Brain Food for Pioneering Spirits: What is actually behind the terms robotics and automation, and how are they reshaping the world of work? In Room #858 of the Deep Talk Club, under our overarching theme “Pioneering Spirit with brAIn,” the group digs into rule-based robotics versus intelligent, decision-based automation, who owns the data, GDPR as Germany’s brake, and the deeper question of whether we even have the luxury of asking whether we want any of this. Listen in on the examples that came up and the perspectives that emerged in dialogue…
Note: This session was recorded live in German as part of the Deep Talk Club, so the video above is German-language audio only. What follows is an English translation of the conversation, lightly edited for readability — the back-and-forth between the moderator and participants is preserved, but the original timestamps and speaker names have been left out.
A wonderful good morning to you. Yes, today we continue with the topic of robotics, automation, and the world of work. And under that heading, we want to take a look at what’s actually behind the terms robotics and automation, and how all of this affects the world of work. And yes, I’m really curious what impulses or examples you’ll bring in too. I’ve also prepared and brought along a bit of material, and I’ll gladly start with that, and then we can see what thoughts emerge from it. First, I looked up on Wikipedia what’s actually meant by the term robotics, how it’s understood. And it says, and I quote: “The field of robotics, also robot technology, deals with the attempt to reduce the concept of interaction with the physical world to principles of information technology as well as to technically feasible kinetics. The term robot describes an entity that unites these two concepts by implementing interaction with the physical world based on sensors, actuators, and information processing. The core area of robotics is the development and control of such robots. It encompasses subfields of computer science, in particular artificial intelligence, electrical engineering, and mechanical engineering. The goal of robotics is to establish, through programming, a controlled interplay of robot, electronics, and robotic mechanics.” That was the Wikipedia definition. And if we now look at the term automation, I found that it’s used in the context of standardized processes and leads to increased efficiency by using various technologies to reduce user intervention to a minimum. And what’s special here is that when we bring these various technologies together — things like artificial intelligence, automation technology, understood as cognitive automation, machine learning, business process automation, and robotic process automation, abbreviated RPA — the result, when we look at this combination, is what we call intelligent automation, abbreviated IA. And that allows us, as users of these systems, to no longer have to think about the process, but about the results or the goals. In the future, connecting interfaces won’t give the user any headaches either. Today it’s still the case that we sometimes have to think about how all these systems we’re using actually harmonize with each other, how they can be connected, whether it works — sometimes there are challenges — and this combination of technologies will make it increasingly possible for us to connect systems with each other essentially at the click of a mouse, without having to do much else. That’s already partly possible today, and it’s going to keep increasing. That means, in this context, we’re talking, for example, about an intelligence that discovers processes in need of optimization — so it acts on its own. We’re also talking about an intelligence that learns and is therefore adaptive. And we’re talking, for example, about an intelligence that eliminates problems before they occur — so it works predictively and predicts problems based on probabilities before they even happen. So that, maybe, as an introduction for now, and I’m curious what you all have to say about it. Maybe some of you know these fields well and can bring in a few impulses, maybe some concrete examples, so we can see what emerges together from this.
And with that, as every morning, you’re warmly invited to join us again this morning. For anyone joining for the first time today, a quick note that we record the room and that it gets published afterward — so joining automatically means you agree to that. And then we have three small room rules. First, a profile photo where you’re clearly recognizable, with your last name and at least a sentence in your bio, simply to make sure these are serious contributions and not sock-puppet trolls. Anyone who doesn’t want that for whatever reason, wants to stay anonymous or similar, is of course also welcome to just use the chat. And on that note, I’d also like to pick up on something that came up in the chat yesterday — well, actually the day before yesterday, I think, we talked about AI and developments and effects on the labor market. And toward the end — though it was already too late for me to pick it up, I only saw it too late — there was also a discussion along the lines that in the future there might be something like certification, certificates that are, say, “AI-free” or something like that. I honestly had to smile a bit when I read that, because that’s still coming from our old way of thinking. Because exactly the example I raised — that in the future we’re only going to think solution-oriented or results-oriented, without having to think much about the process anymore in a lot of places, because certain systems in combination will take that over for us — and if I then look at something like certificates or whatever, I can only say, well, first of all, the question is, how would you even verify that? I can’t verify that at all. So a certificate like that is, in a sense, worthless. And apart from that, it also can’t prevent someone from claiming they created content themselves that maybe wasn’t created by them. You simply can’t verify it — verifiability just isn’t given here. And the other thing is, similar to copying or other things we’ve already touched on in various places, the question is, don’t we also need a certain shift in thinking here — a rethink regarding “we’re not allowed to copy, we’re not allowed to plagiarize”? I was recently talking with someone about aspects like copyright and so on, and I just asked, well, but maybe we don’t even need copyright protection at all — maybe we should reconsider whether that’s even necessary. How cool would it be if we simply had this information accessible and could build on it further? That would also be a way to think and act differently. So, just some first thoughts thrown into the room, and now I’m curious what impulses come from you. A wonderful good morning, dear Marc — what do you say about it?
