 So, und jetzt begrüßt bitte Rainer, ein Informatiker in Philosoph, der mit uns darüber reden wird, was die Informatik nicht kann. Okay, we have a sound back. Ja, herzlichen Dank für diese... Ich hab noch ganz diese Einführung. Genau, ich will heute sprechen über die göttliche Informatik. Man kann das göttliche natürlich auch an Gänsefüßchen stellen. Das ist so ein bisschen ein Experiment, wo ich so ein paar Sachen mal zusammenbringen will. Wenn ihr nach dem Talk rausgeht und sagt, die eine Hälfte wusste ich schon, und bei der anderen Hälfte war alles komplett falsch, aber diesen einen Gedanken, den fand ich spannend, dann habe ich meine Mission heute erfüllt. Wenn wir mal sehen, wie wir das hinkriegen. Ich finde es immer ganz wichtig zu wissen, wenn man jemanden hat, der davon steht, zu wissen, aus welcher Position er spricht, besonders weil wir... Okay, we have audio problems. And we're going to find a laptop and start a stream, and I'll translate from the stream. And so we'll need, by the way, welcome to this talk. As much as we can translate of it, it's about divine computer science. And your translators are Zebalis and Nengvi. And we're trying to get the stream started as soon as we can. We're talking about information and some amnesty international, so as the claimer. Ich spreche aber jetzt quasi für jemanden da. Selber, ich habe Philosophie studiert, habe ein bisschen Philosophie der Wissenschaft gemacht, Sprachphilosophie, Philosophie of mind, habe mich dann die politische Philosophie begeben, habe mich mit Informatikgeschäften gemerkt, das ist sehr interessant, da gibt es ganz schön viele Überschneidungen. Und habe jetzt einfach mal das Zitat, was hier auch am Eingang des Saals steht, rangeworfen Computer science is no more about computers than astronomy is about telescopes. Das heißt, der Computer ist an der Stelle eben ein Werkzeug, um Dinge zu tun, der, und dieses Werkzeug hat bestimmte Eigenschaften. Und diese Eigenschaften sorgen dafür, dass man es auf bestimmte Arten verwenden kann und auf andere Arten wiederum nicht. Ich will mal auch noch darauf hinweisen, dass insbesondere Ada Loveless im 18. Jahrhundert, kann man so einordnen, Charles Babbage, die Difference Engine, beim Übersetzen einer mathematischen Maschine an der Stelle schon überlegt hat da, wenn wir mit mathematischen Konstruktionen irgendwie Objekte aus der Realwelt darstellen könnten, dann könnte man ja auch, wenn die Maschine mathematisch darauf auf diesen Zahlen rechnet, auch irgendwie Objekte verarbeiten inhaltsicher Art. Es war meine eigene literaturische Herr, so eins der ersten Überlegungen, wie man quasi mit Computer nicht nur rechnen, sondern auch Sachverhalte irgendwie bearbeiten kann. Meine aktuelle Ausgangslage ist, dass die Informatik für Wünsche und Sehnsüchte nach einfachen Lösungen gerade herhalten muss. Und ich als Informatiker bin da so ein bisschen kritisch, welche Wünsche da herangetragen werden und auch welche Kolleginnen und Kollegen aus meiner Zunft auch aktiv daran mitarbeiten, diese Wünsche aufrecht zu erhalten. Man kann auch noch sagen, bei der göttlichen Informatik ist vielleicht ein bisschen vorgegriffen, aber die Mathematik und die Physik und die Biologie, die haben das alles schon durch, was die Informatik gerade so durchlebt. Gerade in der Physik ändert sich vielleicht der eine und die andere so an Bildern, wo gerade das nukleare Zeitalter ausgerufen wurde und selbst der Herd in der Küche wurde mit kleinen nuklearreaktoren betrieben. Und sozusagen, das war so ein bisschen die Idee. Da war dann alles nuklear und das nukleare war sozusagen die Lösung für alle Probleme. Jetzt sprechen wir eben über das Internet, künstliche Intelligenz, Blockchain und so weiter. Ich habe das mal als Informatik so ein bisschen zusammengefasst. Der Vortrag soll bestimmte Denkweisen explizieren. Wie gesagt, wenn ihr sozusagen protestiert, dann protestiert, also ich würde ungern mit sozusagen brennenden Holzscheiten aus dem Haus gejagt werden. So, Investigations are continuing as to why the sound has dropped. It's apparently the mixing board for the whole room upstairs that has to be checked and then our switchboards here in the translation cabinet. And we're trying to get an alternative source going and we'll translate from that. So, now we're talking about the Internet, artificial intelligence, the Blockchain and what not. Just talk, it's going to make clear some thoughts. So please don't, you know, run me out of this building with pitchforks. I'm just gonna, I'd like to point out some alternative modes of thought. And yeah, so I'm gonna try to navigate this topic the way I see it. So, with quick steps we're going to go through computer science and then we're gonna talk about ideas and images of the world and of human people. Then we're gonna talk about economies, about unholy alliances and the role that politics plays within all of that. And then some literature for, you know, for their interest in this topic. So, computer science. Well, the basic of computer science is the computer, you