German President Frank-Walter Steinmeier Discusses Digital Technology Ethics

All right. Hello, everyone and welcome. How are you? Let's try again. How are you this morning? [Applause] A very warm welcome to the Berkman Klein Center, to Harvard Law School on this sunny but windy and slightly chilly day. We're really delighted to have you here. My name is Urs Gasser. I serve as the executive director of the Berkman Klein Center. I'm also on the Harvard Law School faculty with my colleague, that I will introduce just in a bit. And of course, I am very, very pleased to moderate this special conversation about the ethics of digital transformation. And I'm of course, even more pleased and actually honored to welcome the federal president of Germany, Frank-Walter Steinmeier.

Hello.

[Speaking German]

[Inaudible]

We are joined by a wonderful group of colleagues and experts. And I will-- if you are not mad with me, I will just briefly introduce you, and we will get to know each other a bit better as we go along and talk about your work, and of course as we engage in the opening conversations. So this should be interactive as much as we can. Eva Weber-Gurska is an ethicist, a philosopher currently at Ruhr University in Bochum. She's doing amazing work, and I'm already looking forward to learning from you today. Quite often, these debates about ethics happen without having philosophers around us. I'm grateful that you're here. Matthew Liao is at NYU, and is a professor of bioethics. He also runs a center on the same topic, and I'm particularly curious to hear also some of the lessons learned from past cycles of technological innovation, as we now talk about digital things and AI, IT, and the like. Jeanette Hofmann, welcome back. Great to have you here. Jeanette is a professor of internet policy at the Free University in Berlin. She's also the director of the Alexander von Humboldt Institute for Internet and Society in Berlin. I've introduced the president already, and he doesn't need an introduction. So next we have Dean Melissa Nobles, who is the Dean of the School of Humanities, Arts, and Social Sciences at MIT. Really great to have you here, as we will hear more about MIT is building a new school of computing.

Correct.

The Schwarzman College.

That's right.

Lots of interesting things happening there at the intersection of engineering and ethics. So we're looking forward to your thoughts on this conversation. Wolfgang Schulz, professor for media and public law at the University of Hamburg. He's also the director-- and now I have to read that, because I still cannot remember it-- the director of the Leibnitz Institute for Media Research, which is known to me as the Hans-Bredow-Institut, but I learned that it's important to emphasize the Leibnitz part. Crystal Yang, really great faculty colleague here, professor of law at Harvard Law School. Does wonderful work, important work on criminal justice and the use of algorithms and data in that area. We'll talk more about that. So as you can see, a fantastic lineup. And of course, I'm so grateful to you, Mr. President, that you joined this group as a participant, and I get a sense already that you're ready to jump in and will take over the moderation function in due course, which is totally fine and will make my job easier. So one or two logistical notes. First, we will end at roughly 11:30. That's the plan. Some seconds of the conversation may be in German. You should have translation. If it's OK with you, I will continue to moderate in English, and I think the reason is straightforward, because my Swiss accent is so strong when I speak German, that it's easier for the Germans when I talk English, so just to make that clear. [Applause] So with that, Herr Bundespresident, here's the question for you to start us off. We met the last time in 2012 in Berlin, and had a conversation about what does it mean to make good policies for the internet age? And I googled this morning actually, and tried to remember what happened in 2012, right? It seems like in internet times it's more like 70 years ago than seven years ago.

Yeah.

And when I googled things that happened there in the technology space was the Google Glass project was kicked off. The iPad Mini was introduced. Facebook went public. And a bill was signed in California that self-driving cars are now allowed and regulated. So I'm wondering, that seems to be a very different stage in our digital transformation process, if you look back only a few years and now fast forward to 2019. Where have we arrived? What are you thinking about? What are your concerns? What are your hopes and how does that connect with the topic of today? Mr. President.

