Hello! I welcome you to an e-lecture in which I would like to define and exemplify our video strategy, a strategy that is tailored for our subject, the teaching and learning of linguistics at university level. Many of the ideas I'm going to present will occur in my new book in German, though. This is why I want to summarize these ideas in English too. After more than two years of video production for linguistics and beyond, I've learned that there are cross-subject as well as subject-specific aspects that determine our video production. I will proceed as follows. First, I will introduce several terms that are used and often mixed up in the context of video production. Then, I will look at the parameters that may be used for a suitable video typology and will also exemplify the several types of videos that emerge from this classification. Well, and finally, I will also introduce some ideas and concepts that might help you to produce videos for your teaching and learning scenarios. So let's first of all look at some terms that are used in the context of video production. For example, there have been distinctions between camera recordings and screencasts, where screencasts are captures of what is going on on a computer screen during a presentation or a program execution. However, since almost all videos to some extent involve a presentation and thus a screencast, this distinction is marginal. Then we have terms such as e-lecture, live digitized lecture, video scribe, or instructional video, which might be used ambiguously and sometimes mean the same thing, but are also used to address different video types. So it seems suitable to provide a somewhat different classification that is more convenient and enables us to precisely classify what we are doing and what you can do with ease. So let's look at the main parameters that can be used for a suitable video classification. An often mentioned parameter is the production style, a term which is used somewhat unspecifically, defining, for example, classroom videos, video scribes that are produced using a tablet, videos that are produced at a desk, and so on. Or take the content. Here you have several possibilities of classifying videos, tutorials, explanations or demonstrations to name a few. And then we could take the length, or physically speaking, the duration of a video. This parameter is of special interest since it is now known that student engagement rarely lasts longer than six minutes. More plainly, students do not spend more than six minutes on a video. So length, as we will see, is a crucial parameter. I hope you can pay attention to this video for more than six minutes. And then we can take the setting that defines where and under what conditions a video is produced. And last but not least, you might want to know whether the speaker's head is part of the video or not. So all these parameters may be taken to classify your videos. Looking at the videos we have produced and used over the years, it seems suitable to select the setting parameter. That is, where the video is recorded as a basis for video classification. And here we can define three scenarios. The first is the classroom setting. A setting where the video is produced within a classroom with a real audience in real time. As shown here, the equipment may range from standard video recording equipment to an in-class recording using a cell phone. However, studio equipment is not normally used with this setting. In the office setting, the video is produced without an audience. The term office is thus a placeholder for all environments outside the real-life classroom environment. And in the studio setting, you produce videos using professional equipment, such as high-end cameras, green screens, teleprompters, etc. Let us look at some examples. At many universities, live digitized lectures, that is, videos produced in the classroom setting constitute the backbone of video-based teaching and learning. Let us look at this example. Okay, so Newtonian Mechanics is our first topic. So Newtonian Mechanics has two parts. As we know now, however, live digitized lectures are non-beneficiary for several reasons. First, they are too long to attract attention throughout. And secondly, they can mainly be used as supplements to traditional teaching scenarios only, but not as a replacement leading to new teaching and learning scenarios. So for us and for many other subjects, too, live digitized lectures do not exhibit a significant gain at all. The videos produced in the office setting are of several kind and can be referred to as instructional videos, whereas studio setting videos are dedicated to specific purposes, in many cases to mere entertainment. Whether they are suitable for teaching and learning is highly questionable. Look at this example of BBC production about English. It was the Vikings who sacked and burnt the religious centre that stood here before. To these pagan pirates rampaging out of their longships in 793, this great centre of Christian piety and scholarship, a pivotal place in the survival of the word in the Gospels, was no more than an undefended treasure house. Thus, the only realistic option that at the same time involves a significant benefit for our learners is the production of instructional videos in the office setting. Taking the parameter duration, we can