Hello and welcome to the eighth session of restructuring enlightenment from Carnap's outbound to conceptual engineering. I'll hand it over to Reza. Thank you. Thank you everyone. Hello. So I was just saying to everyone that there is bad weather. We might lose electricity. I don't think so, but let's see. Regardless, I have to leave 30 minutes earlier today. Endo has been generous enough to agree to hold another session. Next week we will have one hour. So the 30 minutes from today plus an extra 30 minutes that I promised. So that would be it.
We can start. Presentations. Hi, I think I'm presenting today. Unfortunately, okay. So yeah, my electricity is also not working properly. So I have entered into account. So in case one internet line. Sure, I know Iran and Iraq have the same electricity. Yeah, so I have a contingency plan. Okay. Firstly, just one minute.
Okay, so in this presentation, I want to talk about explication as anti-philosophy. So the first question is, what is an explication and how we can define it as anti-philosophy? An explication is meant to result in an explicatum that's exact in contrast to the vague or inexact explicatum. That's to say, the task of making exact, a vehicle, not so quite exact concept that's used in everyday life, like any folk psychological concept you could think of, or even a concept that's used in the earlier stages of scientific or logical development.
Or replacing it by a newly constructed, more exact concept. So the distinction between what can be called the conceptual analysis or amelioration and replacement or engineering would be of crucial distinction for us for our discussion today. So you either simply transform a vague concept in hopes of retaining at least maybe partially a given explicandum, or you could simply give up the explicandum and come up with your own newly constructed or engineered concept. So for the sake of clarity, we call these two kind of explication, partial and full-fledged explications. looking at another angle what does it mean to be exact in this context or exactly in what sense
you can ask the answer to this question i think can be found somehow as implicit in karnoff's writing and i think the first indication of what amounts to can be found in the principle of tolerance when you know when karnoff says in in logic there are no morals everyone is at liberty to build her own logic and so on. The reason why I think this can be called anti-philosophy is because what is rejected here is clearly all the philosophical arguments. What actually counts now for Carnap is only the precision of a given syntactic and semantic rules of the kind of logic which you are at liberty to construct,
not the philosophical, traditional philosophical arguments or philosophers or arguments of everyday discourse. And for Carnap, you know, this is the only remedy which we can provide for the inconclusiveness and the infinite, what can we call, you know, the infinite ambiguity of philosophy, philosophical arguments and everyday discourse. Now, briefly, you can enumerate certain examples, as we discussed in the previous seminar. You know, Karnab sees the task of providing explications as in line, you know, he doesn't claim that's something quite new with him. He says that explications are quite, you know, in line with what other earlier philosophers, analytic philosophers did.
And in fact, you know, in Meaning and Necessity, he lists three or more models for explication that reveal where he is coming from. For example, first, he talks about, you know, Frege and Russell's analysis of natural numbers, where the explicandum is the term, quote-unquote, two. It's not the exact meaning, it's a concept that's used in every discourse, even in applied mathematics, but meaning is quite vague. And to be replaced by an explicanum, that's the class of pair classes, for example, as introduced by Frege and Russell. Secondly, you know, Frege and Russell's other work on different descriptions, which, you know, which contains the phrases like something is so-and-so, something is this-and-so.
and this is as the explicandum and this is replaced by various various interpretation of descriptions that was provided by Ferga and Russell we will not go into the details of this various interpretation, just for the sake of clarity, we are talking about different kinds of explicatum that they are for karma and thirdly Tarski's account of truth where the explicandum is the concept of truth that's used in everyday language and all by in everyday language and by, you know, traditional modern logic. And the explicatum would be the semantic theory of truth that was eloquently developed by Tarskian as T-schemata,
if you are familiar with it. And these three paradigmatic examples for Carnap comes from, you know, logic and the foundations of mathematics. But for Carl Napino, he says another layer should be added to these examples, that philosophy should also model itself on natural sciences. And this involves the transition that we talked about in the previous seminar, when he talks about the pre-scientific concept of fish, which was transformed into a new theological notion, which I cannot, which I do not know how to pronounce it. examples like NACL. Okay, now, you know, beyond this brief characterization, I want to talk about
the four requirements of explication which we're also discussing in the previous seminar. So an explicatum has to satisfy four requirements to a sufficient degree, quote-unquote, sufficient degree that is the phrase that Carnap uses. Firstly, you know, the explicatum has to be similar to the explicandum in such a way that in most cases in which this explicandum has to you know has to be used just the way you know the explicatum can be used and I think and this is what can be called you know the similarity condition and I think you know this similarity condition should not be interpreted in terms of extensions of explicanda and explicata
you know, the extensional, the referential, whatever you can call it, not the extensional description of explicanda and explicata. Rather, I think it should be better construed, you should better construed this similarity functionally, you know, as the functional rule performed by an explicatum in a suitable theoretical framework, for example, which was previously performed by the corresponding explicanda. So, you know, an example, you know, we might talk about and explicate the concept proposition. You know, the concept of proposition can be given a lot of explicata, but, you know, one of them, for the sake of argument, you can say the concept can be explicated in terms of sets of possible worlds.
and the reason why I think this similarity condition should not be defined extensionally is because you could explicate propositions in terms of a set of possible wealth without believing in the extension of the proposition that could have possible wealth. The set of possible wealth are only introduced functionally, not necessarily extensionally. You are not a model realist like David Lewis if you believe in sets of possible wealth. which is a explicata for the explicatum proposition. So the concepts are here similar in the sense that, you know, the explicatum that was introduced performs the same function as the explicatum.
Secondly, you know, the explicatum has to be precise, or at least more precise than the explicatum. As we talked about, in virtue of explicit rules of use or explicit rules of definition given in the well-constructed, well-connected system of concepts. Thirdly, explicatum has to be fruitful in the sense that it facilitates the formulation of many universal statements, empirical laws in the case of science and logical theorems in the case of logical concepts. Fourthly, the explicatum has to be simple, which I think is a quite straightforward and non-problematic requirement.
You know, these four requirements are satisfied, you know, as follows. In an example, you can replace, you know, the four concepts of warm with a quantitative concept temperature. Firstly, the similarity condition, you know. In most cases, when we say that something is warmer than y, according to our sensation, you can explicate in terms of the temperature of x is being greater than the temperature of y. Second, precision. The rules of use for temperature can be precisely defined with reference, for example, to thermometers. Thirdly, fruitfulness. Your temperature can, the concept temperature, the explicata temperature can be used in many laws in science, for example, in the ideal Gauss law of physics.