Well, thank you very much indeed for these kind words of welcome. Ladies and gentlemen, dear students, I think it is fantastic. You know, you've been given the alternative to enjoy a sunshiny day, though somewhat windy, late autumn, but you've nevertheless decided in favor of the alternative-- coming here into an enclosed room to listen to us. Thank you very much for that. And thank you also for reminding me of the year 2012, which I remember well for quite different reasons, and I'll get back to that in a second. You know, my visit to Boston in 2012. But allow me to begin by saying that I haven't been here for the very first time, and I'm always happy to be back in this academic, scientific center, a center not only with regard to the United States of America but also in a much broader sense, because it is a center that is exemplary in bringing together researchers and academics from all parts of the world, from all countries of the world, to make them work on subjects of common concern. And when I remember that visit in 2012, or earlier visits too and later visits, you know, no matter whether we talked about foreign policy issues or other issues, either here in the hall or in other places in Harvard, whether we talked about questions to do with climate policy, about the state of affairs of transatlantic relations, rest assured, every time that I came here, I returned home having benefited to a large extent from the discussions I had at Harvard. There was one exception, and that brings me back to 2012, really. Just once did I risk myself, my whole existence here in Harvard, because I allowed myself to be talked into throwing the first pitch in a baseball match. And I was extremely naive. Never ever had I before I attended a baseball match, held a baseball in my hands, nor been in a baseball stadium. And my then colleague, secretary of state Condoleezza Rice, we all remember her, was aghast when she heard what I was about to do. And the only comment she gave to me was, 'don't do it.' But you know, that is typical of us Germans. I had to accepted and I didn't want to go back on my promise. So once we entered the stadium on the afternoon of that day, I got an inkling of why my colleague Condoleezza Rice was so aghast, because the stadium was filled to the very last seat, 40,000 or 50,000 people in the audience. And I had a certain feeling that they hadn't come just because of me, but they'd come because they wanted to watch the match, a match that was the match really. Here in the United States, the Red Sox were playing the New York Yankees. And I realized all of a sudden that this is not just any match. It's about religious issues, really. Still, it worked out somehow. I survived it. And having survived that experience, I was happy to come back every time. I wasn't shy of returning to Boston, to Harvard. But today, it's a different topic, really, that brings me here, different from the topics we focused on in the past years. We're no longer on the threshold of the digitization, of digitization, of the digital age. But we have already entered that age. I've come here because the topic we will be talking about directly refers back to topics I'm focusing on in my presidency, the future of liberal democracy, that is. How does the internet, how do Facebook, Twitter, algorithms, anonymity in the internet, how do all these things change the democratic culture of debate, which is of such great importance to us in Germany, just as much as you do in the United States of America? Despite the daily waves of outrage that you have to live with, how can we make sure that we keep a general overview? How can we distinguish what is important from what is unimportant? And does this culture of thinking in simple opposites, yes or no, black or white, harsh approaches, whether that takes away from us our ability to see the nuances between black and white? Are we capable of doing that? Do we continue to be capable of entering into compromise, which I believe to be vital for any democracy, if we no longer have the time to differentiate or to see things in nuances in carefully weighing the pros and cons, because it's no longer popular? We talked about this yesterday in Boston with American and German academics in great depth. Today, though, we are again talking about digital transformation, how that has changed our lives and daily experiences. But as Mr. Gasser kindly indicated, we will be focusing on a different priority. We're not really focusing on the question, whether we need digital technologies. They're there, anyway. No one is denying the fact that they open up enormous opportunities for all of us, when it comes to fighting poverty, for example, when it comes to tackling the impact of climate change, when it comes to combating diseases and their effects. Undoubtedly, Germany is a country that has no resources over its own, outside the humanities and human resources. We want to be a country that has technology to offer, and we want to participate in the developments they entail. And that is a kind of introductory remark on my part. As regards to the topic we intend to talk about today the ethic-- a code of ethics for the digital transformation, I would like to just briefly focus on why this topic is so important to me. I actually have come from two visits, and I refer back to those visits. I visited Stanford last year, focusing again on the future of digitization. When we traveled there, a few days before we left we read in the papers that Elon Musk had bought up a company that was engaging in the research in brain implants, and that was doing very well in that regard, that this might help tackle diseases like Parkinson's and Alzheimer's. I learned a lot about the imagination of researchers during my encounters there, how one can influence brain activities with the help of implants and algorithms. This has undeniable and obvious consequences. But at the end of the discussion, it wasn't I, but it was someone who is very well known in the United States, George Shultz. That is the former Secretary of State under Ronald Reagan, who also is or was at the time a member of the board of Stanford University. He said at the end of the discussion, guys, really, I am fascinated by the scenario you have been painting, drawing of the future. But let's not forget, we are living in a democracy. And democracy relies on independent, self-determined, confident human beings if it is to survive. And he addressed himself to the researchers and the academics. So when developing these technologies, don't forget to think of the consequences of your inventions and how that fits into democracy and its principles. In my second trip, and I'm going to be brief about this, with my visit to China, again, we also focused on this topic. And we also talked about social scoring, the opportunities, the perspectives that result for the members of a society. The debates we had were not easy, because at the beginning the Chinese didn't understand why we were asking these questions at all, and why we would find some of these things complicated that come up in the context of social scoring. Because they said, we have 80, 90% of support, popular support for these topics. Why are you against it? You know, we live under different political circumstances, are scared and shocked by the idea of having to submit to a total surveillance of all aspects of our lives, that no matter what we do, this might be linked up to a system that assesses our performance in a negative or a positive way, and that this, of course, has an effect on the way we developed as human beings, that hopes, wishes, and dreams are becoming externalized, that they are stored on a software I no longer have any influence over. For our concept of individual responsibility and of personal freedom is being called into question by such an approach. We, however, know that this is not a problem that is exclusive to the Chinese. German companies, American companies that invest in the United States, that employ people in the United States, they will be working under the very same conditions. And thus we have to have an interest in what is happening here. But let me close by saying that the debate in China hasn't yet come to an end yet. It is still ongoing. We don't know what will be the outcome, the result of all those tests and experiments that are being carried out in China right now. But the obvious question is on the table. Is there something like a minimum of morals for the digital age? Shouldn't we work to have something like that like, like a common expression of the limits of the digital future in the decades or centuries to come? Which brings me down to the question of whether we do not really need a much more intensive exchange of thoughts between the tech community, the political scientists about the philosophy of the individual than is happening at this point in time, at least as I see it. Well, you know, if I were to choose, I would very much like to be in a position where I could leave Boston today, having received the confirmation from all of you that I need not be afraid, that I need not be concerned, that the debate is taking place in the very intensity that I would wish to see attributed to it. But whether that is the case or not, we will have to hear and see from you. I very much look forward to this debate.