distinguish two essential classes of instructional videos. Micro teaching videos, that is short videos that are usually not longer than 5 minutes and primarily involve short and concise explanations. Here are three examples. Short video-based definitions, dynamic demonstrations and concise explanations. Let s look at a typical linguistic demonstration realised as a video scribe. But where shall we put the two prepositional phrases? Well, in order to integrate them into the noun phrase, we have to expand the N bar node twice more and make the mothers of the two prepositional phrases. Micro teaching videos by contrast are longer and are often done in a short lecture format. They are preferably used to introduce a new concept. The two variants I have here are e-lectures. They constitute the backbone of teaching and learning on the virtual linguistics campus and interview videos where experts talk about selected aspects of their fields. Let s take an example. Hello. I thought it might be a good idea to let all the beginners in linguistics know what linguistics is all about. Or should I say what linguistics is not about? Considering the goal of this short e-lecture, I am producing right now my announcement to find out what type of video can realistically be produced by everyone without a big equipment and a long experience in video production. I can now clearly say videos that are produced in the office setting and that fall under the category of micro teaching. They are short, they do not need a talking head and are thus easy to produce and they often involve content that has to be repeated time and again in real life teaching scenarios. And the technology that we need for the production of these videos is manageable. A simple laptop, ideally one with pen input and an external microphone, will do. As far as the software is concerned, you need some sort of screencast software, for example one of the highly popular TechSmith products, and an audio editing product such as the freely available Audacity audio editor, if you want to record your voice on a separate track. And if you want to film yourself or anyone else, your phone or a simple camera could be used as additional devices. And there are so many options to produce and use micro teaching videos. Here are some of them. You can for example simply record yourself or someone else who exemplifies or demonstrates something. You can annotate existing diagrams or create video glossaries or you can explain certain analyses, facts or calculations by simply talk while you're writing. So I hope that I could give you some ideas about video production in general and maybe even video production in your particular field. But before I finish let me finally mention two essential premises. First, learning is not just video watching. You need more than just a few videos, for example you need assessments, additional tasks, thus a full-fledged and deductically carefully designed environment. And secondly, your video doesn't have to be perfect. Do I need it perfect or by Tuesday is the guideline that Aaron Sams wrote into our diaries in 2012 when he was at the first Marburg inverted classroom conference, a guideline that has meanwhile even been converted to t-shirts by Tixmith. So we do not need perfect video productions, let alone documentaries for teaching and learning. We do not need long introductory screens and background music. What we do need are videos that are short, concise, deductically well planned and that satisfy the needs of your subject. Thank you very much for your attention. And I apologize that this video was longer than six minutes.


Now what happens with subtraction? Well subtraction is just addition where one of these numbers is negative, but we haven't paid a lot of attention to the possibility of negative numbers thus far. So back up here with the linear multiplier, what if our multiplier wasn't 10, but it was minus 10? Would we expect our uncertainty to go negative? What does a negative uncertainty even mean? Ultimately we're talking about this delta x as just this distance, and so we're assuming that it's positive, and our value could be anywhere between x minus delta x or x plus delta x, or indeed possibly in the tails of some distribution of about that width. So we're really thinking about the uncertainty that we're quoting as a positive number, it's like the size of our uncertainty. And remember if this slope, if this graph went that way, we wouldn't expect to get a negative number therefore.  And then it doesn't matter whether we pick plus or minus there, and it shouldn't. And it doesn't matter whether we pick plus or minus here, and it shouldn't. In the end what we're going to get is the sum of the uncertainties popping out. And so in fact addition or subtraction, in both cases, you add the uncertainties.  Now on average I end up at exactly the same place, but there's uncertainty. There's uncertainty on my step forwards, and then there's another different uncertainty on my step backwards, and so those uncertainties are not going to cancel. So I'm going to end up back where I started, but now I'm going to have an uncertainty of two centimeters from my starting position. So even though I'm subtracting the values, I'm subtracting my A and my B from each other, my measured values, I still have to add the uncertainties.