Good morning everyone, and a great start to the week to all of you. I’d like to add two terms — you’ve already explained it nicely and quoted Wikipedia for us. And while looking into the topic I also found that engineers make a further distinction: robotics is a huge topic, and there’s also a distinction made between automation and mechanization. Automation is understood as replacing human action, while mechanization is the extension of human capabilities in terms of strength, size, and endurance. And what I find really exciting — I had a bit of time yesterday to look into the topic, and we’ve already done a lot of rooms, and when you look into the topic and use our big search engine, it really depends on your point of view. I find some absolutely terrible things, terrible, terrible, terrible. But I can also take a different position. I’d like to start with the positive side of the topic. There are studies, and you find plenty of them online too — people are afraid of robots and so on. But there are also facts now, and you always say this, question it — is the fear even justified? What’s actually happening? And in the Asian region it’s been found that in these Asia-Pacific regions, there’s hardly any unemployment. Everywhere in South Korea, Japan, and Singapore, which are already very advanced in automation, it hasn’t led to unemployment — quite the opposite, to more employment. And the second question, which I think came up in the room description yesterday, is: who’s behind it? Robots are definitely a key technology, and I also found it really exciting to look into who’s actually behind it — that’s not quite the topic of this room, but when you know it’s a key technology, who’s behind it? Among other things, we had a really, really great company in Augsburg, Germany, that was the European market leader in robotics. It’s now 100 percent Chinese-owned, and in Germany there’s really only one company left that we can point to that’s still involved in robotics. Otherwise Japan and South Korea are ahead of us, so that even if you don’t dig into the statistics and just see that Germany is still right up there when you google which manufacturers actually make robotics, when you dig deeper and look at other statistics, that company the market finds unfortunately isn’t a German company anymore at all — it belongs to a Chinese owner.
Yes, wonderful, thank you so much. There were already several aspects in there. Let’s bring Jürgen in directly too, and see what other aspects come up, and then we can draw cross-connections. A wonderful good morning, dear Jürgen.
Good morning, dear Yasemin. Good morning, Marc. Good morning, everyone in the room. I’ll jump straight onto the stage so I don’t lose the thread. I’d like to anchor myself to two things you presented in your intro. First, I recognized, according to your breakdown, that there are three levels: there’s automation without any further attribute, there’s basically automation, there’s robotics, and there’s intelligent automation. I’ve secured those three levels for myself for our discussion. And regarding the distinction you made, I’d like to add one thing: a distinction is made between robotics and intelligent automation in that the first part, the robotics subfield, runs in a hard-wired, rule-based process structure. It runs — I don’t know if any of you have been to a VW plant or a BMW plant, I subjected myself to that as a total outsider, to look at these robotics lines — and it’s absolutely impressive, but it runs down to the millimeter, exactly according to very specific rules. The distinction to intelligent automation, and you already touched on this in terms, dear Yasemin, is that this isn’t based on rules but on decisions, which presupposes intelligence. And that brings me to a topic I was involved with for quite a while, namely process analysis and process optimization. And if I look at these two positions — how do I automate, how do I roboticize my business processes — I logically arrive at the conclusion, as a foundation, essentially the foundation, no, not just essentially, but unconditionally, that I need data. And that’s the subfield I worked in to some extent — process mining, process analysis, and analyses of which data arises at which support points of this process. In order to then, and I say this quite deliberately, in order to then make a decision — which path do I choose for robotization: are my data qualitatively good enough, and my algorithms good enough, or only good enough that I have to make it rule-based, or are they good enough that I can even build in loops or control loops with quality criteria that then decide how this automation continues. A very exciting topic, especially given current developments. I just want to share this with you in connection with our recent rooms: Microsoft has, according to those in the know, managed to more or less strong-arm SAP into incorporating Microsoft’s bots into their standard applications — bots that go in the direction of artificial intelligence. And the first success report from SAP has already been published. So who’s setting the pace here, my dears? The pace is set by whoever owns the data. And then we’re back at our big topic, digitalization. Thanks for listening.