Get enough accountability out of ethical guidelines and frameworks. I just came back from the West Coast, where you see really a change of wind. Companies now begin to wonder whether they do not need a legal framework for the future development. Such a legal framework could be, for example, anchored in human rights, and legislation could build on fundamental rights. They could set limits to future developments, also to make us see that finally it is society that shapes technology. It's not that technology sets its own rules. But we are not really aware of it, I think, at the moment. We nearly have lost the capability to see and to recognize how we change technologies as societies. So we need to perhaps turn around a bit, give up this idea of complete self-regulation, and come to new models that sit somewhere in between a market approach and a pure government approach. We need new regulatory frameworks that need to work across national boundaries, even though we can, I think, not hope for multilateral approaches. We need something below, and the GDPR, the General Data Protection Regulation that the European Commission introduced, is often mentioned as a gold standard for that kind of approach. Perhaps some countries can get together, build a legal framework and export it via trade agreements.

That is some good advice. Thank you, Jeanette. So a couple of things that I would like to follow up on. One is this role of the ethics principles. You mentioned there is a flourishing of ethical principles around AI in particular. I think 130 or something are out there. We tried to map some of them, but it's getting quite a task. But on the other hand side, given also Wolfgang's remarks and the opening statement by Herr Bundespresident, there is value to these ethical debates, nonetheless, right? And you also make this point, of course, that we need all different approaches and tools, probably including law but also ethics. And if I may ask you, how do you think about these ethical principles? What's the value in these ethical norms crystallizing guidelines and things like that, whether it's for companies or an act by international organizations like OECD or even by nation states? What's the promise, but also what are the limitations of ethical approaches of this sort when we deal with these complex, messy problems?

Yeah, so ethics and law of course have to be distinguished, although they are connected. Ethics is, I would say, the explicit formulation of implicit norms that guide or should guide our everyday actions in our life, our living together. And law, it's the core of the organization of a state or a nation, transforms some of these norms into concrete rules, the infringement of which then is bound up with sanctions by the state. So this is something different. And not all moral norms are legal norms and vice versa, of course. But ethical guidelines now for new topics like digitization can be, I think, helpful first steps to show something that then can be transformed into law, too.

