B (8:56)

Great, thank you. It was a perfect explanation. And I also really love the way you have kind of planned the book. There are three parts, grammar, fusions and limits. And each chapter, there are nine chapters. And each chapter starts with a why question. And then we'll talk about some of the issues you discuss about animals and biology. And I can now see, I didn't know your background, but I can see why you other to write about these issues in your book. So let's start with something fairly broad. So in science they use deductive method. And to find scientific facts in the book, you talk about the first chapter of the book, you talk about some of the shortcomings related to this deductive reasoning or deductive methods. And then you also go on to discuss that scientific explanations could also be causal. So I'm interested to know more about these.

A (9:57)

Yeah, so actually there is an ongoing discussions in philosophy of science about what is an explanation. So because as philosophers of science, we are interested in the normative questions. Why is, for example, an appeal to magic, a bad explanation. And also we are interested in accounting for the fact that the norms for explanation are historically changing. So what people would count as a correct explanation at the time of Aristotle is not at all what we see as a correct explanation. And this is quite puzzling because actually one could say, okay, but science progresses. So this was wrong and now we are okay. But in order to progress, science has to find explanations. So science can change the contents of explanation. But how do you change the norm of explanations? Actually, so the very general questions Philosophers asked are asked is about what is an explanation. And then if you for example, teach philosophy of science in undergrad classes, you'll start in general. You talk about induction and David Hume. So David Hume was the guy who questioned the logical reliability of induction. What is induction? It's starting from some cases and saying something general about all the similar cases. And Hume very forcefully made a difference between two kinds of inferences, the deduction. So deduction is about you have a proposition and you derive something that is somehow already in the proposition. So for example, if you tell me I'll be in Barcelona next week, I can tell you that the next Tuesday you'll be in Barcelona because it's part of next week. So this is a deduction. And as philosopher said, the deduction is an inference that conserves the truth. So since as far as the first claim, the first proposition is true, the proposition that is deduced is also true. But of course in indiction you don't have. That's what Hume was saying, you don't have the problem of you don't have, sorry, this conservation of truth. For example, if you tell me like the classic examples, all swans are white and I infer, well, the next swan I'll be seeing will be white. And actually it might not. Some swans are black, so might be black. So the claim there is not this warranty that you will from the few swan you have seen, you infer to all swan. So the proposition about a few swan can be true, but the proposition about all the swans will not be true. So since Hume philosophers are quite suspicious about induction as an epistemic operation likely to robustly provide crosses. That's why when philosophers in the 60s focused really on the notion of scientific explanation, someone like Karl Hempel, who have been a very influential philosophers in the 50s, Austrian born, but then exiled in America, Karl Hempel was tried to understand explanations purely in deductive terms. So he had. And so I talk in the book about his view of explanation that has been very influential even though it's now very much discussed and in general few people subscribe. But it really played a great role in this general thinking about the explanation. So he says what is an explanation actually explaining is about? So it's a deduction, but because the only deductions are like thought conveying epistemic operations. But what kind of deduction? So he says explanations are the sort of inferences that tells you that tell you that the thing you want to explain should have had to occur. And what does it mean? So if I want to explain, let's say, the motion of the Moon, I start with the fact that the Moon is here and the Moon, or the general fact that the Moon has such orbit around planet Earth. And then what is an explanation? I subsume I show that the motion of the Moon derives from all the facts known about the universe and the laws. And that's the key, the key idea and the laws of physics. So more precisely, explaining the motion of the Moon is showing that if I know the facts about the position of the Earth and the laws of gravitation, then the trajectory of the Moon can be deduced from that. And so that's an explanation. And if you want to test it's very general idea, that also implies that if you want to test a new hypothesis, you have to derive a new hypothesis, let's say, about laws. You have to derive the facts that you know, and you have to show that those facts, let's say you have to show that those facts can be derived from the laws of nature in the same deductive way. So they call that the deductive nomological model of explanation. Deductive because you have deductions of facts from already known facts and laws and nomological because lows nomological means there are lows. Lows plays a very important role in this model. And so that was a way people could, let's say, show that scientific explanations are perfectly rational and avoid at the same time to make them rely on induction. Because induction is quite, quite unreliable. And why causation here? So induction has been, is really connected to causation. What it is to say that something causes something else. Hume says it's ascribing to something A, the power to produce something B. And how do you do that? Often Hume says you make inductions. So you say, you see, for example, you eat bread and so you have eaten lots of bread and you ascribe to bread the power of nourish you, okay, and feed you. And so the next piece of bread you see, because it's bread also you'll say, well, this has the power of feeding me. So you ascribe causal power on the basis of induction. Now, if you are quite suspicious about induction, you might be very suspicious about the very idea of causation. And that's something you find in philosophy of science very often. And that's also why Hempel would say, okay, there might be causation in science, but it's not the core of explanation. If some laws are causal laws, then they play a role in explanation, but they play A role because they are laws, not because they are causal laws. And so that's the picture of explanation, let's say in the 80s. And so turning to the question why causation in explanation, A lot of philosophers then questioned this view of Hempel and actually said, finally said, no. This sort of deductive, nomological view of explanation, it's not. There is a problem because it's only logical. And very generally it doesn't make the difference between explaining something and justifying a belief or making a prediction. So now, taking an example that is very classical, that is due to Wesley Salomon, suppose you have a flag somewhere, you know, and with a shadow, the flag has a shadow. And you want to explain the shadow of the flag. And it's perfectly. If you are Hempel, the explanation is, you know the fact of the size of the flag pole, you know the position of the sun, and you know the laws of optics and trigonometry. And from the fact of the, from, from the side of flagpole, you did use the size of the shadow. So that's an explanation. And someone says, okay, but you can do the same thing the other way around. You can deduce. Also, if you know the size of the shadow, you can perfectly well deduce the size of the flagpole. But nobody would call that an explanation because it doesn't make any sense to say that the shadow of the flagpole, the flagpole, explains the size of the flagpole. So there is something. Explanation should be asymmetric, asymmetrical. And so if you explain A on the basis of B, in general, you shouldn't be allowed to explain B on the basis of A, even though you can justify your belief that A on the basis of B. What I mean by justifying. And here is another sense of the question, why is that? If someone asks me, how do you know, let's say that the size of the flagpole, or for example, the perimeter of the Earth is such and such. And I would say, well, because I know it, because I know the shadow here and sorry, yes, I know the size of the shadow and I know the laws of optics and trigonometry, and it's a perfect justification, but it's not an explanation. And Solomon would go saying, what makes an explanation explanatory is a reference to causation. Why is the explanation of the shadow of the flagpole correct? It's because actually the flagpole causes the shadow and that whereas the shadow doesn't cause the flagpole. So explanation has to go somehow with Causation. And that's why many explanations are causal. And if you look at science nowadays, often. What do scientists try to do often? Well, they make models. And so often they, they make models, let's say, of the data. So for example, you have, let's say, the various positions of the Moon. And so you infer a trajectory of the moon and then you want to make a model of why it is like that, what produces this trajectory. So you want to make a causal model, actually. And in your causal model, you'll enter the position of the Earth, the size of the moon, the size of the Earth, their masses, the laws of gravitation, and then this mechanism in general, instantiating the laws of gravity and also laws of physics, will explain the motion of the moon. So in science papers in general, those models that explain are called mechanical models. So because they display some causal mechanisms yielding the phenomena you want to infer or yielding the trajectory you want to explain. So within science talk, this little worn mechanism that you see all over the place in scientific papers implements the notion of causation that is crucial in explanations. And as Solomon and others have, have said. Is it clear?