know, the universal machine. It's not the technical device necessarily, but it's a Turing machine that can emulate other machines. And so you write software, for example, Algorithms, that define certain heuristics. So computer science is interesting because this sort of science, after it built all of those structures, it says, oh, this is interesting, you know, how does this work? How, you know, we have networks that scale and we have black box testing as though we wouldn't know what we've built. So this is some sort of, you know, Mesh-Science, das doesn't actually know about itself all too well. So this is part of computer science, as well as reflecting its own theoretical base. So there's theoretical computer science, you know, Effectivity, data structures, what can be computed, what sort of claims can be made about applications, what can we say about programs, but also this theoretical aspect also contains the social effects of computers. And so within computer science, there's also, there's always this figure of the freak, you know, someone who reads books and you know, it's always like, ah, don't do databases like this, you know, just think about the consequences and everything. And so the promise that computer science makes is always that well put problems can be solved by computers and then the results will get better and better using computers. And the products that at the end come out of that on the other side. I'm not going to talk about this whole, you know, knowledge, this scientific approach, maybe a little bit. These products, you know, they're tools for all different sorts of applications. For example, image processing up to AlphaGo, you know, autonomous cars, Facebookbots and the basis of social scarring that we've already heard about today. And also climate simulations and emission testing, that's all sort of connected. No, that's the sort of bandwidth we're talking about here. And so our current modes of operation that I want to talk about today, it's not very technical, it's like machine learning, just the databases, blockchain, you know, can we have smart contracts, cryptocurrency and whatnot and voting. The question that, you know, I want to deal with in this talk are the models that computer science uses and then applies their tools to do with these models. So, what gets modeled and what are the limits of set modulation? So, I want to talk about the limits of computer science. And then a further question is the application of those tools and then we need to talk about de-contextualizing and recontextualizing. We're talking about technical systems that have inputs and outputs and of course we can, you know, have phone calls together in some sort of club and record them. And for example, we can measure time within a sprint and then use that information in all sorts of different contexts. But of course, the application is very important. So, for example, a police database, you know, that's a prominent example. So, there was a database in Germany called a politically motivated left and so the data privacy person back then, he was concerned with that. And there was two viewpoints, so the security agencies, they thought that, you know, if there are people protesting nuclear power, they are already a danger to the state. Different people, you know, put different models to these databases. And so the data itself through all of these different use cases could get us quite different outputs. So, for example, the due registry in the Netherlands, when the Nazis came, they were like, oh, yeah, thank you very much for, you know, preparing all of the data for us. So, for example, funny story, actually, the introduction of SAP software, you know, they always say that free computer scientists get sent there and then 30 advisors go to the company to restructure the company so it fits the software. So, again, recon textualizing. So, the question again is how do we build models and what sort of systems do we build. And now to part two, how do we view the world and how do we view humans. So, I've said that, you know, computer science is about, you know, modeling objects, modeling simple states, so a computer can deal with it. And so, basically, we have two problems with that. Mathematical modulation of, you know, for example an image, how do we get the pixel values, the color values, you know, how do we get the information to, how do we get information that is processable. So, maybe the core of all of this is abstraction, abstraction of distinctive features. So, for example, I want to build a system that models friendships, human behavior, human relationships. So, what is a human person? What is friendship? How can they connect with each other? And, for example, are there only like two genders available for choosing and, or is it, you know, is it a free input field. So, all of that affects how people use a certain system. I'm sorry, but not just in Papua New Guinea going to people asking questions about their cottages and questions like, what can you see on this