And for simplicity, you know, both, you know, the rules for temperature and the laws that temperature is used in are quite simple compared, maybe they are quite simple compared to other alternative theories that we have for temperature, for example. You know, in light of such considerations, I think Carnap says, you know, temperature can't be an explicata of warm or cold, and it's quite important for science. Another important concept I want to talk about with regards to these four requirements, which will be important in the later slides, is that, you know, kind of typically is construed, I don't know if truthfully or not, in terms of interpretation of his work, that he has prioritized fruitfulness over similarity and other requirements.
and he plays favorites with regards to these requirements. And I want to highlight, you know, why this favoritism of Karna could be problematic in some sense. You know, here we can bring up the first distinction that we made between conceptual amelioration or conceptual and conceptual engineering in explicating the concept of war. And this, you know, either you choose conceptual amelioration or conceptual engineering would depend on your own aims. For example, if your aim is the improvement of concepts in in the service of, you know, logical, mathematical, and empirical concepts, then you have to prioritize fruitfulness over similarity. So because, you know, you don't care
about the similarity because you want to get away from the folk concept and you want to construct a new concept and the sole desiderata, the sole requirement for you is the fruitfulness and you will prioritize fruitfulness of a similarity. Okay, so the second in contrast to that, if you want to you know to uh your you only want to shed some new light on some some unclear concepts you by introducing a new concept that will just correspond to the four concept the previous the explicit explicanda concept you are you are here trying to prioritize similarity of
fruitfulness you know from this uh and so the difference between this amelioration and engineering would be that you are prioritizing some requirements over others, and we'll see why this distinction will be important for us. Okay, at the beginning, you know, I said that... Sorry, I'm on the right here. At the beginning, I said, you know, that explication can be defined as anti-philosophy, anti-philosophy through and through. And I think this is the angle from which Peter Strawson would target Carnapian explication. And Peter Strawson would be the major influence of the seminar.
For Strawson, firstly, you know, you have to talk about the central problem that he talks about in regards to Carnapian explication. The central type of philosophical problem that here, Strawson, Peter Strawson, the latest Strawson, not the youngest Strawson's son, the advocate of panpsychism. psychism no not that guy the the older guy peter strossan the central type of philosophical problem that you know peter strossan wants to highlight as he says this kind of problems deal with paradoxes and perplexities you know for example it happens that you know when you are reflecting on a certain kind of concept you know on your armchair you find that yourself to be driven to i don't a certain kind of uh accent of kind of view or position that seems quite paradoxical and quite unacceptable
for example you know uh external skepticism you know from arguments like arguments from illusion or from the nature of sensory experience and we typically respond to this kind of conceptual dysfunction or conceptual imbalance to solve it or resolve it or dissolve it whatever way you like it So this is a typical philosophical argument or problem that arise from traditional philosophy, which uses four concepts or some sort of refined concept of analytic metaphysics, for example. Concepts like the world or experience or knowledge. For Strossen, these concepts that are used in everyday discourse, these are the kind of concepts that actually give rise to this this sense of philosophical problems.
But those who are introduced in scientific context, for example, for their fruitfulness, or whatever goal that you have in mind, they have a narrow purpose. They simply do not give rise to the kind of particular set of philosophical problems that he's talking about. So this is the first problem of explication. The first problem is this. You know, if we seek to use Carnapian full explication, you know, we differentiate it between partial and full explication. After you use the Carnapian full explication to resolve the above mentioned philosophical problem, we thereby replace the concept used to formulate these philosophical problems with a concept that's designed to be useful for science.
Well, that's the difference. You replace a useful concept, which is useful for science, with a concept that was previously used as a philosophical problem, like external skepticism. But Strassen says, you know, this simply changed the subject. We are simply changing the subject because there is simply no alignment between what I want when I'm talking about philosophical problems and what the scientist wants when he prioritizes the fruitfulness criteria for his explicata. You know, as we said previously, that the third condition is the similarity condition, that it should be defined functionally as a functional role played by the explicatum in place of the explicandum.
Part of Strassen's thought here is that, you know, given that the use of language in science is quite narrow, you know, the scientific concept is quite narrow, the purposes of science are quite narrow and the ordinary language purposes are quite broad and has a variety of uses in everyday discourse the concepts that we want that are introduced to in science are actually serving a narrow purpose compared to this broad uh broad purpose uh concept broad course uh purpose of ordinary discourse that's to say you know when we we define even the explicatum functionally so the narrowness of the functions of the explicatum simply cannot just allow itself
with the motley of the functional uses that of ordinary discourse so the functional pluralism of of ordinary discourse cannot align with the functional conservativism of of of scientific discourse. You know, if that's the case, then you can you cannot show there is some sort of isomorphism or correspondence between the functions of these two different different branches. You cannot even talk about the similarity condition at all, let alone a sufficient degree of similarity as Karna talks about. Hence, you know, the explication for Strassen is quite irrelevant, Since there is no functional isomorphism or correspondence between the explicandum and explicatum,
the language of science cannot simply supplant the language of drawing rooms or the language of culinary hours or the language of kitchen or the language of court. So I think these two kinds of arguments are directed. you have to make it clear that these two kinds of arguments, the changing subject argument and the irrelevance argument, are quite separate. One of them is directed against partial explication, the other against full explication. Okay. By way of previous example, Strausson talks about Karab's example of warm and temperature.
He says, you know, that our sensory concepts that have a rich source of philosophical perplexity. You know, for example, he used some simple examples, you know. When he says, you know, when you talk about the sensory experiences or sensory awareness of two people, does it follow that from the fact that, for example, you know, we have the sensory experience of the same object, but for me it can feel warm, but for you it can feel cold. That in an object that's really neither cold nor warm. And maybe it doesn't have any kind of warm or cold property. So, you know, such questions can be answered, or the fact that there's some sort of dissimilarity
or disalignment between my experience, sensory awareness of the coldness and warmness and your sensory awareness of coldness and warmness cannot this kind of difficulties, conceptual perplexities and problems that we talked or that we defined in the previous slides cannot simply be solved or resolved or dissolved by formal exercises of scientific concepts like, you know, temperature, wavelength, energy, frequency, whatever. So, and if you try to replace you know, warm and cold and any other kind of related concepts with a scientifically fruitful concept, which is called temperature,
it can be fruitful nonetheless. Strauss does not evade explication altogether. But he says, you know, because scientifically useful concept does not actually give rise to this kind of problems, philosophical problems, you know, the dissimilarity between my experience of cold and your experience of cold that has no kind of, that has no isomorphism with the actual object that has a quantitative level of temperature, because there's no isomorphism between them, you cannot simply claim that you can replace one by another. You cannot simply replace the explicata, the explicandum, by the explicata.
Okay. You know, an argument by analogy can be used to save the similarity condition, the first condition that we talked about, you know, as the answer to the changing subject criticism. You know, when Strossen talks about, you know, when there's no similarity condition between, because of the diversity of uses in ordinary discourse, there's no similarity between the scientific uses and the folk uses of a given concept. He charges us with the changing of subject criticism. And there is some sort of response that can be given by some sort of, you know, by an argument from analogy. You know, I know a number of authors have actually used this kind of criticism against against
straw some in the following law lines, you know, suppose that we are interested in in a in a concept called this concept C. And this concept C has a property F. And the, you know, the question mark indicates that, you know, we are unable to determine to determine this question directly we don't know whether this concept has a property f because because the concept is big or whatever it's actually it does not have explicit rules then we might try to explicate c resulting in the explicatum c which is the c prime you know given this c prime is more
precise than c we might be able to establish you know for example you can say f of c prime you know the the c prime now has the property c because we try to explicate the explicandum which was c with a with a new concept which is c prime then by pointing out the similarity between c and c prime you might argue you know by analogy you know the similarity condition is here is saved or salvaged by some sort of analogy you can say then f of c so the s is determined the s you know the vague concept the explicandum is determined retrospectively by the explicated c prime so that's
the similar the similarity condition has been met and we have explicated the similarity condition But, you know, but I have a problem here. You know, if one uses this, you know, and we please take this in mind that, you know, when you talk about similarity condition as the more fundamental, we are talking about partial, partial explication. Therefore, this is an argument against partial explication, not full-fledged Carnapian explication. So if you use this as an example of partial explication to solve the philosophical problem that you talked about, the dissimilarity between sensory awareness and sensory experience of my warmth and your coldness, and what this argument from analogy can achieve is only FC.
