The floor is yours. Good afternoon, everybody. My name is Sasha Gzerosky. I come from Ljubljana, which is really not far from Trieste. It's about an hour's drive. My primary affiliation is with the Jozhev-Stefan Institute. This is a large research institute in natural and technical sciences. It has at least three departments that are working on artificial intelligence and at least five departments that are working on material sciences from nanostructured materials to ceramics and whatnot.  And there have not been many applications of machine learning to materials in Ljubljana. Special thanks to the organizers for inviting me because actually that has changed in the last month or so since I was invited to give the talk here. I will talk today about some of the methods that my group has developed, some machine learning methods that actually produce explainable models. And they work on relatively complex data, molecules, structured objects. And actually, you need to deal with structured objects to learn predictive models on them. But first things first. So QSAR stands for Quantitative Structure Activity Relationships Modeling. So here we are learning models for predicting one or more properties of chemical compounds. And the relation to this workshop is that actually we could do pretty much the same for materials. And as you can see, we are actually doing it. Now just to illustrate this, the task of QSAR modeling is to predict the property of chemical compounds. For example, activity against a particular pathogen, say tuberculosis. And you can see on this slide already that the compounds are naturally represented by graphs. And the property that we want to predict might be, let's say, a real valued number. So this is actually regression on structured objects. Now when I say complex data, it's useful to have a reference. What is simple and what are we comparing complex to? And the simple data form that I take as baseline is what most people are used to actually from statistics from several hundreds of years ago. But you have a single table of data where you have a target property or dependent variable that you want to predict on one hand.  And we can talk about regression tasks if all of the columns are real valued. But if the target column that we want to predict is discrete, let's say, has just values yes or no, we are talking about classification problems. So this is our baseline. This is what I will call simple data. And when we talk about complex data, there is actually quite a few additional dimensions of complexity that you might consider. There's been a lot of talk about big data. I'm sure you have heard the terms. And already there, there is a number of dimensions along which you consider the data big or complex. So one of these can be the volume. You can have a large number of columns in these data tables, which I showed. And here you need to do some selection on those or maybe estimating the importance. Then you can have a large number of rows or massive data. And the extreme of this is the paradigm of data streams where you have potentially infinite number of data points and the data just keep coming and keep coming and you cannot count on loading all of the data before you start processing. But you really need to do incremental learning from the data as the data arrives. And then you need to throw the data away and focus on the new data that is coming. But another important aspect is actually the variety of the data. And this is the dimension of complexity where we compare it to the simple tables which we saw on the previous slide. And we can have structured inputs as a type of complexity. We can also have structured outputs as a type of complexity. So this slide you already saw where the data are not really just throws in the table but naturally have a structure. For example, you can represent molecules as graphs. This is the case of structured inputs and I will show a bit later other examples of structured inputs. But then there is also structured outputs where the value that you want to predict is not just a simple scalar. This can be a vector but maybe even a hierarchical structure, let's say in the case of hierarchical classification. So here we have the two basic tasks of multi-target classification and multi-target regression where you need to predict a number of discrete variables or a number of continuous variables simultaneously. And the very natural example of such a task is actually weather prediction. Of course, certain aspects of the weather if we would just want to predict the outlook, whether it will be sunny or overcast, this is a classification problem. If we want to predict the temperature, let's say degree Celsius, this is a regression problem, but really weather is a complex phenomenon. You should really take a look at the outlook, the temperature, the humidity, the potential quantity of precipitation, the wind, the direction of the wind, the magnitude of the wind. So these are all, there's a whole number of variables that describe the weather and that are interrelated and they make a lot of sense, it makes a lot of sense to predict them all together rather than each of them separately. So this is the motivation for developing methods for multi-target prediction, okay? And actually we have a whole taxonomy of multi-target prediction tasks. We can have, of course, we already saw multi-target regression and multi-target classification, but you can actually have additional layers of structure on the target variables that you want to predict. A case is important, this hierarchical multi-label classification where the labels that you want to predict have some relations between them and these relations are hierarchically structured. For example, this can be the case if you want to predict the species, let's say present and a certain sample of water, they can, let's say from the Adriatic Sea, just a few minutes from here. And there the living organisms are organized in a taxonomy and actually in each sample, you can have more than one animal or plant present. So this is clearly a task of multi-target prediction and taking the taxonomy of living organisms into account. It's a task of hierarchical multi-label classification where multi-label classification means that each target can only be binary, okay? So this is an example of a multi-label classification task. The data in this table do not come from the Adriatic Sea, they come from reverse in Slovenia, but they are real data measured in the course of monitoring water quality in Slovenia. And we have a number of descriptive variables which describe the water, let's say the water temperature, the concentration of different pollutants like nitrates, concentration of oxygen and so on and so forth. And on the target side, we have a number of organisms for we want to predict the presence or absence, okay? And here we have an example of hierarchical multi-label classification task where we do have this taxonomy of living organisms taken into account. And an additional dimension of complexity, even though you might not consider it as such in the first instance is missing labels in the data. Normally, if you want to solve a regression task or a classification task and you have a data point where the label is missing, you don't know the value of the dependent variable at that data point, you cannot use that data point in the construction of the model. And in semi-supervised learning, actually the task is to take into account both data points with labels for the target and data points which are unlabeled in the learning process. And it's clear that there are benefits to using such unlabeled data points, especially when the labels are not easy to acquire expensive laborious and such like. And a case in point is in fact, structure activity relationships modeling. If we want to test a particular chemical compound for its activity, let's say against tuberculosis or salmonella, we need to perform an experiment in the lab to determine that. We grow a cell culture, we infect the cell culture with salmonella, let's say, and then we try different chemical compounds to see whether they reduce the number of bacteria and each additional compound that we want to test means extra time, extra labor, extra money. So this is why it is very desirable to be able to also use unlabeled data in the process of constructing predictive models, okay? And of course, we can get exactly the same problem, not only for classification and regression, but we can get it for multi-label classification, hierarchical multi-label classification and multi-target regression. And in fact, here it is even more likely that we will get this problem because the labels are more complex and more expensive to acquire. It's of course more expensive to test a compound for its activity against tuberculosis, salmonella, lepra and what else pathogens rather than just for a single one. So the labels are more complex and more expensive to acquire which means we are more likely to have data points where not all of the properties of interests are measured. And you can expect the same actually for materials, you might synthesize a material and then measure just some of its properties and not all of its properties that might interest you. So for some of the data points that you would actually then have missing values. And these target values might be missing for all of the targets, but they might be missing just for some of the targets. Here we have just the value of the first target missing and for the other two we have the measured values, okay? So a case in point which I would also like to mention here and you already had quite a few talks about neural networks, some of them today and deep neural networks as well. And in fact, deep neural networks are very good at learning from complex data, including graphs, you have graph neural networks, but a problem that they have is that they cannot easily explain their thinking, their predictions. And another problem they have is that they are very data hungry and in principle, they need lots of labeled data and cannot learn much from few data points. Granted, there are approaches like transfer learning, you can do all sorts of tricks to try to alleviate these problems, but naturally they have this inherent problem. And the kind of explainability I'm referring to is that, okay, you might want to explain the predictions, but you might also want to look at the model that has been learned and see what is the importance of different variables, possibly their interconnections, their interactions. And this is very, very important in medicine and it is also important in different kinds of science, including material science. So we have been focusing in my group on learning explainable models and of course, a very common form of explainable models are classification trees on one hand and classification rules on the other hand. And I will not go here into the history of AI, but really the expert systems, the first kind of artifacts that define the appearance of artificial intelligence or focus around expert systems which contain if-then rules to represent the knowledge. And lots of the developments that took place in machine learning were highly motivated by the fact that humans cannot just easily state all of the rules they follow, but rather such rules will learn from examples of people's behavior and problem solving. In any case, from tables of data like the ones we saw earlier, and this is another table of real-world data from Slovenia. Slovenia has a very large and lively population of brown bears. In fact, one morning there was report on the news that a baby brown bear was found just outside Ljubljana Zoo and it did not come from the zoo. So we have been doing some work on modeling habitats, usability and also population dynamics for the brown bears. And these are data collected by our forestry colleagues which describe different locations in terms of predominant land cover forest grassland, proximity to settlements and also the forest abundance. And from this we can learn very simple models like the model here at the bottom in the form of if-then rule which says that bears like forests and it should be dense forest and also bears like they are peace and quiet. So it's about a mile outside of settlements that they feel comfortable. Of course, this is only for the male bears. Mama bears are very, very fussy. When it comes about the cubs they want the specific type of forest. It can't be just standing forest, it has to be beach forest, but I'm digressing. So the point is that we have explainable models that we can take a look at. I was just explaining to the models about the brown bears and we were making jokes about it. And in a very similar fashion we can explain also models for multi-label classification. So here we have a decision tree for multi-label classification. It looks at nitrates, concentration of nitrates. This is chemical oxygen demand. And if both are high we come to a prediction that we have Niciapalea and Tupefax present. Niciapalea is an algae which is very tolerant to pollution.  