We are at a point where we're starting to hit the ceiling of the capacity of the planet to support humanity in a stable way. Unfortunately, we've filled up so much of the atmosphere with Gwyneth's gases. We have emptied so much of the oceans of overfishing. We have destroyed so much of our ecosystems that we now have scientific evidence that we need to transform ourselves back into safe operating space on Earth within one generation. The Holocene is called the Long Summer, and the very stable climate has been the conditions for the rise of civilizations as a whole. But now we are leaving this matrix, and so we are now with this epoch, which we call the Anthropocene. And this is just the result of all those cumulative human activities that are creating this big problem we're in. One thing that I find very challenging in thinking about planetary stewardship and sustainability is how we can recognize the problems that exist at scale and at the same time can't make the small changes in our own lives to correct for bad patterns that are happening. What I really need, and I think most of us need, is we need those stories that tell us the bridge from where we are today to where we want to go. And we need those stories told to us over and over and over so that we can make sense of them for ourselves and find the way to the future in solving climate change. The healing of the planet, the healing of our societies, the healing of communities and personal healing, inner healing, all of these levels are connected. And they all draw from a new story. You know, that really reverberates with Māori people in terms of the Paethawhiti, the distant horizon. We have an intergenerational plan, 500 years, looking out further than our lifetimes and thinking about the types of steps that each generation will need to take in order to ultimately achieve the outcome that we aspire to have for our community. What I really need to see is that people understand that all of our economic value comes from nature. It's as simple really as no healthy planet means that there is no healthy people. There has never been scientifically so much reason to be deeply, deeply concerned and nervous. But equally, there's never been so much reason for hope. And this is the big paradox today. The window is still open for transitioning into a safe operating space where we can still have a stable planet and thereby stable local ecosystems. We are here continuing to have one ecological crisis after another trapped in a futile response pattern. What it's asking for is a revolution of love. It's asking us to transcend being centered just on humans, to accept our participation in a larger reality. The climate crisis is an invitation to us to join the tribe of all life on Earth as a contributing member.


Welcome to this video. Today, you're going to learn how to use although, even though and though. This is a question that a student had submitted and it's a great question, so I'm happy to answer it for you. Of course, I'm Jennifer from j4senglish.com and this channel is dedicated to helping you feel confident speaking English and public so you can take your career and your life to the next level. Now, before we go any further, make sure you subscribe and hit that bell icon so you're notified every time I post a new lesson. Now, let's dive in with this video. Let's talk about how to use although, even though and though. All three of these are transition words. They're used to show contrast. So what does that mean? To show contrast, it means you're going to have two ideas and the transition word, although, even though or though, are going to connect those two ideas together. But those two ideas must have some sort of contrast in them. So you can think of one idea as more of a positive and the other idea as more of a negative. There has to be some sort of contrast. Now, what's the difference between although, even though and though? The level of formality. That's it. Although, is the most formal, even though slightly less formal, and though is the most casual. Now, in terms of sentence structure, there's one difference also with though, which I'll explain at the end. But otherwise, the only difference between them is the formality. Let me give you an example. Even though I'm busy, I enrolled in that course. So here, notice how there are two distinct ideas. I'm busy, I enrolled in a course. You can think of these ideas as being in contrast. They're opposite ideas because one might think if you're busy, you wouldn't have time to enroll in a course. So that's why we can use although, even though, or though to show that contrast and connect those ideas together. Now, notice the placement here. Although, even though, or though can come at the very beginning of a sentence. You can say, even though I'm busy, although I'm busy, though I'm busy, I enrolled in that course. Now, another common placement is to have although, even though, or though before your second idea. So you can think of it in the middle of your sentence. So I can take the that exact same sentence, but change the placement and say, I enrolled in that course, even though I'm busy, although I'm busy, though I'm busy. So it can come at the very beginning of the sentence or in the middle of the sentence before your second idea. And it doesn't matter which one you use, both of them are interchangeable and they both sound professional and natural. Now remember at the beginning of the video, I said there's one sentence structure with though that's different. And that sentence structure is that you can use though at the end of your sentence. This can only be done with though. So we don't do this with although and we don't do this with even though it can only be done with though. So I could say, I'm really busy, I enrolled in the course though, and I can add though at the very end. This makes it sound a lot more casual, a lot more conversational and what it's what you'll frequently hear native speakers use in conversation. Now native speakers commonly use though at the end of the sentence, when the second idea isn't identified, the contrast isn't identified, but it's obvious based on context. What do I mean by that? Well, let me show you a real world example. Here's something I wrote in the comment section of the YouTube video. And notice I said, great job practicing though, great job practicing though. Now I'll be honest, though is optional. I could just completely get rid of it and say great job practicing. The only reason a native speaker includes though at the end of an idea is to imply that there's a contrast. So even though you don't see the contrast, it's there. So what is the contrast here? Well, the context is that this student tried a practice example and he made a mistake. So I corrected that mistake and I said, great job practicing though. So if I were to write this as our structure of idea one, idea two, combined with our transition word, I could say, although you made a mistake, you did a great job. Or you did a great job, even though you made a mistake. So notice that I can take that same meaning and just imply that the contrast is there by using though at the very end of a sentence and only having the one idea. This is probably an advanced use and you probably won't feel comfortable using it yourself right now. But a lot of students are confused when native speakers just throw in a though and say something like thanks though, thanks though, I love to though. So now you understand the only reason we're doing that is to show a contrast. So now you know how to use although, even though and though, I'd like you to leave three example sentences, one using the transition word at the beginning, one using the transition word in the middle, and one using though at the end. Remember, for the final example, it has to be though, because that's the only one we use at the end. And if you found this video helpful, please hit the like button, share it with your friends, and of course, subscribe. And before you go, make sure you head on over to my website, jforisenglish.com, and download your free speaking guide. In this guide, I share six tips on how to speak English fluently and confidently. And until next time, happy studying!