You know, FC can be explicated by FC prime. But it seems, you know, if you try to retrospectively construct FC, which was the vague concept, out of the explicated concept, you started with the explicated one, the C prime, then you tried by analogy, try to show that there is similarity with the vague concept. and this you know but ultimately you seem to be leaving out the to me part and the to you part you know this part cannot be you know it cannot be explicated but can be explained by ordinary language so this seems to be a step extra beyond beyond the the the explication part
because to explain, not explicate, to explain is to accurately describe certain mode of functioning of the given non-constructed explicandum of the four concepts. Simply put, you know, if there is a pathology, namely ambiguity related to the four concept, which is the explicandum, then we have to have a precise delineation or definition of not only the pathology, which is the ambiguity, but also the physiology of the explicandum, which is, or we could say, what a non-ambiguous explicandum would look like. But just setting aside the to me part and the to you part
is not illumination, it's just desertion. Gertrude Kauru- Finally, you know, as I said again, no, this is an argument against partial explication not the full-fledged kind of an explication which will you'll deal with it in the in the in the late slides. Gertrude Kauru- Okay, we said you know previously that you know replacing the philosophical problems you with the fruitful concepts simply change the subject, you know the philosophical puzzles and. problems that we face. If you just say, you know, a simple magic bullet, which is useful concepts, can solve our problem. This is simply changing the subject, according to Trossam. And this kind of full replacement is the start of criticism of the full-fledged Carnapian
explication. And it's informative to start with a quote from Carnap. when he says, you know, a natural language is like a crude, primitive pocket knife. Very useful for a hundred different purposes. But for a certain specific purpose, special tools are more efficient. Example, chisels, cutting machines, and finally, microtome. Microtome is the microscopic cutting machine that's used in medical laboratories. If we find that the pocket knife is too crude for a given purpose and creates defective products, we shall try to discover the cause of failure.
And then either use the knife more skillfully or replace it with this special purpose by a more suitable tool or even invent a new one. one. Strauss's thesis is like saying that by using a special tool, we evade the problem of the correct use of the cruda tool. But would anyone criticize the bacteriologist for using a microtome and assert that he's evading the problem correctly by using a pocket knife? Of course not. No one would criticize the bacteriologist for using a microtome. I think there are two brief points to be made here in response to Karna. You know, first, Strasser actually does not deny that explication per se can be useful for us,
for illuminating, for example, not necessarily solving, maybe solving philosophical problems. He accepts that and he actually says, you know, this partial explication, what he calls, you know, actually calls the partial explication, Rational Reconstruction, which was the earlier version of Carnap's explication. Sorry to interrupt. Is there much more to go just because we are a little bit tight on time today? Sorry, no, no, only two slides. Okay, I mean if you can wrap it up in the next minute or two. Yeah, yeah. Yeah, yeah, I'll go there. OK. So what I want to highlight here is that, you know, you could say, you could give two arguments
against counter-ups here. For example, you know, you could say that, you know, you know that an explanation could be useful uh could be useful for our for our for our purposes but but no knowledge is gained about you know pocket knives by replacing it with micro microtomes because to know about pocket knives is to know about pocket knives uh microtomes will not illuminate any kind of uh new knowledge about about pocket knives and requirements requires actually replacement requires some sort of antecedent knowledge about explication which I will discuss in the next slide, you know, a few words. You know, we said, you know, if, as we said earlier, if you don't want to give an
antecedent explanation of the ordinary concept or idea, you are simply, you are simply deciding in advance whether, you know, this kind of concept will be fully explicated. And you will have a deeper problem here, you know, because you are just, you know, simply talking past each other. And I think this revisionary view of full-fledged Carnapian explication, you know, as radical conceptual revision of everyday discourse has a problem of fixing the reference. You know, how can we be sure that we are references preserved across even different explications between a Carnapian and a post-Carnapian explicators, let alone between a Carnapian and a Of course, I'm not talking about referencing the crazy sense of truth makers and stuff. I'm just talking about, you know, the banal idea that we are talking about the same thing as two interlocutors, that we are not just simply cross talking with each other.
Finally, this is an example of that JL Austin uses as an example of the richness and complexity of her discourse. The example involves shooting donkeys, but because I don't have time, I'll not talk about it. Thank you. Dilshaar, magnificent presentation. I actually, to be honest with you, I was really, you know, this is just like you're giving us all this stuff just to bring us to the shooting, shooting donkeys. And then right at the moment, which is critical, important stuff, you say that,
sorry, I'm going to cut it off without even saying what shooting donkeys entails. Thank you so much, though. So, there's so many things to unpack here, really so many things. I mean, I'm just going to really skim through it. I mean, I think that you should also, just like some of the presentation I asked, because of the amount of information contained in this presentation, if you can share it with us. Did Cassia share it? not yet forget sorry forgot don't worry don't worry about it don't worry it would be magnificent
if you can do all of you can do this before next session so basically I can I can I can go through it think about them if see if something comes to my mind and so on so forth yeah so with regard to anti-philosophy. I think that's, I don't know. Go ahead. Can I just remind you as well? I think Vincent has something to put forward today as well, just so that we. Oh, oh my God. Oh, Jesus. Okay. Okay. So Vincent, Vincent, go please. My apologies. Truly apology. Okay. I'll share my screen. Can you see it?
We can see it now. The following presentation called density or risk contra agency will be general and mostly informal, but I aim to explain the concept of density. a density otherwise different from the Archimedean understanding of the quantity of mass per unit volume or how much space a substance takes up, but a stand-in for a frictional force at once material and social contained within a topology. The first part of this presentation briefly deals with this graph, or what is specifically called in graph theory in computer science, as a directed acyclic graph which I devised for this subject matter. When drawing directed acyclic graphs or DAGs, we are primarily concerned about causal relations among variables.
DAGs are a simple way to encode our subject matter knowledge or our assumptions about the qualitative causal structure of interest. Consequently, each node on DAGs corresponds to a random variable and not its realized values. To put it simply, a directed acyclic graph is a graph with directed edges in which there are no cycles or the flow from one variable to another does not result in a continuous causal loop. To cite an example, in the paper called Causally Interpreting Intersectionality Theory, Liam Bright et al sought to formalize the idea of intersectionality by quantitative means. And by explicating this concept, the theory can be more precise in order to resolve ambiguities in such a way that the concept can be fruitfully applied in future research. They used causal graphical modeling in causal Bayesian networks to model a directed acyclic
graph of the variables concerning intersectionality, given here as parental income, race, gender, education, wealth. The literature describes that a graph consists of a set of vertices or nodes that are random variables connected by edges or arrows. The random variables can be either continuous or categorical, i.e. they can take on a finite set of discrete values. Arrows represent direct causal connections between the variables, so that if x points to y, then X is a cause of Y. It's to say that X is a parent of Y and Y is a child of X. The sequence of edges is a path. If there is a path from X to Z that consists of directed edges with arrowheads towards Z, then X is an ancestor of Z and Z is a descendant of X.