B (22:31)

Yeah, yeah. And the structure explanation, it's in science. How does that work?

A (22:39)

Yeah. So actually, one of my claims, and some philosophers absolutely disagree, but others agree, is that not all explanations are like this. Causal explanations, unraveling of mechanisms. And I take it that in many cases some explanations are such that some mathematical properties are playing an explanatory role. And what does mean in my example of the motion of the Moon? It's a causal explanation. And mathematics are, let's say, describing the laws of gravitation. So the relation between the masses and the inverse square of distance, that's the expression of the law of gravitation. But the mathematics is the expression of, let's say, the causal action of gravitation. Whereas in other explanations, what I am is that mathematics are themselves the explanatory, they are not describing causal action. And so an example would be from graph theory. And actually something that I have been trying to argue for years is that graph theory is the science of networks. And okay, so in current science you have networks all over the place. In genomics, like in gene regulatory networks, in ecology, you have trophic networks, networks of all kinds. In brain science, you have also lots of networks of very different kinds. And networks have properties that one calls topological properties that are studied by graph theory. And my point is that in some cases the structure, so the topology of the network plays an explanatory role. So for example, and that's my favorite example, I'll try to convey it by words. It's easier when it's topology, so it's easier with images. But anyways, if you picture yourself a network of predatory interactions, so species prey on other species, some species are eaten by other species. So a network is a set of points, dots, they call it nodes. And that can be related to other nodes by lines, they call them edges. And so a trophic network is a graph that represents all the predatory relations of a species in an ecosystem. So we can have like thousands of species. And if a species eats, so species are the north of the networks, edges are the relation. So there is an edge between two nodes if and only if one of the species preys on the other. And so you can build like this, when you know the ecosystem, you can build the traffic network of the ecosystem. And then the point is that most of those networks are of very general kind, which is called, well, almost scale free networks. In reality it's a bit more complicated, but that's the general idea. What is scale free network? Think of for example, airlines, air traffic, airlines companies. And so they have flights from various cities, and not all cities are connected. And in general you have very large hubs. So for example, if you, for, I don't remember, but let's imagine for United Airlines you have a hub in St. Louis and actually lots of the flights would go through St. Louis. So if you feature the graph of flights, you have a very large hub in St. Louis which is connected to many other cities. And lots of cities are actually connected to very few cities. So in ecology, trophic networks, it's the same. So it's that many species are very poorly connected and some species are very highly connected to many other species. And this kind of network is called a scale free network. And to put it bluntly, let's say you have lots, let's say, well, one or two, about one or two species, like around 10 species that are very, very much connected to hundreds of other species and hundreds of species that are a bit less connected, so they are connected to much less species. And then thousands of species that are even much less connected, and then like tens of thousands of species that are just very poorly connected to one or two. So if you see this, if you have this kind of networks, then let's suppose one species, random, you pick up randomly, one species and it gets extinct. If you do this, the chances that these species will be very poor, very highly connected to other species are very Very low because actually most of the species are very poorly connected. So if one species go extinct, it will change nothing about the behavior of the network, except if you target the species that is really very much connected. But chances that some of those species is targeted are very low. It's a mathematically because just you look at the proportions of the highly connected species in the network. And so in this kind of, it's a sort of toy example. I mean in general it's much more complicated, but that's really the general idea. So here is the topology of the network which entails the fact that very few that if you pick up randomly one species, it will be almost certainly very poorly connected, which entails the fact that the network is random to sorry, is immune to random species extinctions, which entails the fact that the ecosystem is somehow robust. Some species can go, other species can appear, but you know that it will sort of remain stable. So that's an example of an explanation where actually the nature of all the causal processes, who eats whom, who is eaten by whom, it doesn't really count in the explanation. You can just switch the edges in your network, provided that it still has this structure of scale free network, it will be robust. So that's what I call a topological definitions. And topology is a branch of mathematics. And in mathematics you have the different kind of structure, you have algebraic structures, you have structure in places of mathematical functions. And the general claim is that those structures are in some explanation. Those structures play an explanatory role. They are not only a description of the causal processes, they are as such explanatory. If you want to. If you ask me what does account in my example, the robustness of an ecosystem, I will answer it's the scale free nature of the networks. And this is a mathematical fact, it's not a causal process. So this is a kind of reason why things are as they are, that is mathematical and it's a mathematical structure, namely here topological structure. And not a causal fact. I don't know if it's clear, but that's the claim. So the claim is really about the fact that explanations, most of them, okay, they are causal, some of them are what they call structural. Other philosophers say non causal, distinctively mathematical. I'm telling there is, there are several philosophers who defend the same idea. My sort of, my own argument is really centered on this graph theory anthropology case. But that's the idea.