I'm monk assing in real life the whole time Okay, we should pull the camera away when that they're doing that. Just watch the camera. You can get some bad Listen, this could be a crazy crazy IRL stream. We're the gathering of the juggalos in St. Cloud Posse We're here in Ohio. This could get kind of wild, okay? And if I'm not getting banned because somebody's coming up and Flashing the freaking boobs so we have Jacob at home at my house So if something bad happens he cuts the feed it'll it'll freeze for a little bit And then we'll come back like 30 seconds to a minute afterwards I'll be honest if it's real bad, we'll probably end it and we'll just make a vlog out of it So we're gonna edit all this stuff out Danny Here Okay, so here's basically the plan. Here's what we're gonna be doing.  We got a golf cart. Actually We got Finn getting a concussion cuz his head just hit the trailer part of the process So part of it. We got a flight stuff last couple days and got everything sorted out We barely put it together in like a few days Those of you guys who don't know what this is This is gathering of the juggalos in St. Cloud Posse It's like it's almost a convention really.  I didn't even know this existed. I think you sit in the back. Yeah, the Skyler I mean Danny in front. Yeah, does it smell there? How many juggalos? I'm telling you people have been out here for three days. This place smells like a circus I plan on driving like this by the way. I'm just gonna put my feet up like this. Don't say that I'll text on one phone and I'll reach it Don't worry. There's no map for the gathering. Okay, I won't need to look at a map. There's no gathering Flip another cart and break an arm.  That's good. Yeah, we got it. We gotta see some of that Yeah, look at these food He's already Watch the camera Chats for your own good Yeah, you're gonna be some good with it. I'm gonna tell you that Don't hang it up the bottle the booty do We could walk around All right camera down Thanks in the chapter Jacob already an angel to stream Let's take the golf cart and we can let's park at the trailer. Yeah, well, let's just our whip but Golf cart nigga.  Yeah, going up. Okay, I'm not putting no math. So I'm coming back with the juggernaut there It's definitely brewing. It's definitely brewing through it. You can see it on them Yeah, I think it's I think it's good. We'll go walk around a little bit. No, you know you can get that content It's hard to catch them all I'm not gonna lie. It's pretty bright Three titties. There was three titties in that run. Yeah But three titties which is weird because they usually come in pairs Lady though Chilling She looked like job But a hut It didn't look like titties. It looked like rose just born into one thing.   Yeah, I never had Fager. We should get some fagot You got to get a rock and rock rock and rock That's because no other flavor of soda has that space We don't even know what it is you have to drink a rock You know what else we got to find somebody's painting faces.  Really? I think that's what it is Yeah, Danny's Danny's performing tonight in a few hours. We were hanging out at the simply spoke thing and then oh, yeah That's how we came up with this idea.  You should come That's the thing. That's why it's fans a real one.  This may help it. You don't say anything like that make it, but we'll go get good content for you guys We're gonna be good. I probably wouldn't even be But we still I met you from the train rickshaw. Yeah, yeah, that's how that's how Danny I got to know each other because we've got a podcast a few times and it was good He heard me for like months. Let me see He heard me for months to me, too I gave him I gave him the price cuz I thought cuz you know I'm gonna switch to so I thought he's like, oh cuz trying to leech You know, no, that's how I felt cuz trying to leech like he trying to come up. It's a talent, too Saying where's the talent in rap? You know what I'm saying? So the rapper want to hop in and be a streamer you kind of gotta be good at it. Yeah, you can't just show up Yeah, and the audience doesn't really translate.  No, I'm good. I'm good.  Okay, so don't turn around I'm moncasting in real life the whole time my eyes wide open. I'm like Stars on this here stage and I am so glad They need to come out This is a new tech dude new tech and researching this all week something else. I'm thinking about doing chat Setting up a splitter on this thing. I want to set up a splitter Have a microphone and the shotgun and then I want to have a hand That way I can interview people. Okay, so we're gonna try fago for the first time You're gonna see if you can drive that sounds like a bad idea I want to see if I can drive All right, so Danny left let's go to the trailer real quick So it's been an interesting experience with the juggalos so far So obviously this is fun and interesting and all that but there's also kind of like a test run for the tailgate Yeah, we we got some fago Okay, rock and rye. I'm a whole life. I've loved that shit and I've never thought to myself like what is this flavor though I think it's a rock. No, I know I think you're on this, but I want to hear so rock and rye I ain't drunk rock and rye years, dude. I know. Yeah No, that's I can't tell what it is.  