Speaking of law, what's your hope that, looking at your area of research, the law will evolve in this dynamic situation, where maybe ethical principles may lead the way? Where do you see the promise of law in these debates, where we're facing this shift from the human towards the machine?

Yeah, I think law has a very important role to play here. I think I share Jeanette's general sense that self-regulation is probably not going to be a sufficient solution, that there have to be legal interventions. And the law is both instrumental in that it will undoubtedly, by deciding what to permit and what to prohibit, shape the behavior of governments, private companies, in terms of how they design algorithms, how they implement them on the ground. The law, I think, also has important expressive principles maybe related to ethics, where if the law allows for something, then citizens, members of society, will view something as maybe more socially acceptable. So I think the law here has a big role to play. Coming back to the criminal justice system, though, I think there are many ways in which the current law, certainly in the United States, falls short for a lot of the new challenges that might come with algorithms. So to give you some examples, many people are troubled by the use of disparities that can emerge when you use an algorithm to make decisions. And that could be because of the data or the structure of the algorithm. Now, it turns out there's probably pretty limited legal remedies for addressing those disparities. Under current US law, a finding of discrimination under the Equal Protection Clause of the US Constitution would require a showing of discriminatory intent or purpose. And that's hard, because when an algorithmic designer chooses to use a variable or certain types of data, there's probably often no discriminatory intent or purpose. And yet because so many variables can be proxies for things we're troubled by, there's often maybe no direct legal remedy. And so this traditional requirement we've had in the US Constitution and case law of requiring intent and motive is often ill suited to addressing the new types of problems that the algorithms can introduce. Moreover, it's actually been the case in the US that many have interpreted the case law on discrimination as requiring or prohibiting the use of characteristics like race or ethnicity. You can not use them in any way, shape, or form. But the reality is that because of the complex statistical relationships underlying many variables, I, other computer scientists, economists have written and shown that those proxy effects that we may be worried about are often created because of the prohibition on the use of those characteristics. And that once you take statistics into account, you may actually want to use protected characteristics in certain forms to actually remedy those disparities. And so it's actually this problem right now, where I think the law is pushing companies, governments to develop versions of algorithms that may actually be counterproductive to our larger societal goal of equality and opportunity. And I think, to the earlier point about human decision making, the law often does not consider counterfactuals in a very easy way. It often seems to require perfection for algorithms, explainability. But as you point out, what is more a black box than what is in a judge's mind? Perhaps the judge's mind is more of a black box than a neural network or other forms of machine learning. And so I worry that the law, by sometimes requiring perfection and not considering the counterfactual, will often chill and deter what may be innovative and good uses of algorithmic decision making.

Change that right, over at MIT? Can you share your thoughts? And then I would like to open up for a number of questions. So be ready with your questions.

Sure. So the Schwarzman, the College of Computing, which was announced last year, is intended to get at just this issue, that much of the technology that is obviously being created at MIT, we recognize that there has to be a bridge between technology and the humanities and the social sciences in an intentional, deliberate way. And part of why the school was established is, tons of students are interested in computing. They're doing it. They're coming in, wanting to major in computer science, but many of them don't want to only be computer scientists. They want to apply that knowledge to something else, but they want it to be guided by some domain knowledge outside of computer science. And so the goal of the college is to eventually — we're beginning to see joint, blended degrees between computer science and economics, computer science and urban studies, computer science and music. Not all students are doing this, but the interest is great, and it's intended to allow for this connection in a more organic way from the beginning, such that students will have the type of skills, so that we won't be talking about disparate communities, but that students will have enough of an openness, at least an exposure and understanding that this is what it means to be a computer scientist. And conversely, for my own discipline, I'm a political scientist, this is what it means to be a political scientist, is to know something about this. So all of us are going to have to learn more and be open to learning more, if we're going to successfully deal with this issue.