In Breit et al.'s graph, assuming that all the variables are categorical, parental income and education are both direct causes of wealth and additionally, parental income is an indirect cause of wealth via its influence and education. The absence of an edge or arrow between two variables indicates that they are probabilistically independent, given some subset, the other variables in the graph, including possibly the empty set. Race and parental income are independent in the graph. However, the graph also predicts that race and parental income are dependent conditional in education. For Bright et al., and I quote, such connections between graphical structure and the probabilistic independence can be exploited in order to search for graphical models from data. The same kind of observational data that are typically available in quantitative sociological datasets, for example, in epidemiology, political science, or macroeconomics.
Catherine Dutrinovaes also cites this paper in her comparative investigation between Carnap's explication versus Haslanger's ameliorative analysis, citing that by possibly interpreting the concept of intersectionality as understood in the social sciences, The methodology of explication as used by Bright not only identified an interpretation, but that it has the possibility for illustrating the links between prediction and the potentials of social engineering after conceptual engineering. In this dug-eye device, I have the following variables for the concept of density. Economic resources, political positions, degrees of competition, tensions, gradation, and density or accumulating. The direct causal relationships are the following. ER causes PP, PP causes DOC, and so on and so forth.
Intermediate variables serve as a causal link between two variables and then act on the dependent variable to introduce change. Here, PP is an intermediate variable between ER and DOC, DOC between PP and P, and so on and so forth. On the other hand, ER and PP are colliding variables such that they both cause gradations, but ER also causes PP, hence PP are causally dependent on ER. but ER are independent variables that cause gradations. Put in a slightly different manner, ER has a direct effect on gradations, but PP, given its causal relation to ER, has some more derived effect. We can also obtain the causal effect of ER on some dependent variable, like degrees of competition, for this. Let economic resources represent ER, which can either be zero or wealthy,
and one or poor, and political positions as PP, which can either be zero or dominant, and one or subordinate. it. Both variables are being treated as binary only for simplicity here. Thus, the causal effect of ER on some dependent variable, for example, degrees of competition, can be written as the following. More causal relations can be interpreted further, but I limit myself to this for the sake of simplicity. As Bright et al. mentioned, once the causal structure is known, whether by application of search algorithms, domain-specific background knowledge, or other means, the researcher may quantitatively estimate causal effects of interest or test hypothesis on the subject matter. Going to the more qualitative or theoretical aspect of this presentation, I wrote an essay divided into three parts that should qualify some of the concepts or variables I introduced before and expound on newer ones.
This first section is entitled Escalating Tensions. Tensions are dense, cached and pressurized over time, inflated by material contexts, and much harder to truncate as it escalates. Given the actions that constantly premise our enduring civilizational disasters, the planet can only be a containment of tensions that's not solely structured to a pure abstract degree. Thus, every tensile complication can have volumetric consequences. Earthbound crises take up space and its occupation of a physical scope, a density grows planetarily from the coalescing dynamisms, ecological and anthropological, that force contents to expand from a tipping point A to a general threshold X. This density is inextricable to both scientific truth manifested by extensive properties in a social dimension where subordinated geopolitical position and economic resources reflect in the competitive facilitation of knowledge and problems from one side, for example, nation-state, locality, community, etc., compared intertopically, that is, between nation-state, and so on.
Hence, density is nothing but the enlargement of anthropogenic tensions in lopsided site-dependent predation, where a finite capacity for life is withheld against an approaching fatality with regards to what we may be presumed as a planetary pressure in progress. This density can also be described as the range of accumulating planetary risks over time, one in which the supra-hazards that societies emit as a result of modernization are multiplied and compressed from localized region-specific unfolding with the likelihood of outsizing the area of tolerance from an origin point. Zooming in on the level of sociality, risks for Ulrich Beck turned events initially foisted on individuals as their own errors into social events, systemic events, which also require social institutional
political regulation, end quote. Every error in light of ecological decisions and scientific truths are fastened into this interactive quantified involution, which in turn gives rise to both indefinite responsibility and indeterminate hazards. The ecology and technology then to which risks are produced can only prove paradoxical in instances where tools to mitigate the same risks, however germane cannot in themselves be foretold. Even the most advanced predictive mechanism cannot account for the unspecifiable variations to come. That is, a counter formulation or response cannot simply be applied or performed in an undiscovered risk. The disclosure of risk, therefore, is the condition of possibility for discerning its own distribution in space and reduction in amount,
whereas density not only expresses the dormant and accretion of risks to come, but also the the dimensions of human agency in a risk-laden space. While at present, containment measures at the theoretical and practical level are plotted against actual and probable dangers, such as the magnitude of climate change that erupts into irreversible damage and consequently the hierarchical extinction of early life forms, density is already characteristic of disorders, materially speaking, that burst at the seams of recognized maximum. Climate change, for example, is what results from genealogical process of evolutionary and post-industrial technological elevation is synonymous to a density factor that challenges bio-physiological suitability of organic life. Like any qualification of crises, this becomes a subject of demarcation,
of specific ceilings that when surpassed could only launch terrible results. In that sense, what factors in on a global scale of densified conflicts is both a problem that remains unsolved and the deluge of incoming ones at the juncture of risks, breadth, and duration, both of which need immediate repair and rehabilitation. Offsetting the parameters of a dense world acknowledges that an existential breath is looming, but only because problems unfit to the requirement of sapiens compared to the planetary resources reveal the untenability of the current material organization of life. The mitigation of this density should be necessitated by a gradual change of actions in material allocations to construct one that's fitting to the requirements of a densified world making. Density can only count on the parameters where its progressive ballooning is actuated, which means that the pressure is inert and so the designated sphere of action can only
be internal. Vincent, I'm sorry to interrupt but is there a lot more to go or is this just because we're short on time today? I still have like four slides left. Would it be... that's something well i'll ask what what uh reza what do you would you like gunton to continue you're on mute at the moment sorry because maybe we could just upload it and uh yes that would be that would be magnificent we can upload it because we are uh it's 10 50 we only have uh like one hour left given the rest time i mean that would be thank you so much uh it would be magnificent if you can upload it so we can we
We can actually get back to this. I mean, this is obviously super complex. I need to think about it. But thanks, thanks, thanks so much. Let's upload it. Oops, I think I lost all of you for some reason. Reza, you've muted yourself again. I don't know if you're trying to speak to us. My apologies. My apologies.
One second. Headquarter is basically, by that I mean, new center headquarter. I'm getting the message from him. or otherwise I would lose my job here. One sec. Oh, okay. Okay. Oh. Does anyone know how to forward messages on... Why people shouldn't get old?