Yeah It's like cream soda It's almost like red pod cream soda and a cola.  Don't don't chat. Don't get confused. These juggalos got good taste. It's hard I want to walk out there and talk to some people. I'm so worried now. You got muscles. Yeah, that's not that's not what I'm scared of I'm not I'm not scared of that. I'm scared of somebody showing something. You know what I'm saying? Chad give me a second battery is gonna swamp and we'll be good. Okay. We're gonna go out again Catch them but I think it's getting dark now Yeah, just trying to get dark you guys want to go through and try and do one more walk through I just I get some nervous. Okay, we'll go out for a little Okay, so here's the plan chat they found face paint, but they had to find somebody to do it I guess I'm gonna go on stage with Danny and I'll uh introduce introduce Danny and skywalker So that's gonna be uh an interesting experience. Okay, so what I was talking about It's basically this stream was supposed to be a test run for the college football tailgate show That's gonna happen weekly ish kind of It's gonna happen weekly ish For college football season and this has been really fun so far It's been a blast. I'm glad you guys have been having a good time. It took way too long for us to swap batteries That that's gonna get fixed Did you guys hear I was really worried they couldn't hear First gathering This is my 19th gathering You


Learn how to control the ball, keep it in the air, and become a juggling top-tecca. Use your foot to get the ball in the air. Use your laces to keep the ball in the air. Stay on your toes so you can move your feet quickly. Use both feet if you can. Try to keep the ball below head height. Do you like juggling? Keep practicing until you're ready to take the top-teccas challenge.


The topic of my talk is Siri profiling citizens in a welfare state. I'm Ronald Haussen. I represent the platform for civil rights protection in Holland. I work together with a group of NGOs. We sued the Dutch state because of an algorithmic profiling system. It was being used on Dutch citizens in the social security sector. First I give a short introduction of Siri. Then I will go into our problems with Siri while we sued the state. Then I will shortly go into those changing public debate on Siri. After that I will give you the most important points of our court ruling and speak a little about the positive developments that are a consequence of this court case about me. I am a journalist and researcher. I work together with NGOs on privacy and civil rights. I focus on digital technology in the social domain as opposed to police digital technology and more in the social domain of people. Getting help from the government and receiving social benefits. First to introduce Siri, I want to show you a YouTube video, a nation video we made to introduce the topic. As a citizen, you share all kinds of personal information with the government. When you apply for tax, you need a roll-out, ask for a parking permit or take a dog. You give this information in good faith and do not expect it to be used against you. But since recently that has happened. The government can now connect your information with all other sources and in the hands of a risk model to determine whether something is in your hands. For our government, you are suspected for example. Since 2014 the system is called a risk indication or Siri. That system is used to scan citizens on women's risks. That happens without you knowing it and without your consent. If you seem to be enough for Siri on the used risk model, there is automatically a flag in your name. Maybe you haven't done anything wrong yet, but government instances keep you sharp in the holes. You don't know that. You don't get to hear that yourself. But how does Siri actually determine whether you are at risk? That is also secret. Are you already suspected? Look at www.bivorbaatverdacht.nl Well, let's first talk about Siri's goals. Siri, which means system risk indication, is a risk profiling system that the Dutch government implemented in 2014. It aims to produce so-called risk notifications on citizens. According to Siri's data analysis, these citizens have a heightened risk of not complying with a very broad collection of laws in the domain of social security. Citizens who are flagged by Siri end up in a so-called risk register, a registry of risk notifications for two years, which government authorities can access to use the risk notifications to further investigate someone. The goal of Siri, according to the law, is quite a mouthful. It's the prevention and combating of unlawful use of public funds and provisions in the field of social security and income-related schemes, the prevention and combating of tax and premium fraud and non-compliance with labor laws. If I try to explain this to my mother-in-law, I tell her it's cance every citizen for every penny they receive from the government or any penny that the government wants to expect to receive from you. So what sources does Siri use to assess citizens? It's 17 open formulated categories, which are