One other thing I'd like to say about it is, we're starting to have these conversations on campus. They are not easy conversations to have. As much as we try to be collaborative, we've really had to work. We may be using the same terms, but we speak a different language. And it requires patience to do this. So part of what we're doing is also learning some other principles of generosity and patience as we deal with one another. Because if we want to solve this problem, deal with technology in a way that we all want to see, then that's what it's going to require, some other human qualities that we have to bring to bear for this to happen. And I think especially just inclusion is really important for us for our undergraduates, since many of them will be going into leadership positions. They know the technologies. We need them working on the congressional staff. If you all saw the hearings with Mark Zuckerberg in the Congress, people didn't know what Google was, right? Or they didn't know the difference between Samsung and Apple. I mean, they didn't know anything about the technologies. If they don't understand how to open their phones, how can you imagine that they could be responsible and entrusted to do the kinds of things that you all are describing? Some of what we also need, our students to be able to play those kind of roles, precisely because — but we don't want them to do it only knowing the technology. They will also have to understand economics, also have to understand political science, and such. So that is the task of the college. And we're just getting started, so stay tuned.

That's exciting. That's exciting. Thank you. OK, let's open up for a few questions. Our mic-runner is ready and fast on her legs. Who has a question? And please end with a question mark. That would be good.

Me? First thank you so much for all the interesting insights you shared today. My question is, regarding the fact that a lot of you mentioned today that there's an urgency to craft tech specific ethics regulations as soon as possible. So in a way, this is really a moral discussion with a deadline. When would you say is this deadline? When do we have to formalize our thoughts and put it into law?

No, of course I think the deadline is — it's not far ahead, but it's just right now. But there are already a lot of ethic guidelines being written right now. So we really have on national level a different one in Germany. Then there are international levels, like, for example, the high level export group that got tasked by the European Commission. And they wrote something, and then we have already part of this ethic guidelines, for example, extracted, and the G20 group signed it. And so there are already guidelines, but I think the guidelines are only the first step. And then, of course, they're our first step to transform them into law, as we heard already. And so yeah, it's right now, and we should go further ahead. But it's still already something happening, I think.

Yeah, maybe I can add a legal perspective to that, because one of the problems of the law is that the function of law is to have stability. And what we need here is some flexibility as well. And so what we are struggling with, as legal scholars, is to find ways to make law more flexible, to have constant evaluation, to have sunset clauses and things like that, so that we do not have to wait. I think it was Susan Crawford said the marvelous sentence, we have to regulate things that we don't understand. And I think we can't wait until all of the lawmakers have understood what it actually is. You have to act before. But then we need different instruments, especially when you take into account what you said, that when you are talking with lawmakers, even if they really try hard, the problems are really high tech. Only a couple of people really understands what's happening there, and even the best member of parliament cannot be an expert in this field. So we need constant evaluation and some mechanism seems to deal with. Every day, even we as researchers, every week I have a new understanding of how algorithms interact with society. Every meeting, I have an interaction with some software engineer and oh, OK, it's a little bit different than I thought before. And on this basis to create law, that's, I would say, a fundamentally new challenge.

One of the dark sides of having such an amazing group of people is, we could discuss 20 minutes just one question. So you want to jump in quickly with comments, Jeanette and Matthew?

I thought perhaps one way forward could be to pursue a more procedural approach to these problems. For example, think of ways to holding companies accountable to the kinds of technology development they tried to bring to the market, introducing auditing requirements for certain type of algorithms. Make it mandatory to only use in certain areas machine learning systems that are self-explainable, that explain, in at least basic ways, how they come to certain recommendations and predictions. That seems to be a way forward, rather than relying just on rules.

Maybe I can also jump in here. So I think Professor Gasser's mentioned that there are about 130 ethical principles that are being presented by different companies and so on and so forth. I think what we really also need is a rationale, or philosophical — this is a plug for philosophers — a philosophical justification for some of these principles. So for example, a lot of these principles say things like we need explainability. Why do we need explainability? I mean, we've heard some of the panelists asking this question and various other things. And so here in that line, I'm very sympathetic to what Professor Hofmann's saying, which is this idea of the human rights framework, which says that we need to look towards the goal. What are these algorithms for? Fundamentally, they are about promoting human well-being, right? We want to make sure that we have a harmonious society, one that works towards all of us. And so a human rights framework, I think, can really move towards that goal. And there's a rich tradition. There's a rich literature on these philosophical justifications of the different rights. And they go beyond just discrimination, right? They're positive rights. They're rights where it's not just about making sure that you don't discriminate, but making sure that your technologies also work to help people and so on and so forth. And the other thing about human rights is that it's an obligation on everybody. So it's not just an obligation on the engineers. It's not just an obligation on the company. It's not just an obligation on the government. It's an obligation on all of us. We need to collectively make sure that we're working towards making sure that these technologies work well for everybody.