photo? The size doesn't matter, the response is no idea, we don't know. But, well, that's your cottage, isn't it? But my cottage isn't as shiny as that is out of wood. And they went on to the next person asking things like, what does this picture tell you? Does that tell you anything? The size and the material should not matter. And the response then was, well, still we don't know and confronted with the statement that this is your cottage, the response was, well, I can't go into it, so it can't be my cottage. So, you can take this further and say the realization was that the example of natural depiction was clear to those ethnologists because they knew what was relevant and what size in a photo is not relevant. The material is not either, but what is important, how many windows are there, color is important, think like that. So, in this place, it's not so simple to really find an appropriate model. There are many aspects linked to it and the modeling is quite decisive and the question, what is interesting and what's not, are relevant. The activity simply isn't there. It's not objectively clear what is to be considered relevant. Although in computer scientific systems that is often quite well defined. The second pointer or thought about how you build models of the world to then process these models is a nice thought experiment from the colorblind, about the colorblind neurobiologist, neurobiologist. Now, if this neurobiologist knows everything about the brain, what does she know about the perception of red if she is colorblind herself. So, how can you model facts or relationships that you don't know about yourself and that is quite important for systems that you build and that might be used in different cultural contexts. So, the thing is this shift of meaning or shift of aspects that we want to process and that we don't want to process towards models that a computer, a universal machine could handle is a very difficult one. And the terms we use in computer science itself are the machine learns or she knows something or it has recognized a symbol, that football or it thinks, it is thinking if the spinning symbol is shown. So, systems decide something, they feel something and that is something you have to be very careful with for the reasons that I've just talked about. Now, this all sounds very soft and vague and the question is what do we all make of all this and there are two or three current trends that are very clear with the answers to these questions and that is why I'm calling this computer science the one is the transhumanism and just briefly going to touch upon that. Transhumanism has very clear answers we just hack everything into the system and then say, faster is better, longer life is better and remembering more is better. So, not what is the cottage made of but we simply define this everyone wants to live longer, everyone wants to memorize or remember more. So, this human improvement that of course is the question you have to pose isn't really there anymore the question what is better isn't really there anymore but a lot is lost that way also. Then, artificial intelligence I will not distinguish between general or domain specific AI has answers to those modeling questions which are quite interesting too one is well, human is an information machine and everything is quantifiable information with a certain finite resolution and all aspects of human lives are computable so it's kind of from the other way around from behind you get to the statement that everything that we can model in a quantifiable way all the other way around the world ultimately consists of this information so everything is quantifiable and what's quantifiable is mathematically modellable so there's nothing really that does not fit in so these questions are just choices between A, B and C but it's no real decision at this point and these viewpoints both kind of taste like cybernetics perhaps that one of the other of you will still have in mind and that had signals like the whole world consists of control circuits and there was that slogan of Mathematizing Biology you would hear well we all know a thermostat at the radiator you set a certain temperature thermostat will open and close depending on the room temperature so it will approach some kind of equilibrium and this image was then going to be used for the human circuit as well and for human thinking as well and you realize at this point that it approaches it goes in a somewhat similar direction to those approaches that I talked about but there have not been any satisfactory consequences so ultimately the interesting results would have come at a point where the real world would have been too complex to be modeled with these circuits and that means because at this point totalitarian approaches remember everything is information, everything is describable these are totalitarian approaches to modeling that seem to provide a closed answer, a final answer and everyone that contradicts those are just simply nonbelievers or not yet believers so