B (31:11)

Well, if it becomes completely clear, I guess it ceases to be philosophy. So part of it is just to raise these questions. Let's talk about the second chapter. And I really love the title of that chapter, which was why did Mickey Mouse Open the Fridge? And I must say that I really love the titles of all of them. But this one was really interesting to me. And I guess here it's where you talk about the reasons behind people's actions, if they are directed by desires or beliefs. And how do we distinguish between. Again, your book, you talk about distinguish between a reason to do something and a good reason to act or do something. So I would appreciate if you could talk about this part of the book.

A (31:55)

Yeah. So yeah, the book in general, I tried to start each chapter by focus on one sort of quite ordinary question and in order to show the various ways the world y can mean something for us. And so this chapter is really about reasons why we act or why I act the way we do. And so it's about how do we make sense of actions and behaviors and the why did Mickey Mouse open the fridge? It's, I guess it's quite. For me, it's a quite illustrative example of the reasons for action. So the question, and even a kid will ascribe to Mickey Mouse a desire which is like he wants to drink orange juice, he's thirsty. And also a belief that orange juice is in the fridge, it's not under the bed. And also I use this question also to highlight the fact that this ability of. Of identifying reasons for actions, ascribing desires and beliefs to the others is really something that arises very early in life. Actually kids do it. It's in cartoon. And also it illustrates the fact that we can even ascribe desires and beliefs to animals. And so maybe later in time adults will stop ascribing desires to animals or at least to different animals. Let's not talk about great apes and restrain those desires and beliefs to humans. But still this is a very deeply entrenched capacity that we have to make sense of actions of all the others. And so desire and beliefs, they are a reason why we act and why I act in such a way. Lots of complications there. And I'm really not going through in the book. Even in the book, I don't go through all the questions philosophers of action and efficient ask about what exactly is the reason? It suffices me to say that. The reason here has to do with desires, intentions, goals and beliefs. The proper way this is articulated. There are lots of philosophical accounts that are in competition about that and I'm quite neutral here. But the point, and it's related to a Question. What's important here is that a reason is not necessarily a good reason. So I remember here in France, we had sort of public debate. A minister said, you know, about explaining terrorism. And the minister said, yeah, but those sociologists, if they explain terrorism, actually they justify terrorism. And it's absolute nonsense, actually. I mean, if you explain what people do actually, you are trying to find out the reasons why they act the way they do. But justifying what they do is trying to show those reasons are good reasons. And it's different. So why is it different? We are, let's say when we act, we act for reasons. Actually, that's the difference between an action and, let's say, automatic motion sneezing. I don't sneeze for a reason. I mean, you have like biological processes going on. But I'm not saying I will sneeze in order to something. So actions are for a reason. We formulate the reasons. Well, there is also a debate here because psychoanalysts would say some reasons are unconscious. But actually those unconscious reasons, they work the same way. They are reasons why we act. They are desires. They make us strive towards something on the basis that we have certain beliefs about the world which make some action a mean to other action. We may be wrong about that too, sorry, a mean to a specific goal. And we may be wrong about this belief, but we act on this basis. And so there is here a kind of rationality which is once we have this belief about the world, once we have this desire, what we'll do will somehow fall from that. And it's quite rational. And that's why in general, when we have found out, think of a trial, for example, the motives of someone, the desires she has and what she thought about how the world is which makes this goal attainable. By this means, then we think we have explained the behavior, the action which he has done. But of course, we have not judged it. Is it good? Is it bad? That's something else. Because actually the desires themselves can be bad. So explaining finding the reason is finding the desires and the beliefs that are in the basis of an action. It doesn't tell you anything about the moral value of the. Of the belief. And when I say this is a good reason, this is about the moral value of the belief. And so this hinges about. Hinges upon the difference between two kinds of rationality. The first one, sometimes Philip, calls that instrumental rationality. It's about being coherent between my desires, the means, the goals that I desire to achieve and the means that I use in order to pursue Those goals based on what I know about the world. And I may be very wrong about the world, I may have very wrong information. And so I can pick up, let's say, very bizarre means to achieve my desired results. But still I'm rational because. Because those bizarre means are, let's say, the means that makes sense for me based on my beliefs. So if you want an example, think of someone who has been raised. In the idea or the belief that rain is somehow. Rain is a mortal threat and rain kills you. And this guy, if it's raining, he will, for example, if it's raining for one month, he'll never leave his apartment during one month. And someone could say that's irrational. But given what he knows about the rain, it's wrong. But it's. Sorry. What he believes about the rain and his goal, which is to stay alive, it's perfectly rational. So this is instrumental rationality. It's not about the value of your desires or the accuracy of your beliefs. And there is another kind of reason that some, for example, Kant called the practical reason, which is about the value of the goals, the desires, and the moral justification for that. But in order to explain why people act as they do, or to explain why I'm acting as I do, I guess instrumental reasons. Rationality is enough. Ethics or morality comes to play when you look at some more richer meaning of rationality. Rationality that concerns the desires or the goals and evaluate them. So is it clear? So good. So good. So good. New Year New gear. Thousands of fresh active styles are at Nordstrom Rack stores now. Save on top brands like Nike, Puma and free people starting at just $35. How did I not know Rack has Adidas?