Well, I think the problem has been solved. So, okay, my apologies for all the commotion and stuff here. So I have just a few comments. I will definitely get to all of the presentations today. So anti-philosophy. Actually, to be honest with you, I think what Gabrielle mentioned
is more to the truth than considering it as anti-philosophy. I wouldn't say that it's anti-philosophy. It is literally, they are still doing what Gabrielle told us, that they doing something they don't know what it is right but they don't care what it what it is it's something new but out of the con out of convention they can call it uh philosophy but i would say that uh literally um carnapp has a name for it this conceptual engineering is conceptual engineering philosophy? No, it is engineering. What sort of an engineering is? It's not an applied engineer,
and I will say why today. So it's conceptual engineering. Now, I would say that a more fruitful way to think about explication paradigm as conceptual engineering is not to understand uh whether it is still a philosophical um uh endeavor or not but rather understand whether how it can be uh basically used within uh the discipline within the discipline of philosophy whether whether and this is kind of completely would agree with that whether we need to uh what might call to be ameliorate certain stringencies with regard to the program of explication
if we are simply using it within the conventional philosophy or whether that it is impossible that's that's a fundamentally a different question but nevertheless i would say that probably Carnap is more interested to yes to have a certain kind of logical method uh explication to be a certain kind of logical method right logical uh pragma so to speak that's that can that can basically uh elevate philosophy the status uh of sciences or actually make it worthwhile to understand what is going on in sciences. But this might be what you said,
you know, basing it on national sciences, but I don't think that at that mature age Karnam would go with this sort of stuff. He's at this point a very mild manner philosopher who would actually say that, look, you can actually practice it at home too, right? And it's going to be safe, philosophical home, and it's going to be safe, but then you have to basically do certain kind of homework. You know, obviously it wouldn't be a sort of full-fledged explication. It would be a partial explication within the philosophical organ. In a sense, we, I mean, simple as that,
we can envision some sort of explication as a sort of rational explicitation, rational reconstruction of and basically diversification of concepts. For example, the idea of consciousness, simple as the concept of mind, it would be fundamentally fruitful for the philosophical enterprise to actually say what sort of consciousness are we talking about. Are we talking about rational self? Are we talking about phenomenological self model? Are we talking about global awareness system?
or at what level so that that creates a sort of confusion that could be avoided this doesn't mean that it is that sort of really what you might call to be mighty explication that karnab asks us but nevertheless this is something that you can you can practice it at home absolutely i think that it is absolutely necessary to do that sellers does that you know So a concept one, concept two of the same concept comes concept A1, concept A2, concept A3, so on and so forth, you know, to distinguish and to avoid aligning distinction between concepts at different levels of phenomena, right?
uh this this i think that does not require uh so to speak move to the quantitative concept something that only full-fledged explication requires that is really the the centerpiece of the uh the question of explication uh for carna moves toward quantitative concepts that that i think requires an extra step. I wouldn't see how philosophers can do that. You need to definitely have a certain sort of familiarity that only engineer or scientists can have with basically how, you know, with temperature. I don't
know probability is a good example you know that is as a frequent shilliest concept of probability and then he explicated two confirmation uh functions right or credence functions see parenthesis open h comma e equals a degree of confirmation degree of confirmation that that's absolutely uh something that requires a certain source of uh i would say a certain sort of familiarity with quantitative concepts and what philosophers usually are good at are qualitative concepts but but kind of wants demand something extra from philosophers at this point
So that that's that. Then I think the precision, I think precision in two ways, one in the sense that you talked about, and then precision in the sense of calibration. Right? We have it, for example, as I've mentioned, number of times, Young's modulus, or here the concept of density. What we do in explicating these concepts, young modules for basically brittleness or toughness, what we do here achieving is not precision in the sense that you were mentioning, which is correct, but also calibration of the concepts to a very local conceptualist
pace with regard to the system at hand. So look, at some scales, so we are talking about, as I mentioned, we are talking about the concept of toughness, brittleness. These are sort of trite, what you want to call to be engineering, one-on-one stuff. So the concept of brittleness actually functions or responds. might think of it as an aperture to the to the macroscopic uh what you might call the behavior of a steel beam but think about this that if we apply this to certain sort of observation reports
that we have made at for example this length scale at what you might call to be uh 0.005 micrometer as opposed to one centimeter which is basically the microscopic one so at the level of 0.005 micrometers and at the level of 0.0001 micrometer the concept of toughness with regard to the observations starts to kind of uh gets uh basically um starts to malfunction
it's like what uh mark wilson says that you know it's kind of like this uh that that you have basically uh that think of your concept as this map or as the ceiling where basically uh is under so much things going on, like this kind of metaphor of the house as a concept, we're basically under a stress, under conceptual stress, such that at certain sorts of scales or possibility of spaces, the concept starts to buckle. You start to patch up the concept of brittleness in your basement, right? That floods come from the toilet above the kitchen.
You try to patch up that one, and then your basement gets flooded, which is happening here right now. So there is always a sort of kind of futile attempt to patch up classical concepts, right? And precisely because a concept should be understood in the sense of precision, in the sense of calibration, should be understood as the possibility of creating more precise patchworks or conceptual possibility and spaces over a given phenomenon or set of data, right? such that you don't need to basically, your concept doesn't look like one of those 1980s genes
where you basically patch it with all sorts of the stuff and it looks cool. No, it doesn't look cool actually in philosophy. It's actually quite hazardous as Mark Wilson talks about it. So precision has calibration in that sense. And about narrow purpose, I wouldn't say that, you know, there's a dialectical thing going on in the task of explication, in the sense that, yes, there is a, we are actually moving toward a narrower space. But not just that, sometimes that narrower space allow us to unlock a set of problems which we couldn't otherwise unlock or even perceive as problems.
There is a great thing by, does anyone remember those two psychologists that Derrida talks about, about the crypt, the logic of the crypt? Famous, they wrote about werewolves and stuff. Always forget about their names. So they have this really nice metaphor that, look, concepts or idea generally should not be understood as master keys. In fact, there is no such a thing as master key in philosophy or psychoanalysis for that matter or any sort of human endeavor, intellectual endeavor. If there is a lock, you need to develop its keys, right?
sometimes you develop keys actually before understanding that it is it might actually leading to unlocking some uh unlocking a new territory so think about probability essentially what happens here he's narrowing down the frequency list uh the scope of the frequency this idea of probability but what it does actually through this narrowing down with create a certain kind of dialectical tension with a broad perspective of probability. Dialect, this dialectical tension then result in something fundamentally new. He actually lands or arrives at something what we can call a robot epistemology.