Yes, wonderful, thank you, thank you so much. And that’s really exciting at this point, because the data aspect is so relevant, also in relation to the aspects we’ve touched on, like data protection, which plays a really big role in this context. And there’s really a lot to discuss and think through here, because on the one hand it obviously has very positive sides — that, in the interest of data protection, not too much data can be collected, or can’t be stored permanently, or whatever. There are various areas here, and depending on the constellation, retention periods differ, and so on. And on the other hand, these intelligent systems function precisely by using this data. And the question is, to some extent, if we, say, can’t collect data in certain places — aren’t allowed to — while others are allowed to, in inverted commas, what does that mean, conversely, for a development on, say, a societal level, for Germany? Jürgen?
Yes, you’re raising, if I interpret you correctly, dear Yasemin, the key topic of the power of platforms — please correct me if I’m wrong. That’s what I meant with my terminology — power lies with whoever holds the data. And under data, I also subsume its use under certain algorithmic combinations. And that’s exactly a key point I fully agree with. That’s the great challenge, I think, with institutions like Microsoft, Apple, and Google, who sit on — I always say — these enormous grain fields from which the future’s bread gets made. And whoever owns these grain fields and tends and cultivates them determines what bread we eat. And let me throw in one more thing, which was also a topic in one of our earlier rooms: from my own experience in process optimization, process optimization, which is the foundation and also creates the data basis, also runs, like everything else, under an economic input-output cost-benefit lens. I just want to say, I won’t simply nod along to the idea that our whole world will in the future be fully automated or roboticized — in my view that’s not a productive way to think about it, because there will always be the possibility of seeing the economic benefit more on the human side, especially when it comes to physical routines, less so mental routines, rather than handing them over to these very expensive and, frankly, quite high-maintenance systems. That shouldn’t be lost from sight. Thank you very much. I’ll happily switch over to Marc now.
I’d like to briefly note again that we’re recording the room — anyone who comes up on stage automatically agrees to that — and we have three small room rules for coming up and joining the interaction on stage. One is a profile photo where you’re clearly recognizable, first and last name, and at least one sentence in your bio, simply to make sure these are serious contributions and not sock-puppet trolls. Anyone who doesn’t want that for whatever reason is warmly invited to share their thoughts or questions via the chat instead. Just a reminder so you can adjust accordingly or participate via chat. Marc, you wanted to follow up on this.
Yes, I’d like to offer a different angle on the topic. As I said, I looked into this on Sunday, and depending on which angle I take, I find different reports, and my opinion shifts quite strongly as a result. I came across an interesting report from the EU — there’s an EU project called Reela, and it’s not about what Jürgen mentioned, process optimization when we’re talking about production — of course that exists too — but there’s also a Danish professor, and a lot of people are working on where the future might lie in other areas: what could collaboration between a machine, a robot, and humans look like, where the human is supported? For one, in healthcare, there are now systems where people with spinal cord injuries can walk again, because robotics and the machine take over certain tasks, in a hospital setting. And to make that possible at all, there are people who team up and talk explicitly with end users — not just engineers or people who say we need to optimize processes, but people who walk through the hospital and say, look, we have this robot now, and then they realize, the robot is great, but for the patient to actually be able to use it, this piece that helps the patient has to go on their back — it has to be strapped on. Are there processes we can simplify there? Or, take the restaurant industry, for example — they have a shortage of skilled workers. Well, what can someone with a restaurant do? They definitely need a cook, there’s no way around that, someone has to make the food. But if they can’t find anyone to serve anymore, then maybe at some point small robots will be driving back and forth, even recognizing me. Do I think that’s great? No, I don’t like it. I find it much more personal when I can go up to a waiter. But before I could never go out to eat in Cologne again, I would also accept having my food brought to me by a robot on wheels. What I mean by that is, it’s not just about saving money everywhere in the sense of the manufacturing process — there are also a lot of processes that are really about how machines can support people in the future. And the last point I found for myself — we have an aging society, and a lot of people don’t have children anymore either, the birth rate is dropping in Germany too. Who’s going to do my grocery shopping for me later on? There too, there will probably be machines eventually, where I can call the grocery store that’s still around and say, I’d like some sparkling water, and if there’s no one there to bring it to me, then delivery robots will be out and about, where I can pick it up downstairs. So I don’t see it as just black or white — the field is so big that there are surely areas I can’t even imagine yet. These are all just illusions and wishes for now, where I have to say, wow, good thing that exists, that helps me personally and doesn’t hurt me.