what they have in common is the reduction to what is computable and what is computable is then supposed to be real and processable and then of course you have to take care of the difference between computability and precision, you can be very precise but calculate the wrong thing so if you have an example a result that is exactly 15 digits behind the decimal point it could be completely wrong still so these totalitarian approaches mostly um menschliche Sachverhalte modellieren kann ist dann die Physik das Beispiel, das man mit Modellen ist ist Physik das ist eine Kollektion von Partikeln die man modellieren kann das ist das ultimitale Modell das man in der Computing-Maschine modellieren kann also als eine die Gemeinsamkeit dieser Ansätze die approaches die approaches die approaches die technologische Community ist die Reduktion das ist das was sie haben in common nicht in dem Sinne, dass wir ein komplexes Welt haben ein komplexes Staat und wir projekten das auf Modellen aber was ich hier übernimmt, ist die Information von den Fakten selbst bevor sie das Modell mapen also eine unerwartete Ignoranz von Dingen, die wir überwinden was wir überwinden, die ich ein Data-Fetisch nenne weil die Dinge, die du modellierst sind letztendlich mapend in Daten und die Komplexität ist dann weiter reduziert wenn du die Information, die technologische Systeme mit Freunden oder in der Gesellschaft haben dann ist es also nicht ganz fit in diesen Modellen, mit denen du arbeitest weil oft die Gesellschaft wie ein Set von Individuen oder für sie selbst und dann fit in Modellen und dann natürlich mit Objektivismen und das Modell es klingt ein bisschen weig und flotend aber du kannst es runterbauen mehr Data bedeutet mehr Knowledge um mehr Data zu haben und zu linken, mehr Informationen, mit denen du accessest mit denen du dich als menschliches Data als menschliches Data ist dann eine syntaktische Existenz und an diesem Punkt zu haben mehr Data ist natürlich ein Ende itself jetzt, weil du die Systeme feeden und die Dinge kombinieren und wenn du viele Versuche von Gedanken hast ich weiß nicht, wer von dir sagt ok, ich sehe es so die Welt besteht aus welch definierter Information jetzt, please hand up everyone who believes that ultimately everything is defined informational structure and there is nothing else there ok, the courageous ones have shown up of those that believe it i mean thanks very much anyway and between these reduced data objects the context of human use is kind of losing color if you consider an old fairy tale about a village society the way these people interact and the symbols that are exchanged to define group membership and things like that that you can interpret in different ways and you can more or less reduce it further to what the robotist Holrashi Ishiguro said he said that when he builds his robots if he is at home he is so tired once he gets home from that he will just watch TV and that of course a robot could do for me because for the children doesn't matter whether I or a robot is not playing with them I'm not going to say that this automatically fits together but if a world view or a world model looks that way then of course it becomes very simple the world image that is something that is very easy to model and build a computer that processes it and I am also not talking as I was alluding to in the introduction which we probably missed as translators because the sound was gone now these purely philosophical thoughts and this technology belief is spreading rapidly the singularity university in Silicon Valley trains out a class of well-funded brainwashed entrepreneurs each year to build the technologies needed for the transhumanistic vision so there is a lot of money involved and these kinds of thinking the kinds of thought approaches are well monetized and put into existing software system which then unfolds their effect on society now to put it in a less drastic way and a less critical example I am kind of jumping ahead with the context now to show you the parallels the blockchain technology as a concrete technology calls itself a trustless ledger so it is a general database that anyone could look at and there is no central authority involved that you have to trust and currently it seems to be the solution for just everything and anything from Microsoft up to banks everyone is doing research on it what I found very nice was this little chart here where you can think what you want to do, what is blockchain something useful for that or is it just something you can deal with with a normal database so these flowcharts that brings it back to the earlier point the interesting question of course is to work with the blockchain in a reasonable way and to really distribute that trust you have to make sure that the people that work with that blockchain are more or less similar in computing power as we see with bitcoin at the moment if one company in one country simply buys so many strong systems they can then determine what the future for that system should be so the question