A universal learning machine, where basically rational. So he moves from Hume, which is empirical decision theory, to rational choice theory, and then from rational choice theory to inductive logic. Inductive logic, what you might understand, what basically we can think about it, is essentially a fundament upon which a new robot epistemology, formal universal learning machine, can be built.
precisely because it allows us to have criteria of rationality, various criteria of rationality, within systems of in various systems of inductive logic, understanding that it's hence enabling us to examine the applicability of such criteria of rationality for any sort of inductive logic or decision set of decision. problems, a la Ramsey's theoretical decision problem. And hence from that creates basically what you might call to be an idealized version of an inductive agent, which is basically a
universal learning machine, robot epistemology, so to speak. Another thing with regard to I think the Strauss just is so always into this sense that our experience that he just doesn't appreciate what Carnap is trying to do. Carnap actually doesn't give a shit at this point about experience, of my experience versus your experience. Experience is something that sort of comparison of content of experience was something that was only irrelevant at the time of Aufbau. And it was even then it was only relevant within the material mode of speech. But once we move toward logical, even as early as of our car talks about this, that all such polarities between subject and object,
my view, your view, experience, givenness, sensations become fundamentally misleading to understand the logical connections that hold or can be obtained within a system of formal language. Essentially, this is why there's another reason that Carnac thinks that epistemology has understood as a non-formal discipline can lead to huge amounts of confusions, particularly what he tries to avoid here since the beginning, actually, but particularly in the logical probability onwards, is that he does not want to retain any sort of confusion that can be basically
that can be caused by confusion of the distinction between psychological experiential epistemological and logical conceptual classes or conceptual systems. These are fundamentally different things. In fact, this is not really, Strassen's problem might be a problem, might be a problem, but that's not Carnot's problem. Precisely because he's working at the level of a system of inductive logic, where any sort of comparison of subject-object
polarity in the epistemological sense or experiential content would be fundamentally misleading to understand what is going on in the system of this logic of inductive logic Yeah, just, okay, so many things. I just love, I mean, I love all of you, but I mean, one of the people who always kind of like, kind of irks me in an intellectual sense is Delsha, which is, I love it. You know, I just want, here I am. I have written like 300 food notes on this thing.
Put my dairy paws all over it. But another thing that I want to say here, so rational, so talking about this whole idea, I think one of the things that my complaints about this sort of approach to explication in terms of fruitfulness versus similarity, this prioritization, which is, you know, it's actually a very brief chapter, that chapter, and Karnap subsequently ameliorates it, really tries to make it soft and possible so you can practice it at home too, right?
But even then, I would say that this whole idea of really fruitfulness, similarity, sort of connections between the elements of the two poles of explication similarity, fruitful next exactness, so on so forth. There are not as rigid or stringent as usually people understand, you know, rational reconstruction, both interpreted history of knowledge and programmatically charted the future of knowledge as a progressive replacement of intuitive notions by more useful more consistent more precise concepts so we can for example replace as we have been talking about our
vague subjective intuitive sense of hot and cold with the precise quantitative concepts of temperature. Yet, yet, yet, right? The quantitative concept also gives us many capabilities the vague concepts once lack. That's all good and great on the paper, as Delshot said, right? This obviously creates that sort of criticism that Delshot was talking about, but I would say that it is not as as straightforward as this. You know, the replacement process that we have been talking about in the sense of conceptual engineering is a piecemeal and iterative task or mission.
Now temperature remains to be explicated within a more general framework of concepts. Hence the dialectical nature of explication. Conversely, fruitful concepts are often developed long before we can understand how to fit them into a larger scheme or before we fully understand the problem they actually resolve, right? So Karnak for this example, this is the 17th century concept of a derivative, the derivative of a function, right? As a way of expressing the rate of change of a magnitude, which was used successfully by generation of physicists
and mathematicians, but only understood the rationally, that is rationally reconstructed we are talking about, only understood by Cauchy and Weistross, like a century or two later. So rational reconstruction, understanding in the sense of explication, hence is an iterative piecemeal, piecewise basically enterprise. It is not always tidy or unidirectional in the sense of replacing intuitive initially rather vague, sloppy, common sense, full concept, like more precise ones. So in each step, there
will be gaps, points, not fully explicit that have to be left for later reconstructions, you know, in the next step. And you can't do it all at the same time. So that sort of unidirectionality tidy a straightforward path i think it's not really what you might call to me explication uh because we don't have any example of this and carl knows that as well finally fixing the reference uh you know sometimes so fixing the reference here i think that there
was a good point that you mentioned but i have i have some sort of uh at this point i need to think about it more i think the fixing of the reference here is absolutely necessary from an engineering perspective rather than a philosophical perspective because if you don't fix the reference then uh then it would be completely impossible to do any sort of move toward more simpler or I don't know more exact more explicit more explainable concept hence you can't actually do really a better sort of a more robust sort of philosophy and more
detailed and more robust philosophy. Hence, you can't arrive at certain kinds of philosophical problems or scientific problems for that matter. But I'm simply talking about philosophy. I think that what Karnapp, as I mentioned earlier on, what Karnapp tries to do is to install some sort of engineering pragmatism with a pragmatic soul, engineering principle with a pragmatic soul within the organ or not philosophy in the sense that an engineer does this all the time does this mean that we can never actually understand how for example uh i don't know uh the metallurgical structure of this or that uh bridge no you have to fix certain kind of references with regard to
the concepts at hand the phenomena such that you can get the job done and then as i mentioned then then comes the idea of rectification piecewise approximate uh uh uh approximation uh in a recursive manner this is i think that william wimsa's idea of uh you know the major work of william wimsa's philosophy uh re-engineering it's called re-engineering philosophy um re-engineering philosophy for limited beings, a piecewise approximation of reality. This is exactly what explication looks like.
Limited beings. Look, we cannot think that this sort of, that sort of explication as an engineering, conceptual engineering enterprise is nothing, is, is but, has been made but for limited beings such as us, right? So it's always in the realm of approximation, piecewise approximations and rectifications, which is again is an engineering task and requires fixing of reference to initiate certain sorts of problems, certain concepts, but then coming back and rectify them. And to be honest with you, this isn't it? This is the whole point of the dialectical nature of philosophy in a sense, writ large,
that the future of philosophy always initiated by the present problematizations always comes back and hounds its past. So tiny break. Let's come back. Thank you. Thank you.
Sorry, I got overstressed with this flood, so I had to open a can of beer for myself. However, I cannot drink in front of the camera. That is just rude. You need to get a brown paper bag and just drop the cannon now. I can't hear you, Linda. You need to get a... Sorry, I don't have a headphone now. Am I already drunk now? I was thinking you need to just get a brown paper bag, and that would solve your problem, you know? Nobody would know what was in there. No, that would actually...
It looks very more suspicious than... Yes, it's a Nicholas Abraham and Maria to rock. Yeah, thank you. Thank you. Thank you. Thank you. Yeah, it's actually a really magnificent world. I really like it. So coming back to this or two weeks for coming. And tell me when everyone's ready. Actually, I'm really bad at keeping track of time today. I reckon, yeah, I reckon just crack on.
I think people seem to be. So one thing that really is important, particularly with regard to the problem, I mean, explication in general. But with regard to the explication of the concept of probability, and turning into the inductive logic C functions, confirmation functions, is that we are not actually, as I mentioned, as I tried to talk about, it's like a design problem. Hence, the engineering aspect of it. look, the best thing that we can think about it is that it is not a way simply to make
philosophy on par with the system of contemporary sciences, modern sciences, or that creates better concepts. No, it's, as I mentioned, it's a design problem. Design of what? Designs of new sets of problems otherwise unavailable to us from the perspective of our current concepts. So let me read some stuff here. You know, the language of explication, For example, in the sense of design, design problem, sorry, design of problems.
