll measure the two angles. And then I have the radius of the shell of the turtle. And he did. And he found, Measurement of very close to the measurements we have today. So the year was 6,700 km. That's something that would not occur. to Babylonian astronomer, even though they are but belong in experiments where the machine learning people of the time. They fit curves and they could predict the clips of the moon much more accurately than the Greek because they fit curve. That's a different metaphor. Something you familiar with, a game, a total change. What does it mean? It's your familiar. Familiar means that answers to certain questions are explicit. You don't have to derive them.

You're familiar with the Chinese familiar with Billion Balls. So the child could predict that if you let loose one ball, that one will bounce off. You obtain that by familiarity. If a familiarity is answering questions and you store the answer explicitly, You don't have to derive them. So this is ideal for metaphor. All our life, all our intelligence is built around metaphors, mapping from the unfamiliar to the familiar. But the marriage between the two is a tough thing which we haven't yet been able to algorithmize.

It is reasoning by metaphor.

It is definitely a sense.

It's one of the most important learning, taking something which theoretically is durable and stored in accessible format. I'll give you an example, chess, okay? Finding the winning starting move in chess is hard. But it is an answer. either there is a winning move for white or there is a draw. So it is the answer to that is available to the rule of the game. But we don't know the answer. So what does the chess master have that we don't have? He has told explicitly an evaluation of certain complaints pattern of the board. We don't have it. Ordinary people like me, I don't know about you, I'm not the chess master. So for me, I have to derive things that for him is explicit. He has seen it before, or he has seen the pattern before, or similar pattern, he has seen it before. And he generalized and said, don't move with the dangerous move.

I don't know, I'm not in the future. I can tell you that we are making tremendous progress in the coastal reasoning domain. Something that I even there to call it evolution, the cultural evolution, because what we have achieved in the past three decades is something that the wolf, everything it was derived in the entire history.

First they're going to work without collisions. It's going to work in harmony. The human is going to jumpstart the exercise by providing qualitative non-committing models of how the universe works. How the reality the domain of discourse works. The machine is going to take over from that point of view and derive whatever the calculus says can be derived, namely quantitative answer to our questions. These are complex questions. I'll give you some example of complex questions that bugle your mind if you think about it. You take result of studies in diverse population under diverse conditions. And you infer the cause effect of a new population, which doesn't even resemble any of the ones studied. And you do that by do calculus. You do that by generalizing. from one study to another. See, what's common with Beethoven? What is different? Let's ignore the differences and pull out the commonality. And you do it over maybe 100 hospitals around the world. From there you can get really mileage from big data. It's not as you have many samples. You have many sources of data.

Not only temporal, it was structural and temporal, temporal enough, a temporal presence by itself cannot replace causation.

It's important. It's important. It's important. It's important. It's important. Yes. Is it? Yes, I never seen the cause of the propagate backbone.

Do calculus is logical relationship?

Yeah. Correct.

Yes.

Not about between not deriving the order of events. We are given cause of actualization ship. They ought to be obeying the time president's We are giving it. And now that we ask questions about other code of religion, that could be derived from the initial ones, but were not given to us explicitly. Like the case of the firing squad that gave you in the first chapter, and I ask, what if rifleman A declined to shoot? Who the prisoners still be dead? The decline to show that means that this obey order and the rule of the games were that he is obedient and marksman. That's how you start. That's the initial order. But now you ask question about breaking the rules. What if he decided not to pull the trigger? He just became a pacifist. And you and I can answer that. The other rifleman would have killed him. I want the machine to do that. It's so hard to ask the machine to do that. It's as simple as that. But you have to have a calculus for that. Yes.

We put a learning machine that watches execution trials in many countries and many Locations, okay? All the machine can learn is to see, shut or not shut. Dead, not dead. Code issued an order or didn't. Okay, that's facts. From the fact you don't know who listens to home. He don't know that they condemned person, listen to the bullets. The bullets are listening to the captain, okay? All we hear is one command two shots dead, okay? A triple of variable. Yes, no, yes, no. Okay, well, that you can learn who lists the home and you can answer the question?

You want machine to learn, right? You want a robot? So Robert is watching trials like that, 200 trials, and then he has to answer the question, what if rifleman A refrain from shooting? How do you do that? That's exactly my point. It's looking at the facts. Don't give you the strings behind the facts.

Play for manipulation.

What do you do?