is has the trust simply shifted outside of the technological view through that technology and now located elsewhere this trustless ledger refers to the technology but which other actors do you have to trust in what ways so the question is who controls the machines and how strong are they so now an outlook on business so a few people in the room might not like this but I am going to talk about neoliberalism nice introduction in the last century there was a fight between various modes of economies and so communism liberalism I am going to pick neoliberalism and point out why so we have the Chicago Boys in Chile during Pinochet's rule and then Thatcher in the UK starting in the 70s after Britain Woods and monetary value wasn't bound to the gold standard anymore so what I mean by this is austerity and privatisation as modes of this economic model and the subservation of all sorts of areas of life under this economic rule so we have individualisation psychological influences so we have game theory rational choice approaches inputs that make a human being do something and there is always rational choices that these human beings come up with to produce a certain output so you can already see that there are certain parallels in this mode of thought how we can influence human behaviour but this trend spread globally throughout the 80s this understanding of economies and governance so Chile was sort of laboratory for neoliberalism it was privatisation of the health insurance system privatisation of retirement funds privatisation of the school system in Chile they made it a lot harder they even outlawed workers unions so the idea was to get more investments into the country but the result was that the economic output rose a little bit but the middle class was reduced there was a growing gap between poor and rich growing a number of people out of work we can of course talk about what that means degradation of the overall level of people's health and we can also see this sort of development in Germany and a lot more in other countries so maybe as an aside this is way more important in the UK and the US because in the last few years we can see Jeremy Corbyn, Bernie Sanders grüß daily struggling with democracy world view world view world view thank you thank you thank you thank you viele Finances zu handeln, nach all diesen Neoliberalismen Reduktionen. Jetzt haben wir diese Data-Solutions, die quick-solutions promissieren. Zum Beispiel, die weltweit größte und die weltweit größte Räum- und Taxi-Service. Sie haben gar keine Räume, sie haben gar keine Autos. All das kann nicht falsch sein. Die ekonomischen Konzerns, die ich talked about, fit diese Computer-Science-Motor-Thode, die simplistischen Modelle, die simplistischen Weltviews. Wir können auch die Silicon Valley Ideologie nennen. Wir können bestmöglich Produkte kaufen, wenn wir auch einen positiven Ausdruck auf die Welt nennen. Das ist etwas, das Harley-Davidson hat gesagt. Es ist eine digitale Revolution, das ist, was sie sagen. Sie sagen, die alte Welt ist weg. Sie haben alles verletzt. Auch die Sozialstaat. Das stellt sich die Frage, dass die Welt besser wird. Die Welt wird besser werden. Aber wie genau? Und für wen? Was ist das mit dem Staatspenden? Wir wollen nicht nur die Computational-Systems bauen. Wir wollen auch diese Empfeßung, um die Welt besser zu machen. Diese Frage ist, ob wir eine bessere Welt haben wollen. Es raises eine sehr wichtige Frage. Wie wollen wir leben? Manchmal legt sich die Frage, wie wollen wir Tücher? Wie wollen wir Hunger umgehen? Wie wollen wir Hunger umgehen? Das raises eine Frage, wie wollen wir Hunger umgehen? Wir haben die Probleme. Wir haben die Probleme, dass es dafür eine App gibt. Die Frage ist aber so ein bisschen... Hunger und Lobster, das war eine kleine Konfusion. Denn die deutschen Worte sind sehr similär. Es ist ein Toolfettisch. Die Frage ist, welches Problem unseres Lösungen fit? Die Antwort ist, dass es eine App gibt. Es ist nicht komplett absurd, es zu formulieren in so eine heretische Weise, weil man über Ueberhop oder Liftschuttle hört, die Taxikampern, die eine gute Idee haben, zu sagen, dass wir große Fahrzeuge haben und dass wir nicht die Fahrzeuge haben müssen. Wir haben die Fahrzeuge gefordert, wir konnten sie auf fixen Routes ran. Die Leute konnten in die größten Fahrzeuge reinkommen und die restlichen Fahrzeuge dachten, dass es Bassen sind. Es war ein sehr erheblichem Moment, wenn Silicon Valley plötzlich die öffentliche Transporte veröffentlicht. Aber das Funnste ist, dass es ökonomisch funktioniert. Google, Facebook, Amazon sind einfach Hewikitas in unserer everyday life now und Start-ups, mit diesem Weltvielfalt, das ich gesprochen habe, sind strong capitalists, venture capitalists, und bekommen eine politische Unterstützung oder eine businesspolitische Unterstützung. Und sie können dann diese Businessmodelle backed by a lot of finance into the world. And when you then have issues like the German law coming into the picture, you will have swastikas being pixelated. But