And so we have high oxygen demand, lots of nitrates and we have bio indicator species which are indicative of such conditions. And similarly we can have decision trees that predict the composition of the structure of living organisms that can be found in particular sites here for Slovenian rivers. Okay, and we can have such trees for predicting one or multiple targets also learned on relational data. I was showing you earlier data about chemical compounds. These are data from another domain. These are about movies. This is actually from the IMDB. And we have movies and we have ratings for the movies made by users and we have information on the users, the nations, what regions the nations are in. And we can then learn models like this one. This one says that, okay, if a movie has at most 213 ratings it's a drama else if the average age of users who rated this movie is above 42.2 is a comedy or else it's a thriller. And these features have been learned automatically by the decision tree. There has been no process of constructing embeddings and whatnot and then learning decision tree. The decision tree natively operates with this relational representation which is very powerful. Okay, and in particular for QSAR models we typically have structured data which tells us about atoms in the particular molecules and the connections between the atoms, ring structures and so on and so forth. Okay, so the last item that I would like to mention here is that of course individual trees potentially easy to interpret but they are not always the most accurate. So people quite often resort to learning ensembles of trees and in the ensembles we combine the predictions of the different trees to obtain better predictions. But then of course we lose the interpretability which is why feature importance estimation approaches used together with three ensembles are very, very important. And in a nutshell what we have been doing in my group we have been adapting these methods for learning decision trees and three ensembles to A, do structured output prediction to do multi-target regression to do multi-target classification to do hierarchical multi-label classification. So to address all of these different tasks of predicting not just a scholar but rather a data structure. And then we have been adopting them to handle semi-supervised learning the task of handling missing labels. Of course three ensembles and then finally also producing feature rankings based on these three ensembles and then some other feature ranking methods. And all of these are implemented and publicly available in a software package which is called CLUS which can do all of these things and in fact rather the Cartesian product. So we can do semi-supervised hierarchical multi-label classification and we can do of course three ensembles for that and feature ranking for that. And we have a relatively more recent software which can learn relational classification trees, ensembles and also produce rankings in this relational context. And I will not talk more about this more complicated case about the relational trees. I will now just very briefly give you an idea about how you can learn these trees for multi-target prediction and ensembles and what are the key things that you need to do to extend the classical algorithm for top-down induction of decision trees to do multi-target prediction or also potentially hierarchical multi-label classification. So the algorithm for constructing a decision tree from a training set, first it looks at a boundary condition and it says if all of the examples in the data set have a low variance of the target, okay? So this means they are all very close together in the target space. And in that case really we can make a leaf and take the average of their targets or the prototype as the prediction, okay? So this is the boundary condition. In the case we have a single target variable we are having regression. This really is the boundary case which is also used in ordinary decision trees. Now you will notice that this notion of variance here can be actually generalized and it can be defined over multiple targets. It is the same notion of variance that is used in clustering. You know, in clustering you want clusters which are compact, which have low within cluster or intra cluster variance. And it's exactly the same notion of clustering. So predictive clustering trees use this notion of variance from clustering which is extended to the multi-dimensional case. As opposed to just the notion of variance of a single real value variable, okay? And if the data are not very homogeneous then we have to select an attribute an independent variable to put in the root of the tree. And we do this based on the reduction of variance that is done by putting that test in the tree. So whichever attribute, whichever test reduces the most the variance of the target is selected to put in the tree. The data partitioned according to the test and then we recursively construct sub trees for the data sets that resulted from the partition. So really this is the same algorithm for learning decision trees except that this notion of variance is now generalized. And of course, when you calculate the prediction to put in the leaf, it should really be a multi-dimensional average or other form of prototype or a representative object that has to go in the leaf as a prediction. And this is just what I was explaining that this notion of variance is really the notion of intra cluster or within cluster variance from clustering which is really the average squared distance between each example and the average, the centroid of the cluster. And there are differences of course between doing predictive modeling, single target between doing clustering in between doing predictive clustering. So in predictive modeling, you can see that your clusters really are compact only along one dimension. And this is the dimension of the target because you only care about the prediction. In predictive modeling, one target, the clusters really need to be compact only along this Y dimension. And along the other dimensions, they can be arbitrarily spread. And here we have a decision tree, very small one which produces two such clusters. And of course there is an explanation of each of the clusters which is if B is satisfied, then we go to this one. If it's not, we go to the other one. In clustering, in contrast, we do not have a condition on which to split the data. We have the two clusters and a defining feature is they need to be compact and they need to be compact along all of the dimensions considered. So really we are looking at hyperspheres that need to be compact, not too large volume. And at the bottom here, we have actually the notion of predictive clustering which combines the two paradigms. You get three which partitions the data into clusters and then the clusters need to be compact along more than one dimension. Should you choose, and in fact, the predictive clustering trees are general. If you say that you only take into account a single target dimension, you get ordinary decision trees. If you say that you want to take all of the dimensions into account, you get standard clustering. And if you select a subset of the measures that you want to predict, you are somewhere in between, okay? And the algorithm is really very much the same as the usual algorithm for learning decision trees except that this variance function here, which I mentioned, if you want to do multi-target regression, you sum the variances along each of the targets. And this is your new variance. So your variance is now more complex than it used to be. Okay, and you might wonder, why would you want to build now a tree which predicts all of the targets at the same time? You could just as well build a single tree for each of the targets. And you wouldn't need to listen to my lecture here, okay? But the point is that if you try this in practice on average across a number of domains, you actually get a clear advantage of predicting the targets simultaneously as opposed to each of them separately. And here we have an example from three actually domains. These are all from ecology. The first one is Slovenian rivers. The second one is Danish farms. And the third one is Australian vegetation. And you actually have quite a large number of targets to predict in each of these cases. So for Danish farms, I think we had the smallest number somewhere around 50, 60 targets to predict. In Slovenia, we had maybe about 500 targets to predict. And in Australia, more than 3000 targets to predict. And if you take the results on average, the left-most column is for single target prediction, we build a separate model for each of the targets. The next one is multi-target prediction. We build one model predicting all of the targets. And the third column is hierarchical multi-label classification because these are all community prediction problems. All of the species are living organisms. They can be placed within the taxonomy of living organisms. So we can do hierarchical multi-label classification rather than just multi-label classification. And there is a clear gradient of improvement if you go from single target to multi-label from multi-label to hierarchical multi-label. And the last step here is if you use ensembles in the end on top of everything. And the key to this, why this happens, is that actually you do not overfit as much when you build multi-target prediction trees as you can overfit when you build a single tree. When you build a tree for a single target, you can fit and you can adapt to that target a lot, especially if you have a lot of data. Then you can build very large trees, very branched. However, if you need to predict more than one target, if you overfit one, you will be underfitting the other one. So getting a balance, three balanced in the sense that it predicts all the targets well, is a much more difficult task. And to do that, you must not overfit. And we were clearly actually measuring these overfitting scores, which are shown here at the bottom, which demonstrated that it's really the prevention of overfitting that is making the multi-target prediction models perform better. And next, I would like to say a few words about how we can adapt these approaches to semi-supervised learning. It's actually very, very easy. In this function, which is calculating the variance, we don't take into account just the variance across the targets. The y's are the targets. And the x's are also the independent variables. So actually to this variance function, instead of the targets or in addition to the targets, we consider also the inputs with some weight. And this weight actually can be tuned. And we usually tune it by internal cross-validation. And with that, actually, we can very, very well handle unlabeled examples. Because for the unlabeled examples, we can calculate the variances here. Of course, for them, we cannot calculate the variance on the targets if the data on the targets are easy. At least the contribution of these data points to the variance. And this, actually, you don't need to read this slide, but you will notice lots of red numbers. And the red numbers means that semi-supervised learning performs better than fully supervised learning. And semi-supervised learning can take into account the unlabeled data. And it clearly performs better than supervised learning. What is even more important is that actually, by using semi-supervised learning, you can learn smaller models that are just as accurate, or maybe even more accurate than the ones you got from fully supervised learning. And I have here an example which is a favorite for me, because the three learned in fully supervised learning, it only uses 50 labeled examples. You see it has 11 nodes and accuracy 81%. The three on the right-hand side was learned using the exact same 50 labeled data points. But also, the learning algorithm had some 2,000 more unlabeled data points. And by learning from both the labeled and unlabeled data points, we get a tree which is smaller. Not by much, but still with these two nodes less. And much, much more accurate. So the accuracy goes from 81% to 92%. So this is why I actually like this a lot. So I don't know how to turn this. OK, good. And the last thing I will mention here is that we can actually also produce feature rankings, because we can learn trees. And we can learn three ensembles for multi-target prediction. And if we build an ensemble, we can then compute their feature rankings by using, let's say, the random forest score, or Gini3 score, or some other scores adopted from single-target prediction. So we can have feature ranking for all of the different types of multi-target prediction. And also, this actually works for ensembles of relational trees. And we are the first to actually consider even feature importance estimation in the context of learning relational models. So before concluding, I would like to show a couple of examples of how we use this for QSAR modeling for virtual compound screening. In fact, the first one was a collaboration with Leiden University. We were looking at host-directed drugs for tuberculosis and salmonella. And the second one was actually a collaboration with Trieste, another research institute, ICGEB. It's in Padrecano. And there we were looking for potential drugs that would help recover after heart attack. So here in QSAR modeling for virtual compound screening, you actually construct some descriptive variables to describe the compounds. And this can be of structural nature. But they could also describe the compounds in terms of proteins they target from some public databases such as PubCamp. And here you can see that actually this is a relational problem. You can have the structure of the compounds in terms of atoms and bonds, but also functional groups and also the protein targets. These are all one-to-many relationships. This is not straightforward to convert into a table. So as I mentioned, we were looking here for host-targeted drugs for tuberculosis and salmonella. Our colleagues from Leiden tried out this library of pharmacologically active compounds, more than 1,200 compounds. And they measured the reduction in bacterial load. So this is a measure how effective the compound this is in killing the bacteria, essentially.   