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B (41:24)

Yeah, you actually answered my other question as well about this. But I'm keen to talk about you said that you had this background in biology, and I'm keen to talk about your. I think it's a third chapter. Why did. No, sorry, it's fourth chapter. That's where you talk about other living beings. And I guess it's sort of very relevant to previous chapter where you talk about humans, why they do actions. And this chapter you talk about other living beings except humans. And the question is raised if they have a purpose in life, and how can we sort of resort to the question of purpose? And then you also bring up the issue of function in non human beings to answer this question. And where does the Darwinian biology help us in answering the questions of herpes in non human living beings?

A (42:29)

Yeah, so actually the very general question here is about there is something specific to biology which is it's very hard to explain biological facts without referring to purposive statements of some kind. So for example, I can say that let's. Sorry, octopuses, are they. Or chameleons, they change color in order to escape predators. Okay, so this is clearly purposive. And the question philosophers have been asking since the times of even Descartes is okay, but does it make sense? Are we allowed to do this? Provided that since what we usually call the scientific revolution in the 17th century, the purpose stopped being part of the explanatory toolkit of scientists. So Aristotle, in contrast, would be perfectly happy with ascribing purposes to animals or even to natural entities like stones or air. You know, like the stones. That's a famous example. The stones tend to go down, to go to the floor, to the bottom. And that's their. Actually, that's their nature. Nature for Aristotle is a tendency towards something. So for him, nature was full of purposes. And of course, for him, and in general the Greek philosophers and the ancient philosophers, it was really not a problem to say, well, This animal is lying there because he fakes being dead in order to trump a predator.

B (44:42)

Sorry, sorry, go on.

A (44:44)