the question also, on the other hand, is what is being blocked, although it would be allowed in Germany by German law, such as Nippo images, when will people demand their rights for those. But don't quote me on that, please. And the description, therefore, is at least according to some theorists who call Silicon Valley the useful idiots, thinking that these people build interesting things, but simply door openers for much more interesting people like insurances or other finances. So the question is, what remains of the disrupt ideology? Also, ultimately, this means that public bodies use products that were initially made for commercial use. And that is, of course, quite handy, because you have a quantifiable measure for success. But the public bodies work somewhat differently. Public infrastructure like public broadcasters, storing things at YouTube, because they don't have storage capacity. And simply have those restrictions that the commercial vendors impose. You have other things like public infrastructure, sidewalk apps being developed, health system optimized up to the improvements of care for the elderly. And that, of course, is often cheap or even free, because a lot of data is generated and the smart city becomes the city as a service. And I squip there. Now, sometimes I believe that politics, if that's an entity, is becoming somewhat lazy and maybe even on a global scale and then may have people that say, okay, I have solutions and everything seems to fit together. And even secret services are restricted by a certain logic and that says the world is getting more and more dangerous and we need more data. But the people that actually work with this data and try to extract useful information, in other words knowledge out of that, say that we are drowning in ever more data, but no one is stopping that flow. Okay, I'll continue to this. Now, with these ever stronger coupling, there are questions because businesses that you more and more tightly integrate into the public space, these businesses, of course, have to fulfill certain criteria or properties that they do not have. They are not democratic for one thing. They have certain internal processes in their own Dynamics. For example, if Waze, a routing service says, okay, well, there's a building site here, we'll just reroute traffic because it looks nice on the map, but then you notice these are very small residential streets that are not supposed to be used in this way and which are not able to carry the weight of a lot of traffic. So you have certain things that public policy and self-administration would be aware of, but they do not exist in those businesses. And the question then is who makes decisions and who has the final say. And with the power of the companies, the overwhelming power of these companies, the question is how do you deal with that? What are the consequences? And that is where the role of politics comes in. If you now return to the divine computer science and ask what can computer science do or what is it afraid of, or what are you afraid of? Wofür hat man vielleicht, what are you afraid of, then I would say, are you afraid of AI or are you afraid of businesses that enforce their own goals through AI? So the things that I've said that you apply to these is control slipping out of our hands. Is it control of technology or is it the control of organizations that use that technology? And then of course the whole thing fits together in a very different way and you can think of it differently. Because, and that is where the circle somewhat closes, games or economy are something that is nice to model because it's clear what is good. You win the game or you make a profit in businesses. A-B testing, things like that, it's very easy to cover with criteria. But if you have things like social involvement, conceptions, transparency, fundamental rights, then suddenly it gets very, very difficult to say has this been adhered to or not? It's a very complex question or answers to these questions are very, very complex, which we see in the European Data Protection Regulation, for example. Yeah, and the purpose of politics then is of course to have an option to make decisions and clarify responsibilities and discuss these. And it is about the systems that we use to talk about the design of the systems that we use and not just their results. So, if we say that, hang on, if we say that we want to protect the weak, then it's a very complex thing at this point to define what that actually means, what the goal is and to then deal with that, deal with the fact that systems can become inefficient, because you want to take everyone with you, because it's not all just about efficiency and profit. So that means, at this point, I have to make computer scientists deal with the issue that the requirements to their systems are towards inefficiency sometimes, about distributing power, which is always there, to ensure that it's not inhuman or against society. So it's not just about if you have a position where the limits