Crystal.

I promise to be very brief. I know there are a lot of hands up. This is such a fascinating question. I think, I wholeheartedly endorse the perspectives others have raised, especially Mr. President, that the laws must be adaptive. They must be flexible, because we are still learning how they work, how the algorithms work. And so we have to also study when a new regulation goes into effect. What does that mean about the types of algorithms we're seeing that flourish after that? What types of algorithms are now disappearing as a result? To that point about explainability, I think we all have this desire to understand what the algorithm is doing. And so we often, then, might shift towards regulation or principles that the algorithm be explainable. The complication there is, now there's emerging work coming from computer science and economics, showing that when you force an algorithm to be explainable, you generally will choose an algorithm that's simpler, because it has to be easier to understand. But a simpler algorithm, as it turns out in some contexts, actually can lead to both less efficient results and less equitable results, which again raises a conundrum that I think no field alone can address, but just reveals that there are inherent trade-offs every time we make a choice, like explainability. And we have to confront those trade-offs and decide how do we weigh competing values, which are inevitably going to be at stake.

Great. So let's collect three questions, and then we'll respond. One question here, and then maybe one from over here, this area.

Yeah, I'd like to add an observation. I think it's also observable on the podium that we are missing economists, and we are missing behavioral scientists. And it seems to me that these two components are crucial in understanding the impact that AI has had and will have on our society and each of us. Why do I say this? Because AI has enormous economic potency. In this country, the majority of the productivity of this country comes from AI. And why is it that Facebook and Google and other companies have been doing undaunted what they have been doing is because exactly of that. And so that is one reality that we have to face. And this reality is deeply immersed in research as well. Where is most of our funding going? It is going to computer science, to computer engineering. And then we have some alibi, excuse the term, addition of social sciences, and if we are lucky, behavioral sciences.

There's no level playing field between the behavioral sciences and all the psychological dynamics that are opened up by AI and computer scientists and computer engineering. Unless we change these funding structures — and we've heard a lot about the necessity for other regulations for companies, but these funding structures have enormous consequences. President Steinmeier was asking, is there any example about, at the beginning of such an enterprise, to bring disciplines together? I would say, yes. And actually at the Ruhr Universität Bochum, there is one competence cluster that focuses on cybersecurity, which tries to give level-headed, equal importance to social behavioral science on the one, economics and computer science and computer engineering. So I just hope that in the future, such discussions move beyond very important contributions from philosophers, ethicists, and lawyers to also have a brighter view.

As we are at a German-American conference right now, I just want to ask, how does the transatlantic relationship help us in solving all these challenges? What is needed for an effective transatlantic relationship, especially the German-American one, to solve all these challenges together, as like a world and not as like separate states?

Do you think, talking about social media, that the time will come that there will be a reliable algorithm to identify hate speech?

I'm one of those computer scientists writing those messy algorithms, and I know that there are people in my field who think very critical about this. And I know there's a lot of discussion. So I can convince you there are people behind the current talking about the things. How can we reach out to other people who are thinking about this?

My question is short. Thank you all. This was delightful. I would like to understand, are we being human race empowered by technology? Or are we powering technology by humans?

Great. All right. We have 12 minutes left. And I'm Swiss, as I said. So I want to end on time. So what I would suggest is that we actually do a closing round and pick the question that you would like to address, but put it into the context also of your work and what we've discussed here. So we have the question of transatlantic relationships. We have the question around social media and the role of technology in creating a safer environment using the example of hate speech. And we have this ultimate question, is technology empowering people, or are people here somehow to empower technology. So these are a few of the themes. Perhaps we start with Eva.

Yeah, maybe to the two last questions. Of course, I think that the technology should empower people, but for that human machine interaction, it is important that we understand each other, as we already talked about. And maybe just into two aspects that philosophy can contribute here, and the one is, it's not only about explainability that you said, and it's not only what is also important about the ethic or moral justification of why it's so important to explain, but also to see that in morality, for example, it's about reason giving. So the whole validity of moral norms depends, I think, on the fact that they exist between beings that can give reasons and understand reasons. And so one question would be, do we want algorithmic structures who cannot give reasons in an empathic sense, for example. And another topic would be the topic of trust, because the ethic guidelines often highlight trustworthy AI as a claim. I would also be skeptical of this as a best aim, because trustworthiness presupposes also being a moral subject, because trust means to believe that someone will hold to his or her commitment to do something. And this is also something that is only possible for a moral subject. So AI systems cannot be trustworthy agents or subjects.