You want the host to survive. So we therefore look at both bacterial load reduction and host cell viability. And we build multi-target, in particular, multi-target regression models for predicting these two properties of the compounds. And in fact, here we were able to greatly increase the proportion of heat compounds. So we build model from these 1,200-plus compounds. And then we apply these models to the whole of PAPCAM, to millions of compounds. And from these, we get a small number of candidates, let's say on the order of 10s, or maybe 100 at most. And if you think our collaborators just went for the top five and tested them, this is not how it worked. They went through the list and they said, maybe at position 12. I said, oh, I have this one in the fridge. So do pass that one. And then at position 27, they said, oh, yeah, the colleague from the other institute has that. Oh, no, this one is expensive. Let's go for this other cheaper one. And even so, even though they did not take the best rank compounds we predicted, they still got a much, much better success rate of heat compounds than just screening the large number of compounds. Okay, and the second example, which I had mentioned, and this was actually an example of so-called high-content screening. Here the effect of a compound on cellular culture is actually assessed by taking a photograph of the cellular culture under the microscope and then extracting some feature of that photograph using some image processing. Okay, the task here was to identify drugs to reduce fibrosis in myocardial infarction. So this is after heart attack. And here we were actually quite successful. And very recently we had a nice publication in cell death and disease. We identified one compound which was working very well. And then colleagues in synthetic chemistry modified it to be more suited for delivery to the chest, to the lungs. So that was a very nice example of collaboration. And in fact, the other one, excuse me, how do you go back? Okay, yeah. The other one for tuberculosis salmonella, this was actually also published in nature communications of quite nice publications. But what I would like to say is that you can do more or less exactly the same for predicting properties of materials. And there you typically have multiple properties of materials that you would want to predict. And typically you have missing values of the targets for at least some of the materials that have been synthesized and characterized. And we were able to experience this firsthand and I'm using this opportunity to invite you to visit the posters. Today, there is one where we were looking at corrosion inhibitors. Then there is another one where we were looking into foam glass and properties of foam glass. And then one more for learning actually to predict properties of electro-catalysts. And this will all be presented at the poster session today. I hope to see you there. And tomorrow, Cynthia has an oral presentation about mechanical compounds, about mechanical properties of tungsten-based composites. These are used actually in fusion reactors. And we have also very nice results here. And I hope you will be here for Cynthia's lecture tomorrow. Thank you so much. Thank you very much for the nice talk. I see already a question here. I'm gonna give you the priority. Thanks for a different talk. And I'll start actually about the size of the data. Do you hear me? Is it echoing? Okay, so I'll repeat again. Okay. So the question is about the size of the data. Yeah, and the sensitivity towards the prediction of the model. Because it's like whatever, I mean like in medicinal sciences and all, whatever I have seen, change of the, I mean like some of the features, numbers and all, doesn't affect a lot of the prediction of the notes and all. So it's your guess about if somebody's trying to replicate that for material science designs and all. So the size of the data definitely matters. And for some of the data sets that we analyzed for the poster presentations tonight, the data sets were very small, you know, and we had maybe like tens of compounds. And there, of course, you cannot expect great results, but still, if you evaluate the results properly, when you test the predictive power of the models, if you do cross-validations rather than just testing on the training set, and if you actually have realistic scenarios of how you will use this in practice and adapt the evaluation to that, I still think the machine learning methods can be very useful. And I mean, and what's your, I mean, guess it will be when you are, I mean, going down the notes, trying to find some unique patterns about two different like variables or features that may be in case of material science design. So what you will say, when we'll start to lose the interpretability of the model, because as we go down, we'll find some new things that we haven't seen on the data, but how much down we can go before we... Of course, a tree, a tree which is 30 levels deep is not very interpretable, but with the, and this is the same problem with the three ensembles, but you have this feature importance estimates, which are actually very, very helpful. And our domain experts typically do look at the feature rankings and see if this has meanings to them. And for example, this can influence their experimental design when synthesizing materials. We experienced in one of the applications in material sciences that will be presented tomorrow, for example, and another one in the posters. So if you have a domain experts which understands the data well on one hand, and you have some interpretability, I'm not claiming that the ensembles you will get to the bottom of it, but still the feature importance estimates tell you quite some of the story, then you can get useful feedback for modifying the experimental design and exploring further alternatives. If I'm allowed one last one. Okay. I'm around all the way to the end on Friday. One question. Sorry, you can, yeah. Somebody else? Well then if there's no one else, I will give you the mic. Okay, so if you can go back to the slide number 24, maybe one before, okay, I got lost then. So you talked about that, I mean like when we move from the, I mean like say, yeah, this one, yeah. So from STP to NTP, when you're increasing, I see that for Slovenia rivers to these farms, to these vegetation, different types of data set that you have, the increase from STP to MTP isn't always that great. Yes, and there's a very good explanation for that. For the Danish farms, you have very few targets relatively. And if you have two targets, you know, there is only so much room for improvement. And also the room for improvement is smaller if you are looking at ensemble models rather than individual trees. So where there is room for improvement, you know, this multi-target prediction improves it. But there is no room for improvement or there's very little room, you just get that little extra increment that is possible to get. It's still, it really helps you squeeze out the most that there is in your data. Yeah, it achieves the achievable, I get it. Thanks. Okay. So I think we have no time left, but thank you very much again. Yeah, thank you very much.


Wow, what's up everybody once again, it's brand man Sean and today we got to talk about yellow Beezie and how he can create a little bit of longevity in the game. Now first if you don't know who yellow Beezie is, well you might have heard his single that's on me. And if you haven't heard that single, well maybe you know him as the rapper who made it rain on his own mama. And those things are cool, but I'm not here to talk about that today. Right now as I said we're talking about longevity. Now if you can see on worldstar he has videos that have like 3 million views, maybe he has a couple more million view videos, but really that isn't even necessarily blown up by a lot of people's standards. I know that is for a lot of young artists, hey y'all can't wait to get a million views and I know that is for people who discovered him early on, but he's still at a relatively early place in the game and what makes him unique in his position is he's coming from a city where there's not really a lot of big artists that are popping in the game Dallas Texas. You really haven't seen artists come from Dallas Texas and really make it make it out. He is that artist. Right now he's being positioned as that artist and he's really showing love to Dallas Texas. Always talking about hey we come from a place that's a lot of good artists. I don't really hear nobody out there like that that's winning, having really seen it.   He's like on the Astrid, but like for like just the Street Rappers broke through yet like for the mainstream. We got a lot of talent there and I'm not just saying they just couldn't, we got some real talented motherfuckers out there.   Like if they ain't heard about it, they finna see the whole Dallas scene just pop up and I promise you that. Unfortunately the biggest artist that is a rapper that came out of Dallas Texas is Vanilla Ice. The reason all that stuff is so important is any of you guys and gals out there who are coming from a city where it's not a lot of people that have really made it in the game or from then you actually have an opportunity to for real put your city on. That's what a lot of you guys really want to do out there is dope, but it can't just be like hey I'm the first person that came from this city so I'm putting the city on my back. One it does take you mentioning the city, but the next level and to really do it and create longevity in your career whether or not you become huge huge or not is taking on the Gucci Mane effect. If you watched that video I did on Gucci Mane, I'll put the link in the description below. You create a legitimate infrastructure where you're giving light to other rap artists, other whatever kind of artists and also other producers and not only giving them support because you're signing all of them, but giving them support when they're unsigned and they're still free in their situations to do whatever you want to do and just be cool because that gives you the leverage not only do you put the city and give it a name, but you also put other people on and help change their lives or give them small opportunities. It doesn't mean you have to change everybody's lives, but there's two ways to do that. You get a little bit of money and you can start that off before you get huge or you can wait and have a little bit more leverage. You can go through and jump some more of the hoops in the game starting to learn more stuff. So then you take that knowledge and you take hopefully the money in a bigger brand and back and that's going to give you even more leverage when you try to build something back home to help put your city on. So yellow BZ Heath early in the game relatively he could wait which I would probably recommend to full on put the city on his back. But that's an opportunity that really does exist for a lot of you guys out there. J Cole basically did it for his folks. A lot of artists have done that for their folks in one way or another. Tech nine has done that for his folks. It could be you. We already know Atlanta's on lock, LA's on lock, New York's on lock.  So all I want to talk about for this video because I know there's some artists in similar positions while watching these videos. We'll love to know what you guys think about it. We'll love to know you guys personal aspirations or how you want to position yourself in the game and in reference to your city, whether you're from a big city, small city, but other than that, if you like this video, go ahead and hit the like button. If you like it, mine's well shared and if you're not subscribed, you know what to do. Hit that subscribe.