of technology are to be looked at. It's not about being hostile towards technology, but about technology serving the humans and the society. So, from an IT point of view or from a computer science point of view, we do like efficiency, but it's not the ultimate goal. And lastly, I just want to say that there are positive examples, because I largely had this large approach. Small examples of the smart city strategy in Barcelona, for example, it functions in a very participatory way. Highly participatory systems remain in the control of the people affected and because the systems are operated by the city, there are no operational secrets and you can look at this very easily. GNU TALA, which I think is still at experimental stage, it's a payment method, which is anonymous. The people that makes the payment is anonymous, but the dealer that takes the payment can cryptographically prove that the payment has been made, which makes it taxable. So that is the anti-model to those Cypher punks that say we don't want any state at all or ask the freedom of information portal where you can demand your rights. The other one is called Sue the state. So if you document what the power structures are and how you want to deal with them, that kind of reflection lowers computer science from that divine state into a very mundane but very fertile tool. Thank you. Okay, we have a quarter of an hour left for questions. If you do need to leave now, please do so quietly and try not to walk in front of the cameras. And otherwise we have 13 minutes to stay here and think of questions. You know the game for microphones Q and we have questions from the internet too and we'll start directly with a question from the internet. The question is to what extent simulation models are a basis for political decision making? Das ist eine sehr, sehr gute Frage. Oh, that's a very good question. It really depends on what is modeled, what is simulated. So there's a lot of social science models that try to figure out who do I look at when there's a question from the internet. All right. So that try to model individual human people but that for me as a computer scientist I'd like to talk to social scientists and see what they have to say about my methods and work together with them to find adequate models for their views. And so really talk to the people that deal with these problems and not repeat their mistakes. So this might be a clue and the right way to deal with that. Person at microphone 4, are you looking at your smartphone or a Q-ing? Okay, well I am both actually, but I can ask a question. Nerdwise, I am a bit of an Asimov fan and you have these three robot laws there. You talked about how machine logic and biological logic are not completely agreeable or compatible and I agree with you there. But there are theoretical approaches with which psychology can be described quite well and psychological interventions can be made. For example in psychotherapy, organization psychology you can make progress there. So in a way the person viewed as a system of personality traits or an organization as a system of various stakeholders. So I do concur that this atomization is counterproductive for a cool societal development. So the question now, I am looking forward to the question, says Rainer Reak. How do you view this? And hang on, hang on. And which approaches, what approaches of... of cybernetics in a global view of both biology and technology, which of these do you still find productive? So, what you said at the beginning, that was quite interesting and I would have said something even if you hadn't posed the question afterwards. But I believe the crucial point here is to always ask what effects do I hope to achieve with this model. So if we talk about psychoanalysis, psychology and using that, that's not wrong. But what I'm talking about is this works on some level but we don't use it everywhere. So, here it's also about using certain models but keeping in mind that we're dealing with models. And if problems arise and we're all the time we're in some sort of critical feedback loop, is the model still adequate for our purposes. And if it's not, then maybe it's, you know, there might not be an adequate model to... model to talk about the thing that we were trying to look at. And so that's the end of that totality finally. So this, we can end this complex question. And regarding cybernetics, I believe I can make a general statement about that. We'd have to have some sort of concrete example if I understood your question correctly to critically reflect these requirements and that's not some sort of one-size-fits-all answer. Microphone number one, please. I had a certain problem of certain problems with your talk because it had an extreme amount of detail depressed into it. Philosophy, early examples, ecology, you kind of put everything in there and I was missing the kind of main point. And to be honest, I would have hoped that you would say something about, focused on the limits of technology, of informational