Sorry. Yeah. And in the modern revolution, very generally, I mean, things are more, as always, more complicated. But the basic idea is that science restricted to what one calls efficient causes. So causes where some state of the world determines the next state of the world. Whereas if you talk about purposes, it's like the effect that determines the cause. So, for example, escaping a predator, which is the effect of changing color, is why the chameleon changes its color to the color of its immediate environment. So that's. That doesn't fit into the explanatory scheme of the scientific revolution. And modern science in general, where causes should come before the effects. So what to do with that? There is a sort of eliminative strategy which is. Let's consider that when we use purposive statements like the chameleon tries to expiate a predator, the, the wolf is running after the sheep in order to eat it. Those are short, those are formulations that hint towards causal explanations that we cannot formulate because of our limited cognitive abilities. But ultimately there are only causes and effect in the world. But it's just that we have to use these metaphorical anthropocentered, anthropomorphical purposive language to talk about non humans because otherwise. But it doesn't, you know, grasp something real in the world. So that's the illuminativist strategy. And as many philosophers. I don't think, I don't think it's, it's correct because I think there are ways to make sense, first of the purposive statements and second of why those purposive statements are actually necessary in order to make sense of biological events, state of affairs, phenomena. So why is it the case? Actually the purpose of language in biology, it's really all over the place. So it's about functions. So when I say, when I say the function of. The function of the eyes are seeing, I'm saying that the eyes are there because they all vertebrates or the animals to see. So the effect of the eyes is really the reason why the eyes are there. But also what we call adaptation is also purposive. So an adaptation means a kind of. It's as if, let's say that the color of all the stripes of the zebra are adaptation in the sense that the, that it allows them not to be seen because the predator of the zebras, when he sees lots of zebras, actually it's hard for the cheetah or the lion to distinguish where starts and ends an individual zebra. And so it confuses the cheetah. So that's an adaptation for a life where the zebra are herbivorous, living in the savannah with cheetahs and lions. I mean, it's a purpose statement. The stripes are there in order to allow the zebras not to be eaten. And also you have purposiveness when you look at embryological processes which are really crucial for life. So it's very hard to make sense of an embryological process. An egg that develops into, let's say for example, a chicken egg that develops into a chick. It's very hard to make sense of it if you don't say that all the stages of the development are aiming at producing a chick. And so those are the aspects of purposiveness in life. So, for example, if I consider wolf hunting, this is a behavior hunting that is purposive. And purposive means that what the wolf does is explained by the presence of, or the putative presence of, let's say, other mammals and its hunger, which is ultimately related to its need to survive. But then the hunt, its purposely, behavior also means that sometimes the wolf actually, very often the wolf is hunting, but the goal is not achieved. The wolf hunts and the wolf is hunting. Even though the wolf doesn't in the end catch the prey, it's still hunting. So purposely, behavior can fail. Actually, it's an essential part of the meaning of purposive that the goal may not be reached. And then there is sort of hierarchical structure. So there are hunting, which is a purpose of behavior. Hunting is to get food. All the parts of the. Well, many of the parts of the wolf have functions that are related to this hunting clothes, jaws, legs, they are related to the capacity for hunting. So that they have functions. And the functions are understood in relation to the hunt. And then the hunt is in order to eat. So actually the purpose, the function of the claws and the jaws and then the hunting behavior are related to a very general function of the organism, which is eating, which is also directed towards surviving. So you have a very general hierarchical scheme of entanglement between functions of parts, general behavior, general function of the organism, hunting, general purpose. To surviving. So now why that's something biologists have been, you know, sort of epistemic scheme used by biologists since centuries. Why is Darwinian biology crucial here? Because it makes sense of all those purposive statements. So, for example, and this is an idea that has been developed by philosophers Larry Wright and mostly Karen Yander and Ruth milliken in the 80s. What do I mean when I say the function of the claws is to catch prey? First, this statement, this statement is explaining the presence of the clothes. So that's the very general, let's say this kind of explanation, explain the presence of the clothes. That's the first thing. And how is it explaining the presence of the clothes? Well, actually, it refers to evolution by natural selection. What does it mean? It's also a toy example. But the logics of the explanation is here thinks of a very ancestral population of wolves. And also think in Darwinian terms, meaning think populations of individuals that are different, that the basics of Darwinian biology, its population with individuals that vary, that are different one from another. And so some have clothes, some don't have clothes. The ones that have clothes, they'll be. They'll catch the prey. Actually, the ones that don't have clothes, they don't catch a prey. So the ones that have the clothes, they will survive and they will reproduce much more than the ones that don't have clothes. So in the end, because clothes are heritable, wolves, the whole population will have clothes. And that's the. So that's the Darwinian explanation. And what am I saying when I said clothes is. The function of the clothes is catching praise. I am saying that catching praise is what made the clothes selected by natural selection because it gave a reproductive event and survival advantage to the wolves that had clothes. Is it clear? Yeah, yeah.

B (54:09)

And some of the epistemic problems with this question also arise with the purpose of life.

A (54:18)

Yeah, yeah. So that's something. So, so. If one agrees with this idea. So I gave the example of functions, but very generally, actually the logics of Darwinian biology allows you to make sense of those functions, purposive statements. And so someone could say, okay, all the purposive statements or the functions of the parts of the organisms, the purpose of behavior of some animals, you can explain them, you can explain them by natural selection. And natural selection arises as soon as, as you have individuals that vary, as I said, and their differences are heritable. So let's say, for example, if you think about size, heritability means in a population, the tallest ones will tend to have offspring that are taller than the mean. That's what heritability means. And also that those properties gives you an advantage or can give you an advantage or can be costly in terms of reproduction. So you have natural selection for size as soon as the size makes a difference in the chances of reproductive tensors of the animals. So that's the logic of natural selection. And then someone could say, okay, so as soon as you have individuals that vary and that, you know, heritable variations and those little variations make a difference in their several chances, you'll have natural selection and you'll have functions, you'll have proposals, you have behavior, like hunting behavior. And it's the pure logics of actually, natural selection is a causal process. So you do not go out the field of causal processes, which is like, let's say physics ultimately. And someone could say, okay, but this is as soon as life exists. But then why is life. You cannot say life is there because of natural Selection, because evolution by natural selection is a property of living individuals. So is there a reason why life is there? Maybe life is there for something and for a purpose. And so. And actually lots of the discussions with people who, let's say people who are somehow religious and who think there is some design in life concentrates upon the question of like, is there a reason why life originated at the first place before evolution by natural selection? And what I'm pointing out in the book is that there is an issue with this question, which is that animals, most of the biological categories are actually quite well defined. Animals, plants, wolves, primates, and so. And most of the time they are well defined because you can ascribe to them a position in the tree of life, actually. But what about life itself? And actually, I think it's very hard to have a sort of definition of what life is. And what I think all philosophers and biologists think it's very hard to get a definition of what life is. And if you don't have a definition of what life is, how could you even formulate the question, does life have a purpose? I mean, you can say do eyes have a purpose? Because you know what eyes. So you can ask the question, you know what eyes are, but about life, it's much more difficult. And so I tend to think that the question about the purpose of life, I'm quite. For many reasons, I'm very close to Kant and that's a Kantian answer. But the question doesn't really make sense actually. So because you have lots of theories about what life is and no, no way to empirically discriminate between them. And some views are such that, for example, even stock markets will be alive. So that's Philip Marg Badao's. He has a concept of the nature of life, but it entails is very bizarre, these very bizarre consequence. Other definitions of life have the consequence that viruses are not alive, which is also problematic for some biologists. So what life is, I think is so just the definition is so unstable that you cannot even ask the question what's the reason why life is there, except in terms of causal processes that you know the chemistry of the world before life, we make some progresses in that. But the reason why life in there, in terms of goal or it doesn't make sense purpose, is it clear?