As we are all aware that disaster strikes many parts of the world every year and they are in the form of whether it is earthquake or it is flood or it is tsunami or any flash floods etc. So these are inevitable as such but we need to prepare ourselves for the disaster so as to mitigate the effects of the disaster which affects not only about social life but it affects the economy of the nation as a whole. So the objective of this particular study question is to have management for disaster risk reduction so as to mitigate the effect of the disaster. In this question we are studying, we are examining the various kinds of technologies which can be utilized for disaster prediction, its preparedness, its monitoring, its rescue and relief operations and post disaster effect and by this way we are collaborating and cooperating with each other to share our knowledge and the best practices so as to prepare the emergency telecommunication plan to put in place so as to have been better prepared whenever a disaster comes. ICT's role of ICT is very well known whether it is disaster prediction or preparedness by way of communication because during the disaster or before the disaster the information flow is very very important, the information has to be timely, predictable and effective and when this vital flow of information is important for the governments and other agencies which are involved in disaster application, disaster management for that whether it is information coming from mobile network or from satellite network or from the internet this is this plays a very very important role. So communication is a preliminary thing and we have to have effective ICT network in place so that whenever the disaster strikes we should have the early warning system in place and we are better prepared using ICT and nowadays when we are moving towards era of IoT and machine to machine communication their role becomes more and more important with the help of the sensors and actuator when we put on the seabed or ocean floors or at the various portion of the earth we can come to know about the movement of the earth and we can detect that whether any inevitable disaster is going to strike this helps us to have better prepare and using the satellite communication whenever there is a infrastructure collapse takes place in terms of terrestrial infrastructure we can have better communication even during the disaster and after the disaster. So ICT plays a very very important role and post disaster also anthropological challenges which we face ICT plays an important role in overcoming those challenges. Disaster preparedness is a continuous process and it requires continuous updation in our preparedness. So as ITU provide a very good platform for all the nation to come and collaborate and share their knowledge the developed nation which are having resources and knowledge when they share their experiences the developing nation or the nation which get affected frequently due to disaster can prepare themselves and can prepare their emergency telecommunication plan in place and whenever they pose their challenges before the developed nation they also come to know that what kind of requirement will be there for the developing nation or the nation which are getting affected by disaster. So that time immediate you know equipment can be provided and can be transported to other country and since we understand each other's requirement so the regulatory enablement or regulatory requirement can be fulfilled very early so that ICT equipment is put in place during the time of disaster.


Run over to the next court on the other side. I just want to see something. I want to be lonely Stop fanboying bro and play.   Oh my god, iPod literally I can't make this up my guy two minutes in any any park any park two minutes Boom whole crowd and then what does that do for me increase latency? Oh my nightmare. Yes Lady One k friend request pending. I'm hollywood not hollywood. All right.  Just say hi in german. Hello Hey, what we doing? Hey, hello Hello, we are whole god heads Jesus iPod literally I feel like a magnet at all times Hey, y'all run over run over to the next court on the other side. I just want to see something I want to be lonely Run agent run. Jesus Agent It's all right. Hey agent. I'm cold man bring the group back over here. I want to use that iPod. Let me come right back my god Bro, look at this. I I don't know what I did to deserve this man If they if they don't notice the big ass vip logo They'll see my face and notice me and if they don't know it's me They'll get in the game hear my voice and then they'll notice me and if all of that doesn't work iPod They'll see me shoot from full court green light and then they'll for sure notice me because I'm the only one who could do that Right.  I'm gonna be on some Houdini stuff, right? No one's gonna see it coming. You see this you see this you see how I ran here Boom, where'd I go? I disappeared wait wait wait for it a couple seconds.  How did you do that? You see that right there? They didn't see it coming Yo in 2k17 this happened to me a lot where everybody would follow me around So I made a new psn to be covert because I want to record videos without being a target And then I don't really have a choice this year, huh? Oh, we can't hear each other on the got next What a great new addition. I love this feature. Why not, right? Look at the glare on these sunglasses, man I see you iPod Ah So I'm supposed to say Trey way or ssh. Who's who's that? Oh, are you from Toronto? Yeah, I love you man. I love you so much. Hey, what up? What's good, bro? Huge. Oh, got him. Do you guys know who I'm davis is by any chance? Yep, I do Yo, did you know that guy dropped out of high school? I was crazy rise has found that out the other day. I was looking through his high school records, man I like damn, bro. You can even finish high school. Yo asian, what's your thought about this in the game?   Yeah, he's a Oh Yeah, I've been working on this in the my core. Check this out. Wait. Oh, there's too much delay. It's kind of difficult Whoa, whoa, whoa, whoa. Did he say I didn't know how to do it before? Damn, bro, I thought you was a like a subscriber. I thought you really messed with me too, man That's crazy. Yo, why do we get the giant glare on our side and the light disappears when they're playing on offense, man That's not fair Yeah Isn't it so real That's so dope. I'm basically dropping you off in real life and on the game No threes. No threes. I got there Hey, it was nice playing with y'all man.   My fault, bro. Yo, don't drop to the twos next time.   I don't care if I'm fanboying I don't care. Ain't you calling Iso. I see you iPod. That's it. That's it. That's it. That's it. That's it. That's it. You don't want to leave that guy open Anybody with that that? Oh, yeah. Oh, he's coming. That's a misto. He got a right back to you Give me that. Give me that. Yo, let me drop this dude off man. He's talking too much to it. He's talking too much to it.    I just thought it was your mics are trash So let's just use your indoor voices Oh Guys this way there we go right there Hello, how got het you know what that means? No, okay. It was Dutch. Just checking if you dodge. All right. Let's go. Let's get in the game All right, but top right empty court You guys have to go for me Oh My god, I was just watching a YouTube video Oh You know Mike Wang is looking out for these jumpshoots you just jumped you you see that No We said what where do I live? But what are you wearing?  Yes Hey, that's how you get ankysacan right there ladies and gentlemen pay attention. If we win you have to add all of us What No Off off no, uh, you have to I see I was not playing very seriously


Diolch. The first item of business today is portfolio questions, and the first portfolio is COVID-19 recovery in parliamentary business. I would ask those members who wish to request the supplementary question to press their request to speak button during the relevant question or to indicate in the chat function by pressing the letter's RTS during the relevant question. Question 1, Tess White. Dwi'n dod o draws y Cyffredinidau a'r ddwy同 o gaelio i gaelio o'r parffodus o'r Cyffredinidau yn y coronavirus, Rhefoac terfomwyl Scotland Act 2022. Y ddelch yn yr Argych Assumwy Yn y 32 actu sefydlu oedd y Prifysgol Tyfnod 2022 gyda'r Llyfr, gwiriau hefyd.  That review must include consultation with those ministers, which those ministers consider appropriate. If ministers do decide that any measure should be extended, they will lay two documents before Parliament, draft regulations to extend the measures by one year and a statement summarising the review findings, the consultation undertaken and the reasons given for seeking an extension. Any regulations would be subject to the affirmative procedure. The Coronavirus Recovery and Reform Act gave the Scottish Government the power to release prisoners prematurely at the stroke of a ministerial pen. This power was used to disastrous effect during the pandemic when at least 40 per cent of those were released early by this Government. They went on to re-offend. At the very least, will the Cabinet Secretary rule out extending those powers to release prisoners early, given how disastrous the power was used the first time? I wouldn't, for a moment, accept the characterisation of the difficult issues with which we wrestled during the Covid pandemic that Tess White has offered in the supplementary question to me today. The issues that she raises are issues that must be considered carefully by ministers, as I have said in my original answer, be subject to consultation with relevant interested parties. Of course, on that particular power, there would have to be very extensive consultation and dialogue with interested parties, and particularly with victims. I give Parliament the assurance that the Government will carefully consider all of those issues as we would be expected of us under statute. Sharn Dowie To ask the Scottish Government what assessment it has made of the impact on the delivery of its Covid recovery strategy of the auditor general's comments that it underspent its budget by £2 billion in the financial year 2021-22. The Covid recovery strategy is focused on reducing inequalities in tackling poverty, and the Scottish Government is using all available resources to support those in most need during the on-going cost crisis. The Scottish Government annual accounts provide explanations of all significant variances in the portfolio-outturn statements and make it clear that the underspend that was reported does not represent a loss of spending power. The underspend includes more than £900 million of non-cash and ring-fence budgets. It is before allowing for late funding adjustments of more than £500 million and makes use of the limited carry-forward in the Scotland reserve. The Scottish Government has reported transparently at the provisional outturn, and we will confirm the final outturn positioned to Parliament shortly. All funding is fully utilised in supporting the 2022-23 budget. The Deputy First Minister cannot claim that an enormous underspend of £2 billion made no difference to Scotland's recovery from Covid, but let's now focus on making sure that this does not happen again. The auditor general Stephen Boyle has called for greater transparency around the Government's spending. He has said that the Government's accounts do not tell us the full picture. The