technology, because you said it was a mixed science that gets involved in every other science. So is it about the general limits of science as a whole and you talked about consciousness, can you model that? But ultimately isn't it about the fact that so many people are now talking about superintelligence and these are very serious scientists that say in 25 years we'll have that and what's the point about that? Aren't these the real threats that we have with this kind of talk too? This is a very interesting point. Superintelligence in 25 years, that's been the case for quite a few decades by now. Yeah, I don't want to water this down, but the limits I've tried to show here, they depend on how the things we want to look at, that we want to work on, how can we model them mathematically. So if we have A-B-Tests, if we have click rates, we can do all of that, if we want to measure that. But if I want to measure customer satisfaction, then I have to critically think about if somebody clicked five stars. Is that really customer satisfaction or did I really only measure how often people click on five stars because that'll make the window go away as soon as possible on my computer. So this sort of critical distance for me is the limit of computer science, where we have to ask ourselves, are there decisions for what we can make, for what belongs to the model, what we can model and what we can't. Regarding your second point, I had, so thanks for your question, that's exactly the reason why, why I can't find the slide right now. Okay, here it is. Why on this slide up top, it's not slide 42. So fear of AI or fear of corporations that use AI to achieve their goals. So is there some sort of super intelligence, but after, with all the knowledge I have of computers, of course there's the possibility, but right now I don't see any reasons to believe in the coming super intelligence. So I like to ask, I get the concept of super intelligence, but what are really the signs of its coming. So improvements on the hardware side and the possibilities of AI, that always grows in a linear fashion. And so people always feel that we're, just a step short of exponential growth, also records well, of course. But if people can provide proof, show me some signs for this being the case, I'd like to be convinced of that, but until I see any signs for that, I really, I'm more afraid of corporations using AI to achieve their selfish goals. And so this is a political question. This is not a technical question. We've had that throughout history, savory child labor, until someone politically put us up to it. Okay, the internet please. Are there plans to have the most important results of cybernetics involved in a kind of poly contextual logic? What does to access mean? I didn't quite get that context. Are there plans to have the most important results of cybernetics involved with relation to poly contextual logic? So I'm not really familiar with this topic, but again, I'd say if there are adequate models to model the things that we care about, then these limits of computer science that I've talked about, it only ever applies to singular individual solutions, but we can't apply one size fits all model and expect to have great results on all ends. Number four, please. Hello and thank you for the talk. And I come from a somewhat constructivist context and ask what can actually be done. And I realized that the term power was pervasive throughout the talk, and that could mean that everyone has a feeling that they have a freedom of decision, but still certain power is being applied. And the question therefore to you is, firstly, do you know any kind of views of information technology systems from that point of view, or do you consider it a correct approach? Das finde ich eine sehr, sehr schöne. This is a very interesting question. In fact, there are these sort of principles. So I've named them here, right? There's small or even large projects that raise these exact questions. For example, Christian Kühner, once coined the term power of cooperative systems without power. Without power. Without power. Without power. Without power. This sort of distribution of power should be inscribed into hardware and software. And it shouldn't be, then you shouldn't be able to take this distribution out again afterwards. So that's, you know, when we use IT systems, that's something to think about. And in my opinion, within the political context, we always have to be able to understand what happens and we always have to have the ability to influence a certain system. So maybe, well, it depends on the application, but in general we might talk about a peer-to-peer system, but in general we might talk about a peer-to-peer system, so that might be my first hint here, or like Knuthaler, the example I gave, there's a verification from one side, but not from the other. So, yeah, there's approaches there, definitely. Okay, that was it. An applause for Reina, please. And hopefully an applause for us interpreters too. This was interesting, thank you.