What sort of problems, right? So essentially, we want, we have, as we have noticed that with Carnap, there are always some sort of ill-structured problems. Some might actually be pseudo problems, which I don't think that Carnot's method purges them, right? Completely purge these from early on. But even within the remaining sets of problems that are not metaphysical pseudo problems, We might have, we might in fact, as by convention, by virtue of our methods, by virtue of the
languages we use, so on and so forth, we might instead have ill-structured sets of problems. So this is, in a sense, explication in a sense, is it resembles basically the transition from ill-structured to well-structured problems, and from well-structured problems to problems that couldn't be conceived if we had merely inhabited the realm of ill-structured problems, right? The philosophical problem of clarifying and systematizing an explicandum, like the logical
concept of probability, is analogous to an ill-structured problem, whereas the use of both syntax and semantic as tools to construct an explicatum like a quantitative concept of degree of confirmation is analogous to the use of problem-solving tools and methods to formulate a well-structured problem. When a pure inductive logic is applied for use in the mathematical sciences like theoretical statistics or information theory for that matter, like you know, the stuff that we have been talking about so long enough early on, very briefly. An inductive logic, qual logic, qual logic may have to be redesigned
and extended by the logician to better meet the demands of these sciences, right? So you see, this is, we are essentially, as I mentioned, Dilsad mentioned this explication in its primary form that kind of intended had a role in which philosophy can actually contribute fruitfully to sciences, right? And now becomes something, a fully autonomous entity without trying to basically bring back those sorts of metaphysical great outdoors,
lavish great outdoors, to kind of like sit on top of them and say that well, you know, that's what makes philosophy very distinct. No, he wants to purge all of this problem. He wants to, now that they are purged, he wants to show why philosophy is actually important. By creating this sort of, by installing this sort of engineering, conceptual engineering core within it, that primarily for, this is like middle-aged karma, but later on, as I mentioned, he basically gets softened on this issue. Primarily philosophy contributes something really powerful to science in the sense that I mentioned. But then the task of explication in
this sense as an as an engineering design problem uh carnal notices that it can actually serve philosophy first and foremost right by by uh what you might call to be arriving or designing not arriving not arriving actually this is a bad word my apologies if i use it are not arriving a new problem but designing new problems uh that could not be understood rationally reconstructed conceived tackled with seen so on so forth within the realm of the ill-structured
problems. So, as I mentioned, the task of the transition from ill-structured to the well-structured is actually not for the sake of clarity or from chaos to the order. Remember the early on early Carnap uh from from chaos to order uh essay uh chaos the ordered world uh essay no the thing is that he wants to do is that from the ill structure to the willest structure that sort of transition has as as its primary outcome the diversification of the structures in which
which we can basically see sort of problems we could never see. So that's, uh, Sally Haslanger also, uh, you know, the, what's that, resisting reality, she also talks about this, not in the, in the realm of probability, but something like gender and stuff, uh, you know, uh, which So I think that it's actually worthwhile to look at it as a kind of a parallel, even though Sally Aslan is more on the side of ameliorated reasoning as full-fledged conceptual engineering in Kahn absence. But yes, there is a certain sort of this idea that, so she talks about gender, talks about
the role of this, you know, gender in sort of different problems, and of course race. And then she talks about that this sort of attitude allows us to arrive at sort of problems that we couldn't see them as problems to begin with. That is a certain kind of, I would say that this is actually a very philosophical self-consciousness uh probably a little bit hegelian uh for my taste here that that what we arrive at i'm i'm using this merely in the sense of design of the problem
the explication sense what we arrive at gives us certain sort of possibilities of looking back at the world from which we have migrated right from from sort of concepts from which we have migrated that sort of uh what you might call to be self critical self-consciousness of the history of the concept you know is whether you like it or in the heart looks pretty much Hegelian, right, at the end of the day and fully dialectical. So yeah, so when a pure inductive logic is applied for use in mathematical sciences,
like theoretical statistics or information theory, an inductive logic or logic may have to uh be redesigned and extended by logician to better meet the demands of these sciences this is analogous to how the operational principle of a design hierarchy of problems can change over time especially as new technologies emerge with the increase of our scientific or engineering knowledge lastly there is for carter no correct logic as we have talking about principle tolerance 101 there is no correct explication of a concept of logical probability or inductive reasoning more generally but only better or works worse explications this is analogous to engineers who
satisfy rather than optimize yeah or satisfy and optimize both together satisfy certain sort of pragmatic problems at hand and optimize through that sort of satisfaction within that sort of framework that they are working within that locale of the problem space right design space explication is for carnal the ongoing gradual process of improvement of a system of concept designed specifically for clarifying the logical structure
of scientific theories and concepts. This is a kind of conceptual engineering. But conceptual engineering by all means differs from most what you might call to be a specialized forms of engineering, insofar as concepts need not to be tested empirically. Indeed, for Karna, pure inductive logic is not tested directly at all, but instead, we must stipulate our own requirements and restrictions, our own operational principles for what to mean for an applied inductive logic to be called successful.
logic can then be designed from the ground up to serve any number of scientific purposes, or for that matter philosophical purposes, just as an aircraft can be designed to serve any number of industrial, military, humanitarian purposes, right? The guiding idea for why this hierarchical account of engineering design is an appropriate interpretive framework for explaining and clarifying the philosophical significance Carnap himself assigned to his technical projects is that he conceives of logical syntax right broadly understood and semantics also as tools or
instruments chosen not because of the correctness or due to some highly theoretical process of justification but rather because of their expected capacity to satisfy our intellectual ends now this But this is a very, what you might call to be mature, mature form of Karnap. because we have seen
Carnap from previous seminar and the early sessions of this seminar has a certain kind of, what do I call it to be softening that not comes with compromise but comes with intellectual maturity. But nevertheless, still there is an enigma here. And that enigma is ultimately in the theory of probability. And I'm going to talk about it for 20 minutes, maybe 10, 20 minutes next session, you know, our last session. And then I open it, I will try to end up, would you be able to remind me Sunday or Saturday, so I can ask you
a very short reading material, right? Yeah. That you can read, right? So, briefly, I talked, I was going to say last year, last session, about, you know, the movements that Skarnak had taken with regard to the concept of probability, right, from a logical foundation probability, which was a reading material for the seminar, to the later works on probability and inductive logic. Now, imagine this, that within this sort of maturation, within the
concept of probability, Karnam essentially tries to do a lot of jobs, a lot of jobs that he has been trying to do all his life. But this is like, kind of like, what am I called to be a decantation, the distillation of all those sorts of philosophical ambitions, so on and so forth. First of all, within the maturation of his idea of explication, which coincides with the maturation of this idea of probability, explicating at one level the concept
of probability to probability one, right, degree of confirmation, and then further explicating degree of confirmation in terms of expected utility, so on and so forth. You know, that's sort of, as I mentioned, no unidirectional sort of explication, but the piecewise approximation of the concept of probability. Karnap, within that sort of transition from unexplicated probability to an explicated probability and then explicating the said explicated probability even further. Carnap shows
how the practical decisions involved with constructing an inductive logic can be informed by theoretical reasons. For example, reasons from empirical decision theory. In moving from empirical to rational decision theory and then from rational decision theory to inductive logic, Carnot is able to locate empirical and conceptual constraints for constraining the construction of an inductive logic such that it is suitable for the needs of those currently working on rational and then empirical decision theory. And here, so when we are talking about here about rational uh this rational decision theory we are talking about the idea of rational in the sense