auditor wants to see a single public sector account. Last week, the Deputy First Minister deflected and refused to give a straight answer, but can the public now have a clear decision? Will the SNP Government be more transparent with its spending or not? The Government is immensely transparent about its expenditure. The Minister for Public Finance has set out to Parliament in a provisional outturn statement. I have come to Parliament about the financial challenges that we face this year in relation to two occasions, which I did not need to do. I came here voluntarily and offered a statement. The Opposition never asked for it. I came here and offered two statements voluntarily involving significant adjustments to our budget for this year. I have to return to the points that I made when I answered Mr Fraser's question on this last week, or perhaps the week before, to Sharon Dowey. It is just simply, completely and utterly economically illiterate for it to be suggested that there is money within that total that I could have spent. I cannot. There are ring-fence budgets of about £900 million that it is beyond my right to spend. If the Conservatives could possibly look at the official report—I went through all of this with Murdo Fraser on 6 December, which is just last week. I went through all of this with Murdo Fraser, and if Sharon Dowey would perhaps go and read the official report, she will understand how ridiculous the question is that she has just put to me, and perhaps put a question to me in due course that perhaps gets nearer to the substance of the issue. Last month, the Deputy First Minister cut £400 million from health and social care budgets, including the primary care improvement fund, which supports GPs to increase capacity in local practices. Does the Deputy First Minister understand why staff and patients are concerned that ministers are picking their pockets by cutting funding, claiming that they have no other choice despite the fact that they sat on an underspend of £2 billion last year? Will he take the opportunity now to indicate that he will reverse those cuts for the next year's budget? I am going to have to send Jackie Baillie a copy of last week's official report. I thought that Jackie Baillie would have known about the fact that there are large parts of the total figures that were set out in the Government's accounts that the Government cannot redeploy for other purposes. Just to reassure Jackie Baillie in case she is worried about this, all available spending power that was not fully utilised last year is being able to be utilised in this and future years, so there is no loss of resources. On the subject of picking pockets, the Government has reallocated resources within the health budget. Nothing has been removed from the health budget. It has been re-prioritised within health to do what? To make sure that we can afford a 7.5 per cent pay deal for agenda for change staff within the health service. We are, in fact, putting money into the pockets of staff, and I am delighted that members of the trade unions Unison and Unite have voted to accept the Government's pay offer. The quality of dialogue between the Government and the trade unions in Scotland is significantly better than the discussions between the United Kingdom Government and the trade unions in England. I might also add that there is Mr Weiss' streeting and the Labour Party in England and the trade unions south of the border. I ask if the Deputy First Minister agrees with me that it would be good to know whether Sharon Downey or any of her Tory colleagues have made any representations to the UK Government ahead of the budget statement to be set out tomorrow for Scotland to be granted borrowing powers that would allow the Scottish Government to manage its budget effectively and to respond to the repeated economic shocks that are created by the ill-judged and damaging economic policies of the UK Government? I assume that you will take from that question, which was not directed per se at you to cover areas within your remit. I certainly will endeavour to do so. The point that Cocab Stewart makes is an important one about the management of the public finances and ensuring that we have sufficient resources at our disposal. If I go back to the point about the under—Sharon Downey asked me if I would avoid any underspend in this year and that it would never happen again. There has been an underspend in every year since the establishment of the Scottish Parliament, so last year was not really any different. I will have more to say to Parliament tomorrow about the current financial position that we face. One of the advantages of the underspend last year is that I have been able to access resources to deal with the enormous financial strain that we are facing this year in the absence of resource borrowing powers that allow me to borrow to deal with the volatility in the public finances. Before I call question 3, I would remind members that they need to be here on time for portfolio questions, which starts at 2 pm. Two members did not manage to do that. When I call those members, I will expect them to apologise to the chair, to the ministers and to other members and also to give them an explanation as to why they were late. To ask the Scottish Government how the development of a talent attraction and migration service will impact on the delivery of its Covid recovery strategy. The Scottish Government is developing a talent attraction migration service, which will launch in 2023. It will attract people to come and live in Scotland, help those moving to Scotland to settle into their communities and support employers to navigate the UK Scotland's complex immigration system. The Covid recovery strategy, which aims to reduce inequalities in reform public services, includes a focus on creating good green jobs across Scotland. The talent attraction migration service will support our wider ambitions in this space by attracting and welcoming people with the necessary skills to contribute to a net zero economy. As he knows, American Space Technology company Mangata has announced press week as a site of its new manufacturing, engineering and operations hub. That will bring a much welcome boost for the local and the national economy. To ask the Scottish Government how its proposed talent attraction and migration service will assist with such projects. I am absolutely delighted with the news that has come forward from Mangata about the investment at Pressweek Airport. It has been a very strong collaborative project involving Scottish Enterprise, South Ayrshire Council and the Ayrshire Growth Deal and the Scottish Government. I am thrilled with the opportunities that have opened up for Pressweek in Siobhan Brown's constituency. The talent attraction and migration service will assist us in trying to support companies who are trying to attract individuals to work in particular ventures. I would imagine that Mangata will be a company that will seek some support from the service to make sure that we can attract the particular and correct skills that we need to make a contribution to the Scottish economy. Obviously, it helps us to overcome some of the issues that are significant obstacles for us just now as a consequence of the loss of free movement of individuals following from the Brexit decisions. To ask the Scottish Government what assessment it has made of how any additional cost of living pressures will impact on the rebuilding of public services as set out in its Covid recovery strategy, particularly in relation to public services here in Edinburgh. The Scottish Government is prioritising funding to support people in most need and to protect the delivery of public services. The emergency budget review confirmed a range of additional support for those in most need, including the expansion and increase of the Scottish child payment. That prioritisation is guided by the principles of the Covid recovery strategy. The overarching ambition of the Covid recovery strategy is to reform public services to ensure that they are ffiscally sustainable and delivered in line with the principles of the Christie commission. In the current context, we are considering all options for reform, which will allow us to deliver that ambition and to continue to deliver high-quality public services across Scotland, including in the city of Edinburgh. The capital has some of the highest vacancies in our public services and also has some of the highest costs of housing and childcare. I have previously raised the potential development of an Edinburgh waiting in pay with the Scottish Government. If you will agree to meet with me to discuss that further, will the Government look to commission university research into the potential need for an Edinburgh waiting, as we have seen taking place in London? Mr Briggs raises serious issues, and I will happily meet him to discuss that concept. On that occasion, we can develop further the thinking about any particular research that will be necessary in that respect. I suspect that there must be some work that has been undertaken. It is a few years since I have been close to that question, but our dear late colleague, Margot McDonnell, was never backwards at coming forwards with me in budget processes in arguing on the issues that Mr Briggs raises with me, so I will happily meet him to discuss that question. With every week that passes, we see the impact of the disastrous mini-budget that trust in our chancellor get carried away continuing to affect Scotland's Covid recovery from the Covid pandemic. Will the Deputy First Minister agree that, given the key policy levers to address this Tory-inflicted cost-11 crisis, it is held by the UK Government? It is high-time of Tory colleagues called on the UK Government to get on with the job of supporting Scottish people through tough times rather than expecting the Scottish Government to continually clean up? The implications of the mini-budget in September will be long-lasting for people and for the public finances of Scotland and the United Kingdom. The irresponsibility of that event—I cannot call it a fiscal event because there was nothing fiscal about it—will have far-reaching implications. We have already seen significant increases in interest rates as a consequence of those decisions. There will be householders and businesses put under pressure as a consequence. The Scottish Government—I will have more to say about this in the budget statement tomorrow—will do all that we can to help people through the cost of living crisis, but we have to acknowledge the severity of the difficulties that were created by the mistakes that were made in the mini-budget in September. Question 5, Rachael Hamilton. First of all, Presiding Officer, can I apologise profusely to you and my colleagues in this chamber for being a couple of minutes late? I started committee at 9.45 and until 1 o'clock, and then I went to see Hoyke High School, who have made the precarious journey up to the Parliament, to answer questions about what we do in this place. I thank Ms Hamilton for the explanation. Obviously, it is not a matter for the chair what other engagements a member seeks to try to figure into. Sorry, you did ask me to. You already have a busy day, but I am pleased with— Point of order, Presiding Officer. Point of order, Rachael Hamilton. You asked me to apologise to my colleagues, to you and to give a reason as to why I was late to the chamber. If I could