Interventionist. It could be a random point since the rifleman is sick of the day or he just vomits or whatever. So he can observe his unexpected event which introduced noise. The noise still have to be a random to be able to and related to randomized experiment. And then you have a observational studies from which to infer the strings behind the facts. It's doable to certain extent. But now that we are expert in what you can do once you have a model, we can reason back and say, what kind of data you need to build a model.

Yeah, I'm driven by that. All my life, I'm driven just by one thing. But I go slowly, I go from what I know to the next step incrementally.

Do you imagine what the end goal is going to be a machine that can answer sophisticated questions, counterfactuals of regret, compassion, responsibility, and free will.

Free will doesn't exist yet.

That's so far we know only one thing. If Robots can communicate with reward and punishment, among themselves. He thinks each other on the wrist and so you shouldn't have done that. Playing better soccer because they can do that.

because they can communicate among themselves.

Because of the communicate, like us, reward and punishment. Yes, you didn't pass the ball the right time and so forth. Therefore, you're going to sit on the bench for the next two. If they start communicating like that, the question is will they play a bit or something? Is it possible? Is it possible they do now? Without this ability to reason about reward and punishment, responsibility. And in fact, I can only think about communication, communication is not necessarily natural language, but just communication. And that's important to have a quick and effective means of communicating knowledge. If the coach tells you you should have passed the ball, pink, he conveys so much knowledge to you as opposed to what? Go down and change your software. That's alternative. But the coach doesn't know your software. So how can the coach tell you you should have passed the ball? But the tech, our language is very effective. You should have passed the ball. You know your software, you tweak the right mode you'll, okay? And next time you don't do it.

No, not well defined. When you should pass the ball, it's not well defined. No, it's Very soft, very noisy.

Because the machine has to empathize. To understand what's good for you, to build a model of you as a recipient, which should be very much what is compassion. suffer pain as much as me. I do have already a model of myself, right? So it's very easy for me to map you to mine. I don't have to rebuild the model. It's much easier to say, oh, you're like me. Okay, therefore I would not hate you.

And moreover, who is me? That's the fact that that's consciousness. They have a model of yourself. Where do you get this model? You look at yourself as if you are a part of the environment. If you build a model of yourself versus the environment, then you can say, I need to have a model of myself. I have abilities, I have desires and so forth. I have a blueprint of myself. Not a full detail because I cannot get the whole thing problem, but I have a blueprint. So that's level of a blueprint. I can modify things. I can look at myself in the mirror and say, hmm, if I change this mode, tweak this model, I'm going to perform differently. That is what we mean by free will.

That's right. Some people tell me, no, this is only part of consciousness. And then they start telling me, what do you mean by God? And I lose them. For me, consciousness is having a blueprint of your software.

I'm concerned, because I know we are building a new species that has a capability of exceeding us. Exit the archer abilities and can breed itself and take over the world, absolutely. It's a new species, it's uncontrolled. We don't know the degree to which we control it, we don't even understand what it means to be able to control this new species. So I'm concerned. I don't have anything to add to that because it's such a great area that I'll never happen in history. The only time it happened in history was evolution with human being. It wasn't very successful. It was a great success.

We have a sample of one sample of one. It's us.

We have more than a sample of more. We have theories, theories, and that's a good idea. We don't need to be statisticians. So a sample of one doesn't mean poverty of knowledge. It's not. A sample of one plus theory, conjectural theory of what could happen. that we do have but I really feel helpless in contributing to this argument because I know so little and my imagination is limited and I know how much I don't know and but I'm concerned your born and raised in Israel born and raised in Israel

Yes, because I was in the Nachan, which is a combination of agricultural work and military service. I was really idealist. I wanted to be a member of the Kibbutra out my life and to live a communal life. And so I prepared myself for that. Slowly, slowly, I want the greater challenge.

But I learned from that what I can either. It was a miracle. It was a miracle that I served in the 1950s. I don't know how we survived. The country was under austerity. It tripples its population from 600,000 to a million point eight when I finished college. No one went hungry. austerity yes. When you wanted to buy to make an omelette in the restaurant, you had to bring your own eggs And they imprisoned people from bringing the food from the farming of the villages to the city. But no one would hangry. And I always add to it. And higher education did not suffer any budget cut. They still invested in me in my wife and our generation to get the best education that they could. So I'm really grateful for the opportunity and I'm trying to pay back now. It's a miracle that we survived the war of 1948. They were so close to a second genocide It was all in plant. But we survived it by miracle. And then the second miracle that not many people talk about. The next phase. How no one went angry in the country managed to triple its population. You know what? It means to triple the imagine United States. Going from what? 350 million? Two million. Yeah. That's unbelievable.