B (59:36)

Yeah. And you also talk about, within the next chapter, you talk about, explain the causes of historical events. And your example is the First World War. And that chapter was quite fascinating to me. And the main reason was that there were a lot of Concepts that I wasn't familiar with myself, for example. So you talk about why the First World War happens and is it based on triggering causes? And then you said that this kind of explanation is not adequate. And then you talk about David Lewis's idea of modal realism. And that's what really interested me because I hadn't heard his name before and wasn't familiar with this model realism. So can you talk about why, why, why, when we're talking about the causes of historical events, say these triggering events, triggering causes that lead to that event is not an adequate explanation. And what is David Lewis's idea of modal realism?

A (60:39)

Yeah, so actually, I'm starting with this thing that, that historians are discussing. So there were the explanation of World War I, and I was struck by the fact that at the same time, you know, in history classes, we are told that it's the assassination of Archeduc, Franz Joseph, Franz Ferdinand in 1914 that is the cause of the First World War. And we are also told that the situation of Europe, especially with these alliances that made it impossible for Germany being attacked without Austria replying and so on. So the situation of Europe made it actually very probable that World War I would have occurred anyway. I mean, if it hadn't, if it wasn't this, like, assassination that triggered the First World War, it would be like something else. So, and so my question is, okay, so is this assassination the explanation or not? Is it the cause or not? And I saw that actually you have kind of causes that are quite different. And this very question is about. So the question about the cause of World War I, the answer will be different. If you look at what we can say, what triggered it, given the state of the world? And this will be the assassination of Prince President. And what was the general background that made it possible? And actually towards the general situation of alliances between the countries in Europe? And this is a difference that Fred Bretzky makes between structural and triggering causes. And I think it's quite useful. And then why David Lewis. David Lewis defines what he called modal realism. But actually, what. What is it and what I am using. So what is it? Is the very sophisticated realization of an idea that was initially an idea by Leibniz in the 18th century, that this is. We live in a world, it's the real world, and there are possible worlds. So a world, for example, where actually I'm living in Marseille and that in Paris, it's another possible world. And of course, lots of things would be different. So if I were living in Marseille, it wouldn't be the same apartment there, it would not be raining outside, and so on. So there are possible worlds that are variants of the world as it is. And for Leibniz, that was very important because that would provide him the frame for addressing the question, why is there something rather than nothing? Why is the world like this? But actually, David Lewis doesn't. Ansel Kripke and Robert Stalnaker, who are the philosopher who worked on those ideas, they don't take the whole of Leibniz, but just a very general idea that there are possible. You can think of possible worlds. Those possible worlds may be more or less different than our world. So a world where, for example, I am, let's say, a soldier in Argentina is more different than our world from the world where I'm just a philosopher living in Marseille, and the world where you and me are chimpanzees is a world even more different. Or a world where, let's say the law of gravitation has another formula, is a world even more different. So the intuitive idea is that you can think of possible worlds. Those worlds may be more or less different than the actual world. And Lewis's idea is that in order to make sense of lots of things that are really crucial in our. Let's say, in our conceptual scheme, in our ways of thinking and in our language, actually we have to refer to possible worlds. So, for example, when I deliberate and I think, should I do this? Actually, I'm comparing two possible worlds. The world that will derive from me doing A and the world that will derive from me doing B. Those are two possible worlds. And so even deliberating is about thinking of possible worlds and what I am, what am I doing when I choose. Actually, I'm saying the possible world that derives from me doing A is better than the possible world that derives from me doing B. So let's do A. Well, I may be wrong. That's not the problem. But the point is that deliberating refers to possible world, even implicitly. And so that's the general idea. And what was the relation with World War I? Actually, it's very simple. What is an event that is necessary? So, for example.

B (66:11)

Like.