that in the in the inductive sense right in the inductive sense and and at the in the in the inductive sense the concept rational is only relative to the sort of system of inductive logic you are using, the sort of language within which you are allowed to make certain sort of inductive moves or inductive connection. So this, so, but by no means Karnap is doing some sloppy move here. This actually, Karnap demands that the idea of rationality in the sense that people usually through the history from Hume onwards, have attributed or reasonableness,
have attributed to inductive problems or inductive method, ought to be relativized with regard to the use of the system of inductive logic. which means that uh this is you can you can actually think about it also in terms of philosophy uh i remember my dear friend patricia reed asked me on twitter that um it is best to go with the idea of reason rather than rationality because you see we have different sorts of rationalities uh i mean i'm not talking about what people call themselves rationalists uh or rational just like Hitler thinks that is rational, you know, actor. No, I'm simply talking about,
for example, the idea of rationality in different frameworks of rational choice theory, rational decision, Ramsey's rational decision theory, rationality in that sense, in this sense, or that. So essentially Carnap's framing of the idea of rationality or reasonableness in the inductive sense can also be redeployed within uh common uh philosophical uh dialogue uh and i i meant i i remember that i said to patricia that uh look it is actually more fruitful to talk in fact more about rationality than reason because reason gets a little bit bloated it's a bloated concept it's
It's all, has always been a bloated concept. Well, rationality, people demand you, force you, in fact, to explain what you mean by your, by rationality, by your rationality. So, so that force, that force that comes from the outside, the explicatory force to render it, what, what, explain the concept, make it more explicit, make it more exact. That is, I think, is a fruitful way to approach the sorts of what you might call to be dialogues. That was just a digression. So with regard to the idea of rationality in empirical and rational decision theory,
Carnap relegates the role of these normative and empirical reasons to the methodology of inductive logic, not to the inductive logic, to the methodology. So it is not that, what you might call to be these normative things of what my rationality is in the inductive sense is opposed from your rationality, how we can make it different, and they're all needs to be accounted for, right? This is not something, however, that he relegates the importance and significance of this problem to the
problem of inductive logic as well, but rather the method of the inductive logic. Carnap himself says in 1962 paper this, what the axioms of inductive logic themselves are formulating purely logical terms and do not refer to any contingent matters of fact. The reason for choice of the axioms are not purely logical. Thus, in order to give any reason, any reasons for the axioms of symmetry, I move from the pure logic to the context decision theory and speak about beliefs, actions, possible losses, and the like. However, this is not in the field of empirical, but of rational decision theory.
Right. Therefore, in giving my reasons, I do not refer to particular empirical results concerning practical agents or particular estates of nature and the like. Rather, I refer to conceivable in Italic, series of observations by X, to conceivable sets of possible acts, of possible states of nature, of possible outcomes of the acts and the like. These features are characteristics for an analysis of reasonableness of a given function, CR0, confirmation 0,
in contrast to an investigation of the successfulness of the initial or later credence function of a given person in the real world. Success depends upon the particular contingent circumstances. Rationality, however, does not. Rationality is relative to that system of inductive logic, right? That language, the framework of language. So the finding of a rational credibility or credence function can be understood in terms of the success of an inductive logic, logic, which has been applied using a particular set of resources, namely the success of hypothetical
agents working in a hypothetical world. Like the possible state descriptions expressible in an object language can be unambiguously formulated as a problem of applied logic. So this is Carnap's solution to Hume's problem of induction. He provides us with a set of conceptual resources formulated in semantics and logical syntax, and then uses these resources instead to explain when the credibility or credence functions derived from an inductive logic are rational, when they are reasonable, and when we can call them to be successful. this is how
we can describe carl's explicatory design conceptual engineering design solution to hume's problem within the realm of inductive logic in engineering terms, right, in completely engineering terms. The construction and design of a robot, an idealized agent within the context of rational decision theory, is an engineering project. The medium in which a conceptual engineer works, however, is not the physical world of electric circuits and hammers, but the world according to a logical
system which can be modified and tested using the instrument of logical syntax and semantics. The conceptual engineer constructs different requirements of rationality within this inductive logic. Empirical decision theory places constraints on what requirements of rationality and thusly what kind of robot epistemology will be useful in the empirical sciences while the formalizing of these requirements is an applied inductive logic means that the engineer will have to construct a pure inductive logic which is adequate for the task of designing such a robot for karnak rational or normative decision theory acts as a kind of
idealized buffer separating empirical decision theory from inductive logic understood as a kind of qualified psychologism rational decision theory allows karnak investigate all the possible ways in which idealized agents or robots or formal learning machines right can produce credits or credibility values for all possible conceivable states of the world relative to any exchangeable sequence of the agent's total available evidence which is basically all formulated within a particular logical system the entire project hence resembles the kind of hierarchy of
interconnected design and construction problems here the operational principle is to design a universal learning machine, a la Solomonov, or robot epistemology, or an optimal learning machine, as Karnak calls it, based on the reasonable rules of rationality for inductive thinking, which may eventually be used to help guide the decision-making of actual persons. Applied inductive logic provides us, in this sense, with the formation of a well-structured problem from the ill-structured problem that is Hume's problem of induction. So Hume's problem of induction is by virtue of its purely empirical nature is an ill-structured problem
to begin with. I wouldn't say vague here. I'm saying ill-structured with the idea of how we have talked about the idea of a structure in previous sessions. ACARA provides us with no guarantee that a completely adequate or the optimally reasonable robot epistemology or learning machine will be found. This is, as I mentioned, this is a process of satisfying rather than searching for the truth, right? So this is actually the same thing goes with Salomonov. So people say that, well, Salomonov is a universal learning machine. No, this is fundamentally an engineering problem.
That it is about satisfying. We are not going to talk about good engineers. We are not going to talk about satisfying truth. We are trying to test. We have arrived at a new set of problems through our transition from ill-structured to well-structured problems that allow us to test a different realm. It's what you might call to be an instance in world-making, that we have, in Italy, recognized what we thought we had already recognized.
Okay. No questions taken. I'm not going to take any questions today. Next session, we are going to do that. And thank you, Anta, for being so generous at doing this for us. No, I mean, yeah, I benefit the same as everybody else. Yeah, we can do it like a court, you know, you present your defense, and then the next week we come back. Sure, sure, absolutely. Yes, that would be nice. And then, of course, you know, I will give, I don't know, like five minutes of, you know, kind of wrap up thing. And yes, it would be nice to just have a kind of a conversation going on. Yes. I mean, but look, I mean, it's just so many things that we can talk about.
And we haven't gone through even scratching just the surface. but I mean I'm glad that you all have been reading picking up you know some good stuff or kind of you know finding faults in some of the arguments so on and so forth I mean this is what a good class should be but yeah and don't forget to ask me for a text it will be short text I don't want anyone type of beer you drank okay i will i will send you guys a youtube unfortunately any of you okay check the youtube of dennis hopper
in blue velvet he asked uh kyle mclaughlin what sort of beer do you drink and then he said something and said, fuck that shit. Unfortunately, I'm drinking that one. Yes. So let's get together. Thank you so much. Absolutely magnificent, magnificent contribution by all of you. And yes, I will try to, through our question and answers, also go over some of the Turing stuff that I promised. okay love you all thanks good luck ciao ciao bye bye