Yes, thank you, thank you so much. And the angle really is relevant here, because depending on how we look at it, we always arrive at different results. And you just raised this aspect of the aging society — we recently also talked about leadership shortages, skilled-labor shortages, and so on. So, just to confirm what you just said, this isn’t only about the cost-benefit factor, but also about the fact that positions that currently remain unfilled might, viewed long-term, remain unfilled precisely because of these technologies, because you might need fewer human resources at that point. So if before, certain identical tasks were maybe distributed across ten employees, it might be that, through the new technologies I can now deploy, combining automation and intelligent systems, the reduction of routine tasks and the intelligent development of solution options, problem detection, and so on, could create a way for the skilled-labor shortage issue, among others, to be absorbed to some extent. So, viewed from that angle. Then, if we pick up the data aspect again, there are different perspectives there too. On the one hand, you could look at it as: those who have power because they have the data are simply ahead of others, or you end up in a dependency. You could discuss whether the monopolies need to be weakened somehow — can that even succeed, and how would it have to be shaped? Because it’s not enough to have this discussion just within Germany or Europe — even if Europe decided to do it, but the rest of the world doesn’t join in, it wouldn’t help at that point either. So these hurdles need to be seen too. And at the same time there’s the whole general discussion around data protection. That means, not just now but also in recent years, what losses or development potential have we, as Germany or Europe, already missed out on because we didn’t allow this data to be collected, given data protection concerns? That’s one question. On the other hand, of course it’s also worth discussing, well, but what would it mean if all of that were lifted and data were just collected everywhere — isn’t that also a danger, and what form of democracy would develop out of that? Is that even still a democracy at that point, with all these aspects and stages to consider — centralization, decentralization, and so on are all aspects that play into this. And we’ll definitely revisit that, to discuss it later on a political level — we’ll have rooms on that in a few weeks too. We can already touch on it now and see clearly what a can of worms the whole topic opens up, and that on different levels it’s really about looking at this and thinking it through. From an entrepreneur’s perspective, I can say it’s definitely a problem — obviously, if we can’t collect data, we can’t keep up in competition. But if we then discuss it on a socio-political level, we have different challenges to master. And that shows how complex this topic is, and above all that we’re not acting alone but always in an interplay — we have to look at the whole thing globally. That means, if something gets banned in Italy, say, or something gets banned in Europe, the question is, what’s the consequence of that? Does it mean the others stop too, or do we just cut ourselves off completely on our own? And the question is, how far can you even prevent this, or what does it mean in consequence — or do we, to some extent, even if it’s painful in one place or another, have to go along with this development because we simply can’t slow it down? And I’m curious what you say about that, Marc, Jürgen — do you want to follow up on that?