One of the components. Religion is a strong motivating course for many, many people in the Middle East.

That's a good question for robotics, you know? Should I call you that question? We provide with religious beliefs. Suppose we find out, when we agree that religion is good to you to keep you in a line. Should we give them about the metaphor of a guy? The metaphor of the robot will get it without us also. Why? The robot will reason by metaphor. And what is the most primitive metaphor? A child grows with Mother smile, father teaching, father image, and mother image. That's God. So, what do you want it or not? The robot with, but assuming the robot is going to have a mother and a father, it may only have a programmer, which doesn't supply warmth and discipline. What discipline it does, so it's all about to have a model of the trainer. Everything that happens in the world, cosmology and so it's going to be mapped into the program.

I really don't know. I think it did. But as long as you keep in mind, it's only metaphor.

Yes, yes.

So his name was abducted in Pakistan by Al-Qaeda driven sect and under various pretenses. I don't even pay attention to what the pretence will. Originally they wanted to have the United States deliver some promised airplanes. It was all made up, and all this demands were bogus. I don't know really, but eventually he was executed in front of a camera.

The coin is absolutely yes. We don't really appreciate the depth of the hate which which billions of people are educated. We don't understand it. I just listen to what they teach in Mogadishu. When the water stopped in the tap, We knew exactly who did it, the Jews, the Jews. We didn't know how, but we knew who did it. We don't appreciate what it means to us. The depth is unbelievable.

If you are indoctrinated sufficiently long and in-depth, you are capable of ISIS, you are capable of Nazism? Yes, we are. But the question is whether we have to, we have guns with some Western education and we learn that everything is really relative. There is no absolute God. He's only a belief in God. Whether we are capable of now, of being transformed on the certain circumstances to become brutal. That is where I'm worried about it, because some people say, yes, given the right circumstances, given a canonical crisis, you are capable of doing it too, and that's more is me. I want to believe it, I'm not capable.

I lost.

The message was that we are not treating terrorism as a taboo. We are tweeting it as a bargaining device that is accepted. People have grievance and they go and shen bomb restaurants. It's normal. Look, you're even not surprised when I tell you that. 20 years ago, it said, what? For grievance, you go and blow a restaurant. Today, it's becoming normalized. The banalization of evil. And we have created that to ourselves, by normalizing, by making it part of political life. It's a political debate. Every terrorist has to become the freedom fighter today and to more and become terrorist in the eightest switchable.

If we don't want to be part of it, become it. Yeah, if we want to separate good from evil, let's one of the first things that what was in the garden of Eden. Remember the first thing that God tells him, he wants some knowledge. He is a tree of good and evil.

I see some beautiful people coming from Pakistan. I see beautiful people everywhere. But I see horrible propagation of evil in this country to It shows you how populistic slogans can catch the mind of the best intellectuals.

I didn't know that.

Oh, many good memories. He was my mentor. He had sense of balance that I didn't have. He saw the beauty in every person. He was not as emotional as I am and more looking at things in perspective. He really liked every person. He really grew up with the idea that a foreigner is a reason for curiosity, not for fear. It's one time we went in Berkeley and homeless came out from some dark alley and said, hey man, can you spare a dime? I've reached back, you know, two feet back. And then it just hugged him and said, here's a dime in Joseph. Maybe he wants some money to take a bath or whatever. Where did he get it? Not for me.

Ask your questions. Really? Your questions are never dumb. And solve them your own way. and don't take no for an answer. If they are really dumb, you will find up quickly by trying an arrow to see that they are not leading any place. But follow them and try to understand things your way. That is my advice. I don't know if he's going to help anyone. Now that's brilliant. He's a lot of... It's an inertia in science, in academia. It is slowing down science.

Against your professor. It is, I wrote the book of why, in order to democratize common sense. Another to instill a rebellious spirit in students, so they wouldn't wait until the professor gets things right.

I already have a tombstone.

And the fundamental law of counterfactures. That's what it is. It's a simple equation. what it can't affect in terms of a model surgery. That's it, because everything follows from that. If you get that, all of us, I can die in peace and my student can derive all my knowledge by mother mother called means.

Thank you for being so attentive and instigating.