Yes, I'll take the question on hate speech. So I mean, there are some attempts using machine learning algorithms to detect things like fake news and things like that, but I actually want to give you a very grim picture. This is like election 2.0, since we're coming up to another election cycle. So there's some evidence. There's something called deep fake, which is being able to produce all these videos that just look like they can superimpose your photo or you onto another video. And then they can get you to talk and do various things. And what people are finding is that — so there's the theory that you tend to vote for people who look like you. OK, and so now they're creating deep fake videos, where they superimpose your picture onto a candidate's picture, so it looks like you. And now supposedly that's going to influence your voting behavior, because you're more likely to vote for people who look like you. And so that's going to be very worrying in the future. And then the question is, we're going to get to a point where it's going to be very hard for human eyes to be able to detect those differences, and that's going to be very worrying.

I'd also like to pick up the question on hate speech. What I find really good about this question is because we have so many examples that show how deeply ambiguous we are about such wording. Facebook once told me the example of the term bitch. Bitch can be really dismissive, when you call a woman a bitch. But nowadays, in some circles, bitch can also be appreciative. Women might refer to each other as bitches. How is Facebook supposed to regulate wordings that have so different meanings? And that, I think, shows also the limits of technical filtering of language. Language is changing all the time, and it differs across cultures also very much. So there are really limits.

Another point, if I may, the question of empowering versus disempowering. I really like this question, because it implicitly refers to autonomy of human beings. I think it's a mistake to think autonomy needs to be defended against technology. Technology, in many ways, enhances our autonomy. Think of flying around. Think of your watch. I mean, we coordinate as societies through these technologies. And at the same time, they are disciplining ourselves. So it's not an either/or. And technologies and human beings are not opposites. It's the matter of how we structure and shape the relationship between the two.

Sure, I'll just take the question of the computer scientist who said these kind of conversations are also happening among computer scientists. But we need to get better connection with others, who are thinking critically about it. I think that obviously education plays a hugely important role in this. That is, early on getting students of different disciplines to work together and to learn together in a way that addresses these questions exactly. The challenge of all knowledge is making sure that it doesn't stay siloed, that we work in a truly collaborative way. And it seems to me that's the challenge for the 21st century.

Yeah, I think I'll pick the comment, if I may, on the funding and interdisciplinary research. I think we talk a lot about interdisciplinary research, and we need it to solve problems, but the academic system is not really designed to cater that need. We still have problems with that, and I constantly get phone calls from colleagues that want to apply for project funding next week. And they said, oh, we have just seen we need some ethics in it, and we need a lawyer or something like that. Would you be available? And normally I'd say no, because it has to be part of the project question and not just an icing on the cake that has already been baked. That makes no sense. And so I think we have issues here in the academic system.

And maybe 30 seconds on the transatlantic issue. I think it's really helpful and good for these questions that there are really stable research relationships between our American colleagues and the research in Germany. It's really great, and that survives even if there is a political winter or autumn, that we have this relationship. And to solve these kinds of problems, I think that's extremely helpful.

Yeah, I'll just follow up also on the research question to the excellent question over here. I failed to mention, I am actually an economist as well as a lawyer. And I would welcome many more economists studying this area, and I hope that the funding structures as well as the incentives do promote that greater collaboration. I think the computer science community is doing amazing work. It's often siloed from what the economics community is thinking about, what the legal community is thinking about. And so I think initiatives like what Dean Nobles is doing is probably a really great way of bringing people together. And to education, there is such a need for infusing this type of learning in legal systems. And I don't think that US law schools, at least, have really been at the forefront of this. In fact, many of the decisions you read from state supreme court judges who are ruling on the use of algorithms and making important case law have explicit acknowledgments. I'm paraphrasing here, but I'm not paraphrasing so far of, the judges in this case were limited in their decision making, because they didn't understand how the algorithm worked. Well, that's a really big problem. And so we need to train the lawyers who will be deciding these cases, working on behalf of clients who are both creators of algorithms and individuals adversely affected by algorithms to understand how algorithms work.

Mr. President, you have the final word. Thank you.