A (66:14)

Me, if I drop stone, like in the street, from my window, it will fall. That's necessary. What means necessary? It means that in whatever world where there is me, a window, a street, me dropping the stone will. The stone will fall. So the necessity has to do with some. Necessity has to do with all the possible worlds around our world and what goes on in this world. So what does it mean that? So for David Lewis, causation is actually causation. The meaning of causation is contained in the sentence if A hadn't be the case, B wouldn't be there. So that's A causes B means something like if A hadn't been the case, B wouldn't be there. And so the wouldn't be there. It's a conditional statement. It refers to possible worlds. So the causation for the causal statements are about what would happen in worlds like us, in worlds like os. Except regarding the thing A that I'm saying it's the cause of B. What does A causes B means? It says in all the worlds that are like os, where A doesn't occur, B doesn't occur. Now, I mean, it's not so simple because of course, what does like ours mean? And that's a huge question for philosophers because it's about basically how you compare world. So how you say this world is more like ours. So this world, let's say, is farther away from our world than this other world. If you picture yourself sort of universe of all the worlds. So technically it's a question of the Matrix, the distance, how you measure the distance between worlds. But actually, for this question of explaining World War I, what does it mean that World War I was unavoidable? It means that in lots of worlds around our world, even in worlds where there is not this assassination of the Archduke in Sarajevo, there is still a World War I. So that's where the possible worlds come into play, is that when I'm saying. World War I was unavoidable, that there are lots of chances that it appeared, etc. This is about all the possible worlds in which there is no Sarajevo murder. And in many of those possible worlds, like there is World War I. And so that's how you conciliate the idea that the murder of the Archduke in Sarajevo caused the World War I. Which means that in some of the worlds around ours, you don't have the murder and you don't have the World War I. And the almost necessity of World War I, which is if you look a bigger picture and you have lots of worlds around in 1914, and in almost all of those worlds you still have the World War I. So that's an account of necessity, modality, and also what I call inexorability, which is it's not necessary. But in most of the world, possible world like us, around, like ours, you have an event, and that's why I call it inexorable. And also Lewis was a model realist, so he thought that all possible worlds exist. Other philosophers who use possible worlds, like Stonemaker, for example, are not modal realist. Actually, I'm neutral on that. I mean, I'm not saying other worlds exist. I'm saying we refer to the idea for the world in order to make sense of. I mean, each time we talk about causation, explanation, we do explanation, we deliberate and so on.

B (70:47)

And talking about causes, in your book you go on to talk about conspiracy theories as well. I'm keen to know. I've talked to a number of historians and also historians of science and talk about conspiracy theories. But I rarely ask the philosopher why conspiracy theories are so common. You discuss it in your book and you also talk about the idea of chance, which helps us understand why conspiracy theories appeal to masses. Can you talk about this please?

A (71:17)