respond to that point of order specifically, I hear what Ms Hamilton has said by way of an explanation. I was just trying to be helpful for future reference to point out that, obviously, it is not a matter for the chair to work around individual members' busy schedules on a daily basis. I appreciate that the schedules are busy, but equally, a start-time of 2 p.m. remains a start-time of 2 p.m. I would ask Ms Hamilton now to please ask her question. Scottish Government, what it considers to be reasonable grounds to postpone the passage of legislation through Parliament? Thank you, Presiding Officer. I thank Rachael Hamilton for her question. The Government keeps its primary and secondary legislation programmes under careful review and adapts them as necessary. For example, as members are aware, steps were taken to pause delivery of some legislation last session at the height of the pandemic. However, once in Parliament, timing of legislation is for Parliament to agree. Rachael Hamilton. I thank the minister for that answer. This morning, the rain committee of which I'm a member considered the Hunting with Dogs Bill at stage 2 for a second week. The bill was delayed by two weeks as a result of the minister's trip to COP27 in Egypt. We were also afforded the opportunity to hear further evidence on a part of the bill that was causing confusion. In stark contrast, despite the unavailability of a raft of extra evidence—the interim cast review, for example, the UN special rapporteur on violence against women and girls, two separate court rulings on the effect of obtaining a GRC on the definition of women—I could go on. The GRR bill has been railroaded through this Parliament with a total disregard for the need to consider that additional evidence. Why is it that we have one rule for one bill and another rule for GRR? Does the minister recognise the need for us, as legislators, to be allowed to do our jobs and apply adequate scrutiny to legislation using all of the evidence available to us? Thank you, Presiding Officer. I thank the member for her question. The two bills she mentioned show us the flexibilities that are available within the Parliament to actually afford bills to go through. As always, my role as Minister for Parliamentary Business is to work within parliamentary procedure. The timings of bills are dependent on the size and detail of the legislation. Once a bill is in the Scottish Parliament, it is for the Parliament to decide how it proceeds. On some occasions, that might take a faster route than others, depending on what the legislation is and what it is trying to achieve. Parliament itself, Presiding Officer, decides the timings of all bills. Question number 6, Jim Fairlie. Thank you, Presiding Officer. I would like to ask the Scottish Government how its Covid recovery strategy considers the needs of rural communities. Presiding Officer, the Covid recovery strategy sets out an ambitious vision for recovery that is focused on bringing about a fairer future for those most affected during the pandemic, including people living in rural communities. The Covid recovery programme board, which I co-chair alongside the president of COSLA, oversees work to achieve this vision and recognises the need for local communities to inform on-going priorities for recovery. Policies such as the place-based investment fund and the regeneration capital grant fund support investment and regeneration projects that are shaped by the needs and aspirations of local communities and deliver inclusive growth for remote communities. Jim Fairlie. Thank you, the cabinet secretary for that answer. Rural communities, as you know, are often reliant on reliable bus routes that link them to the shops, facilities and amenities in their larger towns and cities. The industry has an acute shortage of drivers, and as the Deputy First Minister will be aware, in October, more than 140 bus departures in Perth and Cunross were cancelled in one day. It is clear as we recover from Covid that Brexit is still having a clear impact on these shortages. I can ask the Deputy First Minister when the Scottish Government last engaged with the UK Government on this, and given the powers to fix it or reside with them, whether they have given any indication on what they intend to do to improve the situation for our rural communities. I acknowledge the significance of the issues that Mr Fairlie raises. We obviously share constituency boundaries, and I am aware of similar issues that have been wrestled with in my constituency. As Constance would have it, the Minister for Transport hosted the second bus task force meeting earlier today, which the United Kingdom Government Minister, Richard Holden, attended to discuss the issue of driver shortages. Obviously, there are, as Mr Fairlie will know, acute shortages of employees across a whole range of different sectors, and it is particularly acute among bus drivers. It has been exacerbated by the loss of free movement of population and the pressures that have been put on our labour market. Yesterday, we had very high levels of employment, announced very low levels of unemployment, so we still have a very tight labour market. We are continuing to work with operators and our partners across the public sector to promote the bus sector as a place to work, while recognising that many of the levers to address the issue of population migration rests with the United Kingdom Government. Driver shortages is an issue, and I have experienced that in my North East Fife constituency as well. We need to make progress on that issue. However, there have been cuts in services in my constituency. In stagecoach tells me that it is because of the fall in usage of buses since the pandemic. I am interested in how the Government is going to drive up passenger numbers and improve usage, and is the community bus fund going to be used to help that? Mr Rennie raises a number of legitimate points in relation to the provision of bus services, and we are trying to support the industry to increase usage. For example, the extension of the concessory travel scheme to young people has had a discernible effect. Obviously, as a consequence of that, there are concessory fares that are contributed by the Government based on usage. Measures like that are designed to try to increase usage of bus services. Obviously, there will be various ways in which we can support the industry. The Government looks to work with the industry to find the most effective ways in which we can do that, and the points that he has made about the community bus fund are points that the Government will consider. Willie Rennie has raised an important point in relation to people seeing bus services being withdrawn entirely for many people living in a rural community. Those who are elderly, for example, who rely upon a bus to get to medical appointments or to avoid social isolation, that causes real concern for them. What will the Scottish Government do in its budget tomorrow to try and support bus services? As it is for me to disclose the details of the budget to Parliament today, Mr Fraser will understand that I cannot do that. I am very mindful of those issues because ensuring that we encourage people to use public transport, particularly for them to be credible bus services that people can choose to, is very much part of the Government's agenda of decarbonising transport as part of our move to net zero. To ask the Scottish Government how its policies across Government will support disabled people living in the north-east to recover from the Covid-19 pandemic. The impacts of the pandemic were not felt evenly across Scotland, and some people, including disabled people, were disproportionately affected. The Scottish Government recognises that the Covid recovery strategy is focused on delivering a fairer future and addressing the systemic inequalities that were exacerbated during the pandemic. In September, the Scottish Government accepted the findings and recommendations of the supported employment review report. Those recommendations include the development of a national infrastructure programme of supported employment quality standards and insurance approach for Scotland and funding for people with lived experience to deliver training to employers to myth bust and raise aspirations. Will the Deputy First Minister provide timelines for the implementation of those recommendations through No One Left Behind and the publication of their planned new policies on supported employment arising from the report's recommendations? I can confirm that the issues raised by Maggie Chapman will be fully addressed as part of the No One Left Behind work that the Government is undertaking. The next stage of development is expected to commence early in the new year and will obviously involve the delivery of specialist support services. I am very happy to update Maggie Chapman on the progress that is made, but it is important that we continue to deliver services to meet the needs of individuals with disabilities and to support their participation within our society and economy. I can call question number eight, but only if the questions are brief and the answers are brief. Question number eight, Paul Sweeney. Thank you, Deputy Presiding Officer. I apologise for being two minutes late to this session of Parliament and also due to being a meeting to do with racism in the Scottish society. Mr Sweeney, please take a seat. I think that in terms of being equal to everybody, I would just remind you that it's not a matter for the chair to fit around a member's schedule. It starts at 2, you were three and a half minutes late, it's a point of fact. Whilst I hear your explanation, it's not really a matter for the chair, but I know that you have apologised, so please now ask your question, but reflect on that perhaps for future portfolio sessions. Thank you, Madam Deputy Presiding Officer. To ask the Scottish Government what impact industrial action by public sector workers will have on delivery of its Covid recovery strategy. The Scottish Government recognises the concerns of public service workers and the need for sustainable pay deals and fair working conditions. Indeed, the Scottish Government has supported public sector pay increases at an anticipated additional cost of £700 million. The Government will continue to engage with different workforces as part of our work to implement the principles of the Covid recovery strategy, which focuses on reforming public services and reducing systemic inequalities. Can I commend the Government for finally stepping into avert industrial action being proposed by nurses in Scotland? It could have and should have been done sooner, but it is certainly better late than never. The minister will know that nurses are not the only public sector workers set to take industrial action if their pay demands are not met, so they commit today to this Government showing the same respect to other vital public sector workers, including hardworking teachers who are in dire straits due to the cost-loving crisis and who are desperately needing a pay increase greater than what is currently on offer. I simply point out to Mr Sweeney that the Government has been actively involved in trying to resolve pay disputes for some considerable time. We were involved. I spent a large part of the summer working to resolve local government pay issues. I spent a large part of the autumn trying to resolve civil service and health service issues. I