Yes, gladly, Jürgen, and then Marc. First of all, heartfelt thanks, dear Marc, for your remarks — you actually brought us back to the original topic, the connection to the world of work, and thank you for that. And secondly, dear Yasemin, I could hardly keep up with all these connections you drew, thankfully, the complexity that this topic makes clear once again. And forgive me, I’ll throw in yet another topic — when we talk about the world of work and its effects, in my view we’re also automatically talking about the effects on education, upbringing, and the school system. And if we assume that in the future too, the world of work, in its dimension, impact, and shape, remains a central political task, as it is now — it’s not for nothing that we have a labor ministry and an education ministry — then for me it’s always a requirement to see these two subfields in connection. What I mean is, I can’t demand — based on our current state of knowledge, we’re heading into a future with artificial intelligence, yes, with consequences for entrepreneurship, yes, possibly protection against data monopolization — while forgetting that, for this world of work, we need suitably upgraded, in the truest sense of the word, upgraded resources. And that turns this topic into an absolute monster topic. Thanks for listening.
Yes, absolutely. Thank you, thank you so much, Marc. I’d like to add two more points — first, regarding the effects on the world of work: if you ask which tasks robots are actually taking over now, there are studies showing that a lot of work is boring, dirty, dangerous, and difficult. Robots handle that. If that’s the case, that’s a great thing. If it leads to a complement where the human being no longer has to lift heavy things and doesn’t get back problems because there are machines that do that, then that would be a wonderful complement in that case. And on the topic of data protection, that’s very, very important, and it’s going to keep the courts busy — there will probably be specialists for it in the future too. And there are also a lot of companies, for example in cancer research — cancer research needs a huge amount of data, and because of data protection, a large company in Germany can’t advance its cancer research in Germany as specifically as it would like to, and is now relocating large parts of that research to the UK in order to keep researching in the field of cancer there.
Yes, thank you. And that’s also a really important aspect. That doesn’t necessarily mean the whole company relocates, but rather a relocation of certain functions — headquarters-level relocation, so to speak — carrying out things like data collection in a region or country where that’s possible without problems. So these are aspects too. That shows very clearly, in these concrete examples, that people find ways around things. The moment we try to regulate and restrict, there are always workarounds people take in order to find new possibilities again in the interest of their own company and their project. And accordingly, the question is how sensible such regulations even are at that point, and whether we’re not bringing even more disadvantages upon ourselves — disadvantages that already show up today in the development of the world of work, with the skilled-labor shortage and so on — whether that isn’t perhaps even reinforced by it. With that, I’d like to welcome Susanne into the round. A wonderful good morning — what do you say about the topic?
A wonderful good morning. I was triggered by Marc’s remarks regarding automation in the world of work, in areas where it’s hard to lift, where it’s dirty, where it’s loud, and so on. And I have to say, I really support automation there. I come from the field of workplace safety — I advise companies as an occupational safety specialist. There are already quite a few improvements I support, simply to relieve the burden on employees, to preserve their health to that extent. That means, for example, we already have demographic change, as mentioned earlier — I see more and more that the average age in companies is going up rather than down. There’s a lack of young talent — especially in the trades or other manufacturing businesses, that’s really a huge topic. We have, for example, a roofing or carpentry business we work with — we looked at what options there are to keep the employee from constantly having to go up on the roof, working at height, which is also one of the most common causes of fatal accidents, and we moved forward with drone technology, deploying drones with cameras to check what’s going on on roofs — is there maybe a leak or something that doesn’t require constantly climbing up. In manufacturing businesses too, a lot of other automated processes have replaced humans, simply out of the need to make workplaces more ergonomic — not necessarily just for economic reasons, but so employees are relieved too. Because there always still needs to be someone behind the machine who operates it, maintains it, keeps it running, feeds it, whatever. And so it’s quite a balancing act. So I support it from an occupational-safety perspective, that it gets automated. From a data-protection-officer perspective, there are always snags that hold us back. GDPR is really a massive brake — but you were talking earlier about collecting data. The problem isn’t just collecting the data, it’s evaluating the data. What do we want to extract from it, and who’s supposed to do that? I keep seeing that we collect an incredible amount of data in the world of work regarding prevention — I collect all sorts of information about dangerous situations, near-misses, first-aid cases, and so on. Depending on the size of the company, I sometimes have an insane number of reports, and someone has to sort through what’s actually a report that needs attention and what do we do with it. On that side, in my view, no artificial intelligence can evaluate that at the moment, because it’s simply far too complex. And there, as Marc also said, we need to keep an eye on not automating everything, because people need a good education. School education in Germany isn’t necessarily geared toward the effective world of work. And so, when I look at what we also have in everyday life, there are so many construction sites right now, so to speak. From my perspective, I see it as a huge problem too — where do we even start, who’s supposed to take charge of this so that this automation, data collection, evaluation, and then the actual utilization gets implemented effectively in the world of work? At the moment I only see that a huge amount is being thrown onto the market, a huge amount is being tried, but the effect, in my view, is still very, very minimal. In the area where I’ve done this, I do see a good effect. Also in medicine, what’s already been mentioned — that people with spinal cord injuries can move again, or move at all in the first place. But otherwise, across the board, we’re still far, far away, and we’re behind from childhood on already.