all summed up here. Notice that these categories are described quite broadly and vaguely, so each of these categories can contain dozens or even hundreds of types of personal data and the highest advisory council of the Dutch government advised against the implementation of Siri and said that this list is so broad that it is hard to imagine a type of personal data that is not covered in it. So where does Siri get this data from the five big public authorities, which basically make up the welfare state in Holland, the tax service, the unemployment service, the social security bank, the labor inspection, the immigration service and the local municipality. It works by means of the siloing government databases. So these databases are filled with all types of personal data that citizens provided for a very specific purpose, a verification, whether they have the right to a certain social benefit or a tax cut. But all of these data are centralized and combined for a new, very broad purpose, which is risk indication. How does Siri make use of this data? We're very curious about that. What combinations does Siri make? What defines someone as a risk? What logic does Siri use to assess people? So we filed a freedom of information law request and the answer to that proved to be very disappointing. Almost any question you have on Siri was declared confidential by the Ministry of Social Affairs. According to them, it plays into the cards of anticipating fraudsters. So if people would know what Siri is looking for, they would be able to gain the system. So anything has been declared classified. Let's see. However, we did find out a few things about how Siri functions and how it is deployed. It functions as we call it a neighborhood troll net. Referring to the large amount of data that is collected and the people that are analyzed. It analyzes any citizen in one or more postal codes that are next to each other. And every single neighborhood Siri was used, was relatively poor with lots of inhabitants that are dependent on the social services which Siri scans for. And also have a very large amount of people who come from migrant backgrounds. Which is also one of the problems we have with Siri, which I will go into now. We sued the Dutch state in March 2018 with a very broad coalition of several NGOs and two Dutch writers. Our first goal was to delete Siri from law, never to return again. And we also wanted to change the discourse on this topic to mobilize public opinion on instruments like Siri. Our main problems with Siri can be divided into two main topics. Siri is a carte blanche in a black box. The carte blanche part being the government is free to roam through these 17 categories. I just summed up and basically all the data you ever gave to the government is fair game to use for this new, very vague and broad purpose. And the black box part being there is no transparency whatsoever being given about how you are assessed, what data is used exactly what combinations are made. And this in our view creates a paradox of transparency where the government should be as open as possible to citizens and citizens should have a right to a private life. This is completely turned around in Siri. The government being completely intransparent and the citizens being forced to openness about almost every aspect of their personal lives, considering the 17 categories that Siri is free to browse through. And this in our view is a recipe for distrust, which our co-claimants and author Maxine Febedewadi formulated as follows. If you are no longer assessed on the basis of violating a no-norm, but based on secret risk profiles, the fear of repercussions is present in every context with the government. I think that sums up pretty well our main problem with Siri. It creates a climate of distrust which shouldn't exist in a democratic state of law. Well, since we announced our court case, we saw the public debate on Siri and instruments like Siri shifts. How did this happen? Well, first of all and most importantly, it appears that the citizens you analyze with Siri are not too keen on this. Siri was used in two districts in Rotterdam, in Rotterdam south, the poor part of Rotterdam. And when the labor union part of our coalition spread the word about Siri in these two districts and organized a public event to inform citizens that it was considered very controversial by the inhabitants, they felt they were treated like criminals with the city specifically picking their neighborhood to scan. And a short interview from the Dutch daily trou is very telling in my opinion. I interviewed an attendee on the information event we organized. Deeply offended is Majo Boekeu. The Rotterdamer has been living in the Netherlands for almost half a century, 50 years in which he worked hard as a carpenter that blighted up Sue as the father for his three children. They all have a job, he says proudly. And now this with a swinging arm, he points to the apartment blocks in his Hillesluis neighborhood. They live there, the criminals. I am one too. Apparently I've worked for nothing all those years. I think this is pretty telling how on how you feel when when when the government has