am delighted, as I said in my answer to Jackie Baillie, that Unison and Unite have accepted the offer that the Government has made. I acknowledge the claim that has been made by members of the teaching profession. I simply say that all claims must be affordable. Mr Sweeney knows very well that the Government is significantly constrained in this financial year by the availability of resources. I have explained all those issues to the leaders of all the teaching trade unions to set out the very real challenges that exist in trying to deliver the pay increase that the teaching profession has put forward, which is, in the Government's view, unaffordable. We are open for negotiations, but the propositions must be affordable and the Government and our local authority partners must be able to find the resources to finance them. Thank you, Deputy First Minister. That concludes Covid-19 recovery and parliamentary business portfolio questions. We will now move on to the next portfolio questions, which is finance and the economy. I remind members that questions 1 and 2 are grouped together and that, therefore, I will take any supplementaries on those questions once they are both answered. If a member wishes to request a supplementary question, they should press the request of speak button or indicate zone chat function by entering the letters RTS during his relevant question. I call question number one, Mercedes Galber. To ask the Scottish Government whether it will incorporate the costed package of tax increases recommended in the Scottish Trade Union Congress commissioned report options for increasing taxes in Scotland to fund investment and public services into its 2023-24 budget. Minister Tom Arthur. The Scottish Government welcomes the report published by the Scottish Trade Union Congress and recognises the contribution such publications make to public discourse on Government finance and tax policy. The Scottish Government will set out its budget position for 2023-24, including proposals on tax policy, fully costed by the Scottish Fiscal Commission tomorrow. The Government is well aware of the indefensible wealth inequalities that blights Scotland, yet when I called on the First Minister to support even the principle of a wealth tax back in June, I was told that this is, quote, not something that this Government has the power to put in place. Last week, the Scottish Trade Union Congress outlined exactly how a wealth tax could be implemented. Instead of pleading powerlessness, can the minister tell us what this Government has done with 15 years in power to develop a wealth tax? The provisions to introduce new national taxes are contained under section 80B of the Scotland Act, which requires an order in council, which requires the agreement of the UK Government. I suggest to the member that that is perhaps the barrier. If she thinks that the Prime Minister will be amenable to the introduction of a wealth tax and the devolution of that power to Scotland, and she has any particular strategic insight in how that can be achieved, I would be most happy to hear from her. Question 2, Gillian Mackay, has joined us remotely. To ask the Scottish Government what its response is to the papers on taxation policy recently published by the Scottish Trade Union Congress and Institute for Public Policy Research Scotland. As outlined in my answer to the previous question, the Scottish Government welcomes both the Scottish Trade Union Congress report and the report by the Institute for Public Policy Research Scotland. We recognise the value of such publications in promoting public discussion on Government finance and tax policy, and we will set out our budget position for 2023-24 tomorrow. I thank the minister for that answer. If he agrees that the reforms previously agreed between the Scottish Greens and the Scottish Government during the last parliamentary session have resulted in a more progressive version of income tax than anywhere else in the UK, were those who earn less pay less and those who earn more pay a bit more, as well as raising additional funds for public services, and does he also agree that a progressive and fair approach to tax in Scotland in stark contrast with the UK Government's chaotic mini-budget tax giveaway to the rich and multiple U-turns has ensured that Scotland is a more equal place and has helped to deliver major projects, such as free bus travel for under 22s and topping up the Scottish child payment. Minister. I do agree with Gillian Mackay. I sense the devolution of income tax. We have created a fairer, more progressive income tax system in Scotland that raises vital revenue for the Scottish budget. That has seen those who are able to contribute a little more while protecting those who are not. That approach has allowed us to maintain the most generous social contract in any part of the UK, with a range of social security payments and public services available uniquely in Scotland. That ensures that Scotland remains a great place to live, work, study and do business in. Our decisions on tax policy for 2023-24 will be set out tomorrow, and we will continue to be guided by the principles of fairness and progressivity set out in our framework for tax. The Office for Budget Responsibility expects living standards to fall by 7 per cent over the next two years due to Tory economic incompetence, meaning that even low to middle earners will inevitably pay more tax. What discussions has the Scottish Government had with the UK Treasury regarding reducing tax avoidance, which the OBR only yesterday estimated at £35 billion a year across the UK to ensure that everyone pays a fair share? Is this something that he believes the Tories take seriously, given who are the Channel Islands and Islayman tax havens, just offshore? Mr Gibson is absolutely right to highlight the OBR's conclusions and that people in Scotland are ultimately paying the price for the UK Government's mistakes. Although the majority of taxes are currently still reserved to Westminster, Scotland's framework for tax specifically sets out that our taxes are designed to combat tax avoidance, and the UK Government should follow our lead. Tax avoidance takes away money that should be used to support households and public services. Funds are needed even more so now, so I will continue to urge the UK Government to tackle tax avoidance of any kind. Question 3, Willie Rennie. To ask the Scottish Government whether it will provide an update on support for liberty steel DL. Minister Ivan McKee. The Scottish Government continues to work closer with Dell Site Management through its agency Scottish Enterprise with the company continuing to trade through a challenging economic climate. The member has recently been advised that payments of the loan provided to DL by Scottish Enterprise have not been made in time, however, debt for bearance is not uncommon in the current market. When the minister reported on the state aid issues to Parliament last December, he said that Tata would need time to reflect on its position. However, our freedom of information release found that Tata had already reflected. It specifically warned the Scottish Government the night before the statement that it would be prepared to take them to court. That was in an official letter on the eve of the ministerial statement. Why did the minister choose not to tell Parliament about the risk of court action the very next day? On 15 December 2021, we advised that Tata Steel were informed of the matter and were provided prior notice of the statement that was delivered in the Scottish Parliament on that date to allow them to consider any commercial implications for the business and ensure that they had time to notify their head office in Mumbai. At the time of the statement that was delivered, it was understandable that Tata Steel would need time to reflect and consider their position. As previously stated, we will continue to have supportive dialogue with Tata and the company of access to our officials as they require. Thank you for asking the Scottish Government when it last met Orkney Islands Council regarding the Scottish budget 2023-24 and what issues were discussed. Scottish Government ministers last met Orkney Islands Council on 30 November 2022 when I met with Councillor James Stalkin, the leader of Orkney Islands Council, to discuss revenue and capital funding regarding the 2023-24 budget, the 2023-24 local government finance settlement and funding for the Orkney Islands Council ferry services. I understand that Councillor Stalkin has written to Mr Swinney this week outlining proposals to operate the special islands needs allowance, which has remained static since 2008-09 when it was cut by 24 per cent. Mr Swinney will know my long-standing and serious concerns about the large disparity in funding that disadvantages Orkney compared to the other island authorities. However, the proposed change to Sina could help to narrow that gap while still benefiting other local authorities throughout through the redistributive floor mechanism. Will the Deputy First Minister take on board the reasonable and progressive proposals and look to include them in the budget for next year? The issues that Mr MacArthur put to me were clearly the issues that were put to you by Councillor Stalkin. Obviously, there is a lot of complexity around the local government finance formula and there is also a procedural question, which is that local government itself is essentially the body that considers changes to the distribution formula through the work of the settlement and distribution group, which is entirely a local authority-led process. I have heard the issues that have been raised by Councillor Stalkin. There is an interaction in some of those questions with the setting of the floor for the local government finance settlement, which is obviously very relevant to that question as well. Those points will be reflected on as the Government formulates its budget and considers that through its passage in Parliament in the course of the next few months. To ask the Scottish Government whether it will provide an update on the public consultation regarding the Scottish aggregates levy. The public consultation on developing a Scottish tax to be placed in UK aggregates levy closed on 5 December. 