Well, my first impulse is to ask whether that’s maybe more of a German problem, what you just described, because other countries manage it, and other companies manage it too, especially in the Anglo-American world — not just to collect data, but to know exactly what to do with it, how to deploy it, and how to actually evaluate it. That means, quite clearly, if there are problems here, then either the right resources aren’t in place to handle this data properly, to use the right tools for it, and to feed it back into AI to work with it again. But these are quite classic things you’ve described that obviously work in other companies and other countries — that’s exactly why they’re miles ahead of us.
That’s exactly why I say GDPR is basically our giant brake. Yes, I see it that way too, that Germany has this problem — I do advise international companies too, and there it runs completely differently. So yes, that’s why I say, not globally, but we here in Germany have this problem. We’re way behind from childhood on, we’re unbelievably backward in that respect, there’s nothing like it.
Yes, and that makes this issue clear once again. On the one hand there are of course the big players who are already quite far ahead, and on the other hand there are also a lot of companies abroad that are still relatively fresh into it too. But we’re lagging behind everywhere, no matter what comparison you look at, totally behind. And the longer it actually takes to have these discussions and get into action, the bigger this gap becomes — and that shouldn’t be underestimated either. And then again this aspect that Jürgen also raised with education — we keep coming back to this topic of education. Yes, it’s a political task, among other things, to look at this education system and become active here. It has been in the past, and it’s going to become even more so now and in the future. And far too little is happening here, in inverted commas, or far too slowly, let’s say, but also too little, because digitalization often just means, and this is an observation you can make, that some iPads get ordered that maybe can’t even be used because there’s no internet access, or whatever. If you look at schools, it’s really — well, it makes your hair turn gray, because apart from the fact that teachers might need support and so on, it already fails at the most rudimentary things — you really saw that a lot at the start of Covid, that schools sometimes didn’t even have internet access, so the devices were there once they’d been ordered, but still couldn’t be used or deployed. So these are quite fascinating phenomena in this context. And I think, Jürgen, you wanted to follow up, if I saw that correctly — Marc, if you want to say something too, go ahead.
Yes, first of all, heartfelt thanks, dear Susanne, for your remarks — that brought me to another point, and please forgive me for stretching this tent even further, namely the connection between automation, the world of work, and the world of education. The meta-level for me, which I already touched on in the artificial intelligence room and our future shaping of everything around us, runs under the fundamental question: everything we do, do we even want it? And a key crux, dear Susanne, that you pointed out, is this “we” — the problem in connection with this innovative technology is certainly this issue of “we,” because we decide — if we decide alone, as Germany or even as the EU, and act against what’s in inverted commas a technological mainstream through corresponding regulations, then, and I’m being deliberately provocative here, we’re choosing to forgo a potential advantage in the future shaping of a modern world of work. That question is fundamental for me — what do we actually want? And so, for me, this chain, this conceptual chain of automation, world of work, world of education, should be extended, essentially, by a “world of meaning.” What is the meaning of life going to be in the future — something we’re constantly confronted with especially through the recent generational discussions, that there are efforts, not least regarding work, but also regarding retirement, to give it a completely different meaning than what we — or what I — experienced. I don’t want to speak for everyone. Economically speaking, over the last two to three centuries, through the industrial revolutions, we’ve always moved to a higher level of economic utility function. That means we’ve had an extension of life expectancy, a higher health status, a higher education status. Our path always went upward, and our society has changed from a needs-satisfaction society into more of a needs-creation society. Along the lines of, sure I have an iPhone, but when the next one comes out I have to have that too. Sorry, I’m probably drifting off now, but essentially, once more, this huge topic for me always carries the underlying question of where this path is actually supposed to lead, and whether I even want that. Thanks for listening.