decided to pick your neighborhood to turn everybody inside out, looking for reasons to investigate citizens. Other developments in the in the shifting public debate on Syria is that a week after the protests in Rotterdam arose, Major Abu Talib announced that he would stop the the Syria investigation because of a conflict with the ministry about using even police and medical data, the only two types of data that weren't yet in the scope of Syria. The ministry wanted to use these these data too in the in the Syria investigation in the Rotterdam city. The mayor of Rotterdam couldn't agree with that. In the same week, the Volkskathons revealed that Syria hasn't caught a single thruster since its adoption. There were very, very many different reasons for that. But the main reason was were technical and capacity problems, but also a lack of added value. So I can get into that after the presentation. But in my view, it's really showed that Syria really has no extra value on top of already existing less far-reaching instruments the government already has. And last but not least, a week before the the court's session was held, the human special rapporteur on extreme poverty and human rights condemned Syria in a letter to court, calling it a digital equivalent of inspectors knocking on every door in a in a in a district. And I want to go to the verdict that came on February 5th two months ago. So it was a big win for our coalition. The serial legislation was declared non-binding, which is the most rigorous way for for a court to to to to deem something illegitimate. We had a victory on the most important and fundamental points that that that exist in the in privacy and data protection laws, things like transparency, which the court called the leading principle of of data and privacy protection, verifiability, data minimization. So we won on there was we were we were we had a bit fear that that that's the verdict would present a repair option. So that's a few cosmetic changes could be brought to Syria and and the government could just go on using it. But that's not an option anymore. The verdict is very, very fundamental. And it really leaves no room for a system that's that's as far reaching and in transparent as Syria. So we are quite happy about that. The most important point points of victory being insufficiently transparent and verifiable. Therefore, citizens cannot defend themselves against the data analysis carried out. And it's based on fundamentals of privacy and data law protection, data protection law. And one of the biggest wins in our view is that the the the the the the the the the the hate court confirmed that instruments like Syria can have a chilling effect on the willingness to share information. So that it was one of our main problems with Syria that it creates a climate of distrust between the state and its citizens. I won't want to don't want to tire you with long citations from the verdict. But I am now because this is one of the best fragments of the of the verdict. It's citizens should be able to defend themselves against the fact that the risk reporters have been submitted about him or her. But also, if no risk notification is being submitted about a citizen, they still have the right to know how they are being analyzed, what data is being used, they must be able to track their personal data. This really makes it impossible for a Syria like system like Syria ever to be built again. Other positive developments are that several public authorities and governments already are looking at their own data in-house data analysis instruments to assess some based on the the Syria verdict. So the UAFA is the the largest is the unemployment agency in Holland. It's a very big public authority and it's on their own initiative. They are checking their own instruments. That's also and there are also several laws being on hold one at least one big data matching law is being put on hold because of this verdict. It's just it's too far reaching looking at this verdict. So that's also a good thing. Let's see. At the same time, we have the biggest scandal in the Dutch tech service since ever with hundreds and maybe thousands of people forced to pay back tens of thousands of euros without any sufficient legitimation from the tech service. So they can't even prove that they were fraudsters and the people that are being being treated as fraudsters still don't know why they are being treated as fraudsters by the by the tech service. So it is a very bad thing to happen to the people but it did create a perfect storm for the Syria verdict because it is clear to everyone now that analysis can have a very very very big impact on people's lives and it can actually destroy people's lives as we have seen in Holland. So the Syria court case provides very valuable lessons in the strong legal precedent for current and future data analysis practices. But still we need to actively push these lessons because not all governments and public authorities will take their own responsibility. So that's a thing we need to keep an eye on in the future. That was it. Thank you very much for listening to my talk. I hope it's been clear and it's been interesting.