25 responses were received. Those are currently being analysed and a consultation analysis report will be published in due course. I appreciate the diverse perspectives provided by the range of organisations who responded to the consultation. Consistent with the Scottish approach to taxation, as set out in Scotland's framework for tax, we will continue to consult and engage with stakeholders to help inform the development of the tax. I thank the minister for the answer. Given the concerns raised by many different organisations regarding the short length of time provided for public consultation, how will the Scottish Government ensure that stakeholders are listened to and given a strong voice in the design of the tax? I thank the member for his supplementaries. He will be aware from our framework for tax, one of our principles is engagement. Although the consultation is an important part of the engagement exercise, it does not represent the entirety of the engagement exercise. I remain committed to engaging with stakeholders. My officials have met with stakeholders recently with regard to that, and I will continue to do so going forward. I would be happy to meet any member who has any particular issues that they wish to raise with me on the matter of an agregat tax. To ask the Scottish Government how it will support innovation and entrepreneurship in Scotland's digital economy, including the game sector. The Scottish Government recognises that innovation and entrepreneurship is the real engine of economic growth, and we are supporting Scotland's founders, innovators and entrepreneurs in many different ways by delivering on our national strategies for economic transformation through our forthcoming national innovation strategy and leading entrepreneur and a search review of women and enterprise. Most recently, we launched our national tech scaler network, a £42 million investment that will widen access to entrepreneurial opportunities and support founders, including games company founders, offering free commercial education and mentorship programmes, while also building a dynamic community of innovators and entrepreneurs. Changing misconceptions about the game sector is vital to unlocking its enormous potential, and I was pleased to host the inaugural Scottish Games Week reception here in the Parliament. The game sector message is clear. Through joined-up policy support, it has the potential to be transformative for both Scotland's digital and creative futures. Will the minister be willing to engage with the Scottish Games Network and lize with his counterpart in the culture portfolio to examine how we can support the industry, foster that potential in Scotland's digital and creative futures? I was delighted to attend the event in the Parliament for Scottish Games Week, that Claire Adamson organised, and to be able to speak to the businesses and others that were present at that event, to show the Scottish Government support and recognition of the importance of the sector and how we can work together to build its future. I would be delighted to meet the member to discuss that further. I have no doubt that my ministerial counterparts with responsibility for culture feel likewise on the issue, and, as she indicated, other countries have performed well in this area. It is something that Scotland can absolutely learn from to ensure that our game sector in Scotland fulfills its full global potential. If he will welcome the announcement this morning from the University of St Andrews about the establishment of a new business school, which will focus specifically on innovation, entrepreneurship and the dissemination of digital education. Absolutely, I will. That is part of the very strong and ever-expanding ecosystem across Scotland on innovation, entrepreneurship, our recent investments in NMIS, MMIC and much else that is happening in Scotland's universities and elsewhere, as a real testament to the strength of Scotland's economy now and in the future. The BBC yesterday reported a slowdown in recruitment in the game sector in Scotland as it responds to the cost of living crisis and economic uncertainty. Given Scotland's historic place in the industry, has the minister had a discussion with the sector about the support it needs to continue growing and realise its full economic potentials? We continue to work closely with the game sector, others across the digital economy and across the whole economy. Those businesses, as many others across the whole economy, continue to suffer from a shortage of skills, talent and labour to fuel the growth potential. We continue to work to make sure that those skills are provided as necessary. Despite the comments that the member makes, on that specific issue, the sector will continue to go from strength to strength. The demand is strong, the skills here are great, the businesses are very well founded and we work with them to transmit that and find opportunities globally. Question 8, Grymson. To ask the Scottish Government what its response is to the comments from the oldest general in his 2021-22 audit of the Scottish Government consolidated accounts that financial support for burnt island fabrications limited, Ferguson Marine engineering limited, Presswick airport and the Lochaber aluminium smelter has not delivered expected outcomes and is unlikely to achieve value for money. The Scottish Government's financial support of those businesses is on-going and it is therefore not possible to make a full assessment of the final outcomes or value for money at this point. Where a business face is difficult to that cannot be addressed by a market response and the business is critical to the economy or is a long-term strategic asset, we will rightly consider options for support. The Scottish Government will continue to work with those businesses to deliver value for money for the public purse. That was not really any kind of answer. If we look at Ferguson Marine, the oldest general says this, during 2021-22 the Scottish Government wrote off £52 million from the capital value. The value of vessels 801 and 802 in the consolidated accounts was £78 million. So far, as we know, the cost of building them has been well in excess of £200 million for vessels that are worth £78 million. That gap is only going to get wider, so does the Minister believe that that is value for money? The steps that we have taken to preserve commercial shipbuilding on the Clyde for now and future generations and to maintain that strategic asset in Scotland's economy, we believe, is hugely important. Certainly, the workers and the communities that are employed in Ferguson's would think so. Certainly, those who value the importance of Scotland's commercial shipbuilding assets would think that that was the case too. My colleague the Deputy First Minister has reported back to the Parliament on the specific roundabout the challenges that yards face and the Government support that has been put in place to ensure that the yard continues to operate and deliver those ferries and ferries going forward into the future and will continue to do so. The minister seems very casual in response to losses of hundreds of millions of pounds in the various industrial interventions. Has the minister learned anything from those episodes and those losses? If so, can he tell the chamber what they are? Willie Rennie should have a look at the assets that are in play. The L is still operating and employing a significant number of people producing steel and keeping Scotland's steel production in play. Locarba continues to operate. The smelther is operating very successfully, as is the hydro that is part of that site. Again, it continues to employ hundreds of people on that site. We are glad that we made those interventions back in 2016. We have now had six or more years of continuous production and employment as a consequence of that, paying tax into the Scottish economy, supporting local communities and keeping those strategic assets in play. I do not think that we have got anything to apologise for that. As I have indicated in my previous answers on the subject, of course the Government will step in where, as I have said, there is a strategic asset to be kept in play or something that is of importance for the Scottish economy. By virtue of the fact that it is very nature, those are situations that the private sector has declined to support. The Scottish Government is of course taking itself into a situation where there is a risk of things not working out as we would all hope that they would, but I think that, on balance, much of that has been successful and continues to be so. With regard to Ferguson Marine, does the minister not agree that it is faintly ridiculous that a publicly owned shipyard such as Ferguson's is now dependent almost entirely to avoid redundancies by building subcontract work for B systems on a tech 26 programme for the ministry of defence, whilst the Scottish Government is handing £100 million ferry contract to Turkey's shipyard and probably likely to award another £100 million ferry contract to Turkey's shipyard? Is that not completely contradictory to any idea of a national ferry building or shipbuilding strategy? No, it's not. We've made the decisions on where we're going to place work based on criteria that are in place. We make decisions on supporting and working with strategic assets to ensure that they continue to operate and we work with and encourage other partners across the sector and beyond to co-operate where it makes sense to make sure that businesses flow into different operations and support employment and the future of the sector as a consequence. Thank you minister. That concludes proof of the questions on finance and the economy. There will be a very short pause before we move on to the next item of business. Thank you.


I'll watch the coverings here, the light will cover there, so you guys should sit here. The light will cover there. What's your phone number? 7. Avoid moving on roads and limit open areas of the room. Got a following intel? This is going to provide information on high-value items that are located in Cedar City. Most recent intel has identified possible... from your SP. Once you enter the first building in Cedar City, you will locate and notify the enemy of your location. Locals will notify the enemy of your location. You'll have 50. Got a grid location for you? Here to copy? 1-0 Sierra. Foxtrot Echo. 5-4-8-9-9-4-0-6. That is your SP. 5-4-9-8-9-9-4-0. What? If you're rockin' in there. Do you want to come help? There's not too many people. No, come and look. Alright, so... Can I have someone write this down for me here? I'm going to give you the... This is our blue right here. Yellow and green and yellow, and the blue is the high-value asset. Yeah. Sorry, enough with this. You're saying when you're in there, but when you're in there, making no of what? So when I ask you to pull out of your right... You got to start moving. Yeah. That's our... See, that is our wooden... Yeah. We have all this high-grounded muscle. If you come down here, they can potentially see it. I think that's... That's my click. Go, go, go, go, go, go, go, go, go, go, go, go, go, go, go, go, go. Come back out. Stay right there, stay right there. Alright, I need to boost the charge of this building. Get in the deep house. You didn't tell him? Don't tell him, don't tell him. What's your name? I need someone to take this. I'll take it. He's got the easier guys in the middle of the night. You have to take the 8k for me. Stay where we can? Stay where we can. Stop right in the street. Your door and two windows. What's the other thing? Stay with me. I know, we're staying right here, but we're pulling. Yeah, just one at a time. Here's your mission. People will be moving through the area and require detailed information on the posture of the enemy they may encounter. Your mission is to provide a detail. We'll notify the enemy of your location to complete your mission and expel to the extraction point. Your start point and extraction point is your current location. Those two, that's where they're... Green and blue. No, they're on the floor. Those two were north. These two right here... Okay, north is this way. Blue is northwest. Somebody know your team for green is north. Yellow is north. Have you used this scope before? No, I have not. All right, so I'm going to give you a very quick brief. One's the oxide, and the other side. Those two. It's over here. Okay. On the left, so we got to get... What we got to do is get from here to there. Yeah, but look at it. And then only cover the right. Do we have permission to check it? And you.