Let me push back quite provocatively here. From my perspective, the question might not even be, do we want this at all, but rather, do we even have the luxury of thinking about whether we want it or not? So aren’t we actually under a kind of compulsion here, without the luxury of choice? And I’d like to bring in a very concrete example. We just experienced this with electric mobility. Various German companies really resisted and refused, and that has rather led to us having a problem today because of it, and being thrown far back in our development, while other countries have overtaken us many times over when it comes to developments in electric mobility, for example. And we’re not talking about electric mobility today, I just wanted to bring it in as an example. But I do see the danger that if we’re on the same horse here, so to speak, asking ourselves, do we even want this — for us to be able to ask ourselves that question, all countries globally would have to pull together. And they don’t. And the moment they don’t, that would be the precondition, in my view, for being able to ask such a question — if they don’t do that, then the question for me is, isn’t this a luxury we’re discussing here? And we probably shouldn’t even allow ourselves to ask that question at this point. Jürgen?
Yes, I notice, maybe there’s a hidden hint there too, dear Yasemin, that I talked too long. That was actually the background to that pointed statement, this “we” that Susanne also raised — this point that we can only… and of course we can opt out, dear Yasemin. Of course we can say, we’re deindustrializing, which some political currents are indeed vehemently pushing for right now. Only, you have to live with the consequences. You can do anything — you just always have to live with the consequences. And that, for me, is the result of the cognitive process: what do I actually want? Because it means making a decision after weighing what consequences that decision carries with it. And quite correctly — let me put it in a nutshell, hopefully there’s a fitting saying for it — capability is the measure of permission. And permission, in this environment, is our status, not just economically but also politically and socially, that we’re no longer able to act as a single country, but are increasingly dependent on looking beyond our own borders and seeing what’s actually happening around us.
Yes, absolutely, I’m completely with you there. And if we were to actually say, we’re willing to pay that price as a consequence, then of course a lot of things would follow from that — like, how would our people in this country need to be trained, what would we need to take care of, education context is a relevant aspect here too, and so on. Then, regardless of whether we want it or not, one thing becomes massively clear through the changes now taking place: it’s not just about initial training anymore, but increasingly, especially when we look at the world of work, about retraining too. So how do people need to be supported now, for example, to be able to acquire and learn future-proof skills, overarching skills, so that classic initial training alone is no longer enough — and accompanying these changes in companies at the same time — the extent and shape of that then also determines what, for example, Germany decides to do. Marc, you wanted to follow up too.
Yes, absolutely. I’d like to pick up on “do we want this?” So many questions arise from that. Do we want this? Who decides that? What are the consequences? And what could the alternatives be? And then a question — how do we finance this? And I think none of us in this room would be upset if someone said, you now have to work less, so you have much, much more free time, but you don’t have to worry, your life and our prosperity are still secure. And I’m definitely not a fan of communism, but still, these are also philosophical questions — if a company, for example, multiplies its profit tenfold through automation and has the option to then lay off ten times as many employees as it needs, then you have to be legally allowed to think and talk about whether the entrepreneur then also has a responsibility for that money earned to flow back into society, yes or no. If you ask the entrepreneur, and you asked me, I’d of course say no — why should I let profits I’ve earned flow back? But that, then, is again the task of politics, and there you see how complex the whole topic is. But fundamentally, we need to become aware — and I think you raised this too — do we want this? Do we even have the luxury of deciding on that? And if we say, we don’t want this, then I also have to stand here and say, okay, dear Jürgen, we don’t want this, we don’t want a robot. We lose our prosperity, we lose touch with the world economy. That also means you no longer have money for electricity, and if the meaning of your life is to sit outside and look at trees and listen to the water, then that’s what you do, but then you freeze and you don’t have a house anymore, you sleep in a tent. You then have a very meaningful life, but no more luxury and no more prosperity. And those are, well, discussions we need to have, and above all, entrepreneurs mustn’t be allowed to decide on this alone — the whole society needs to be involved, stepping in and making sure that the world doesn’t end up with, I don’t know, 100 or 200 rich people and everyone else just poor.