Yeah, sure. So actually I use this, I talk about conspiracy theories first because I've been working on this for some time. And so I'm like a deep interest and I think that it has also an important political interest. But here actually lots of my book is about drawing a line between what are, let's say, the correct merging of meanings of Y and incorrect ones. So when I. So it's in the. I call that in general fusions. So one of the idea of the book, which is something that's not very exceptional in philosophy, is that reasons mean several things. And like they mean the justification for beliefs, the reasons for action, the reasons of things or events, like the causes or the structural explanations, as I talked about. And if one why question asks for one specific kind of reasons, in general, it shouldn't be answered by another one. So for example, if I am asking why is there hurricane like in this part of South America? Now the explanation is causal processes. And if someone says, well, there is this hurricane because the humans in South America, they were sinners and God decided to punish them, this is not a correct explanation because it refers to goals, purposes, intentions. That's not what takes place in nature. So this is a confusion. And conspiracy theories, they are a kind, interesting kind of confusion because most generally they rely on the will to find intentions behind events. And so those intentions, conspiracy theories concern the specific kind of intentions. They are malevolent intentions and intentions that are part of a group of people and intentions that are hidden, non public that the three characters of the intentions to which conspiracy theorists appeal. And I was interested in that because for me it's an interesting confusion between the natural, the causes that are explanatory of an event and the appeal to an intention. And it illustrates also the fact that sometimes we are frustrated with the explanations. Natural explanation seems not to make sense of events and phenomena. And so the most common example in the history of philosophy about this confusion between intention and causes, it's religion. So religious people want that things that occur are not only the result of causes, but the result of God's intentions. And. And lots of philosophers like Spinoza or Nietzsche think that this is based on a sort of frustration with causal explanations and. Which doesn't. Which don't provide meaning. And so while we had conspiracy theories, which are more like, you know, a tinier topic than religion, even though it's politically important. So a conspiracy is the need for an intention in order to explain some phenomena. And why are they so common and so popular? That's a quite old question. One of the classical papers on conspiracy theory was by historian Richard of shader in 1933 or four, I think. And it's. They are. They really were very popular just after the Revolution, French Revolution. So there are two books that I don't remember the titles, but I cite them in the book that talked about the Illuminati conspiracy were written actually just after the French Revolution. And one of the explanation of why they are so popular is about the loss of order. So if you look at the waves of Sconpiac series, one was just after the French Revolution, one was actually in the wake of the Russian Revolution, and one was after the 9 11. And so some historians make the case, and I think they are right that when an order. So for example, French Revolution, it was the aristocratic order, the end of the Soviet Union, it was a sort of bipolar order of the Western world. So when an order fades away, it's like the meaning of things, the meaning of events tend to disappear. And then in order to give meaning, people are very much attracted by theories that tell them that the things have a meaning in terms of an intention of hidden groups of people. And that's why one explanation and something that makes conspiracy theories attractive is trying to say in the book is our sort of reluctance to one kind of explanations, which is actually. Which leaves some room to chance. And so it is. So what does it mean? First I tried to cash out the notion of chance. And actually it's not so easy because chance ties together two ideas. The first one is that, for example, I meet you like in the market where I didn't expect to see you because I didn't know you go into the same market. Actually, the Meeting you is like, someone could say it's a perfectly deterministic event, given my intentions, your intentions. The way the world is, I had to be in the market at the same time as the time you had to be there. So of course we would meet. But because none of us had the intention of meeting the other, we talk about chance. So one aspect of chance is the lack of intention. Another aspect of chance, which is quite different actually, is suppose I toss a coin and the coin lands on the can. Sorry, the coin lands on one side. Sorry, head or tail or whatever. Head. The coin lands tail. And one would say, okay, that's by chance. I mean, but what does it mean here? Chance. It means the chances of head and tail were the same. So chance here has to do with equal probability. So the word chance actually is unstable because it tends to mean equiprobability, equal probability, and it also tends to mean lack of intention. And those two things are very different actually. So the very concept of chance is unstable. And I think that make also explanation that at some point, say, well, this is also by chance, sometimes hard to accept while they have to be accepted, because actually lots of events are such that there is no intention behind them. And lots of events also are such that actually, you know, like one or the other configuration was almost equally probable. And so. And also something else is that. It's hard in general for many people to think that very meaningful events like, you know, the life of Lady Diana, for example, can be there out of pure chance in the same. In the sense of, for example, events that are like, poorly. Yeah, sorry. There's another meaning of chance, which is things that happen and that were. We keep like that had low probability. And so if an event is very meaningful, like the assassination of John Kennedy or like the. It's hard to say. Well, it's not. It's not pure chance, you know, a plane crash or where someone very important was there. And I'm trying to. Well, there are some examples like this, but. So Lady Diana, yes, chosen car accident. And some people say she was so important it shouldn't be a car accident. So it's a dissymmetry between the political or moral significance of an event and the chance inclination, which is like, without meaning. That makes some conspiracy theory quite attractive to people. Even though the very word conspiracy theories, I'm not a fan of using it too much because I think it's hard to think of conspiracy theories without political context. So, for example, if I read like the New York Times, that this, let's say let's imagine the Prime Minister of had a country that was about to go to war. No, sorry, that's a bad example. Okay, let's say if a politician that was an opponent to the President died in a car accident. If I read it in the New York Times, it would be irrational to say, no, he's been killed, it's a conspiracy. But if I am like North Korean citizen and I read in the newspaper that the only opponent of the Kim Jong Un died in a car accident, it's quite rational actually to think that it was a conspiracy. You see. So because of what we know of North Korea and the fact that actually no newspaper there is reliable, there is no real freedom of information, thinking of conspiracies, groups of conspirators is not irrational. So there is a definition of conspiracy theory, which is. Conspiracy theory is a theory that appeals in a non necessary manner to a group of malevolent people acting in secret. And the word non necessary, the definition is by David Aronovitch, an English writer. But that's useful. But then what does not necessary mean? And my point is that if you are a North Korean citizen, an unnecessary appeal to a group of conspirators, well, it might be very necessary given what is the kind of state you live in. Whereas if you are Western and American, Australian citizen, well, hopefully in my example, it's not necessary to appeal to a group of conspirators. So the point is that the world conspiracy theory, without the context where you use it, I mean, who talks of conspiration in which country? What's the political regime? It's not really meaningful.

B (83:50)

Before we come to the end of this conversation, I'm curious if there's any other book or project you're currently working on.

A (83:58)

Yeah, well, actually there are several projects, but one is a very academic book on this question of structural explanation, but it's really intended towards professional philosophers. Another one is actually I've been working on a book that was published there, hopefully it will be published in, in English. It's called Les Societies du Profilage. I mean profiling societies, where I'm looking at how the gathering of lots of data about people through a lot of numerical digital channels allows fine grained predictions of the, like the behavior of people or the beliefs of people, and also act upon the beliefs of people. Like in the case of Cambridge Analytica, the scandal about the Brexit and what kind of political governance, what kind of political setting is produced by that and so on. My other project are more technical things about philosophy of ecology about what's an ecosystem. Yeah. So that's in general what I'm doing.

B (85:24)

Right. Professor PHILIP thank you very, very much for your time to talk to us about your book. I strongly recommend this book to our listeners. It's, you have a lot of good, relevant examples which makes the, makes the really difficult concepts more and more accessible to a lay audience. Thank you very much for your time.

A (85:48)

Well, thanks to you. Thanks. Thank you very much for your interest and your attention and the podcast that was great.