Yes, absolutely, and a lot of the systems we’re talking about — and this will also become clearer over the coming days — also function with, for example, ideas of centralization, and so on. We’ll pick all that up in the coming days and weeks too. And then, of course, a logical follow-up thought would be whether we don’t need to move much more strongly into decentralization — away from this globalization and toward a more decentralized approach, and then also, within Germany for example, or within Europe, bringing back various things we previously outsourced. So all of this is genuinely relevant here, right down to, when you hear about developments where a company, for example, is considering not relocating but actually selling itself abroad — and thereby, for example, the qualities we still lead in today, in areas where Germany is still ahead, would fall behind again as a result. There have been many comparisons in recent years where we, as Germany, were pioneers in certain areas simply because we had this know-how, and through the sale of companies or takeovers of companies from abroad, that has contributed to this know-how no longer being here anymore, and accordingly we have to buy it back expensively from outside, which triggers another chain reaction. That’s one thing, and the other thing, which we already touched on recently, is also relevant here again — that we, well, I’ve lost my train of thought now, doesn’t matter — you might want to add something too, and then we’ll already be close to the closing round. Marc, Jürgen, Susanne, if you want to add anything else, go ahead. Marc, I saw you — and then we can slowly move into the closing round for today, because we only have eight minutes left. Time really flies with these highly complex topics, it’s incredible how fast it goes. Marc?
Yes, my closing word would be, I’m leaving this room, as so often, with more questions than answers, but I’m confident, and as long as we keep the discourse going, I keep noticing that suddenly new doors open again and again. Thanks for the room today, and I wish you all a great start to Monday and the week.
Okay, that was your closing word at the same time then. Let’s continue in order — Jürgen and Susanne, what would you like to highlight? What question marks came up for you? What are you taking away from today’s room, Jürgen and Susanne?
Yes, as always, my heartfelt thanks for all the contributions made, and for your moderation, that always has to be said, and I mean that gladly. And it’s shown once again that, for this room, for these topics you open up, dear Yasemin, thank goodness, a key challenge is always the complexity. And I also take away, from a subfield I spent years working in, that I’m picking up new impulses. Thank you for that, and I’m looking forward to the next stages we’ll have, and I hope, and I assume, that you, Yasemin, will keep guiding the threads of this overall context so skillfully in the future too, because that’s really a challenge. Thank you very much.
Yes, thank you, thank you so much, and I’m afraid the complexity isn’t going to decrease either, but will tend to increase, because with the different daily room topics we’re also opening up further construction sites, so to speak. That means, for example, tomorrow we’re going to look at blockchain technology — that’s yet another technology, and that’s the exciting thing, looking at the whole interplay of it all. And then I’m very, very curious what discussions, what insights we end up with, and also from the perspective of, well, we can of course discuss it on a societal level and so on, but the question is also, what influence do I personally even have, and in which area do I actually move? And that will be another exciting question we’ll deal with. So I’m very, very curious where we end up in the end. Susanne? Are you still with us, Susanne? We can’t hear you yet — your mic is off, in case you can hear us.
Yes, sorry, I’ve got someone standing in my office who wants something from me — I unfortunately can’t answer right now.
Alright, good to know then. Thank you, thank you so much. Well, let’s wrap up the room for today then. I found it really exciting, and tomorrow, as I said, we continue with blockchain technology. We’ll look at what’s actually behind blockchain technology and what its fields of application are, both in the past, today, and in the future — so where the whole thing is heading. And that gives us another area of technology, so to speak, where there are also massive developments happening, and we won’t be looking at it from the currency perspective tomorrow, but really talking about the pure blockchain technology itself — and at some other point we’ll also have a room specifically about digital currencies. So just a quick mention of that on the side, and I’m really curious what examples you might bring in tomorrow too — maybe you know one or two already, and then we can open up various aspects again here, and there will surely be a lot of topics here too, like environmental contexts and so on, climate contexts and so on, that need to be considered as well. So the discussions here will surely stay exciting, and I’m curious what insights, or what question marks, we’ll take away from tomorrow’s room to start with. With that, thank you so much for joining, and hopefully see you again tomorrow morning at eight, here at Deep Talk. Until then — ciao.
