 quick introduction to Stavros. So this is called again every time I hire a linguist emergent tech profiles for linguists, translators, and language experts to report on upskills. My name is Laurel Sutton. I'm your host here. Our support person is Marcus Robinson. So you can reach out to him. He's monitoring the chat and he'll be dropping links in. Brief description of what this panel is about. The upskills project is an Erasmus Plus strategic partnership in the EU. So we're getting a European perspective here. It's for higher education that seeks to identify and tackle the gaps and mismatches in skills for linguistics and language students through the development of a new curriculum component and supporting materials to be embedded in existing programs of study. The recent upskills needs analysis, which was done via survey, explored the current academic offer in language and linguistics-related fields and the requirements the job market has for graduates in these areas. And the analysis highlighted the need for a new skill set and a new mind frame to meet the demands, as well as the professional challenges of the industry. And our presenter for this hour is Stavros Asimokopoulos from the University of Malta. So take it away. Hello everyone. Well, let me wish you most of you good morning, I guess, where you are. It's after, it's early afternoon here in the Mediterranean. I would like to first of all thank Laurel and all the organizers for their kind invitation. It's actually really exciting for me to be able to share all these, like our first results from the project with you. Before I start, I'd better explain a little bit the title, probably, oops, oh, anyway, yeah. So basically there's this well-known phrase you know that was produced by Fred Schell in the 1980s, where he said, every time I fire with the performance of our speech recognition system goes up. So this actually, well, this has been misquoted many times and whatnot. I mean, the idea back then was that perhaps artificial intelligence and technology in general can actually, you know, surpass the need for human intervention when it comes to analysis of data and whatnot. Obviously Fred himself, the late Fred and everyone these days actually disagrees with this. It is essential that human intervention is there, even when we're dealing with big data, because unsupervised systems don't work as well as supervised ones do. So basically, our title, my title in this talk is a wordplay on every time I fire linguists with what we were trying to do, the upskills project, what we're trying to do, the upskills project is to identify what are the skills that are needed for students, for graduates of linguistics and language related disciplines, in order to be able to find employment, especially in the industry sector. And this is something that actually is quite topical, I think, when it comes to this distinction, to this discussion. So basically, this is a meme that was created. So job title, linguists, the guys smiling, and then desired qualifications, degree in computer science, and then suddenly becomes a bit like, wow, that's not a linguist then. So basically, what we're trying to do in upskills is to sort of got these two fields to a certain extent by also identifying what kind of skills students need in order to be able to make it in big corporations or companies that have to do with language technology. Now, just a bit of information. This talk and all the materials that are presented here is a joint effort. This is an Erasmus-plus semester with partnership, which receives some funding from the HUE to conduct the research that we're doing and to develop the materials that we will eventually do. We are a consortium of eight partners, six of us, we are the project leader and Valte is the coordinator of the project, but the University of Belgrade, University of Bologna, Clara and Eric, an infrastructure consortium, University of Graz and University of Priyanka receive funding from the Erasmus-plus funding stream. And then the Swiss, our Swiss partners, Geneva and Zürich University, Geneva University of Zürich have received funding from the equivalent of the Erasmus-plus in Switzerland. So this is all a collective effort and everything you're going to see is actually, the slides have been prepared by all of us rather than just me alone. Just representing the consortium. So as Laurel has actually already said, our main aim is to tackle the skills gaps and mismatches in students of language-related disciplines. And our point here is to somehow manage and create a better workforce. How are we going to, like, what's the rationale behind this project? Oh, my computer is slow, I think. Okay, okay. So the rationale is that graduates of linguistics and language-related degrees, again, I'm using this basic title because we're not talking about language, only we're also talking about translation students. We're interested in even in language degrees like English, French, Italian and whatnot, and how we can all, you know, help graduates from these paths to find a job in the industry. So they are needed in research and industry jobs that will become clear by the end of this talk. However, what they sometimes lack are problem-solving skills, data analysis knowledge, like how to deal with data and how to actually curate data in order to fit into systems. Project management skills, which was quite a surprising thing, as you'll see, because we didn't anticipate this to be so central in business. And of course, and what we'll be focusing on most, ah, sorry, apologies, my computer is slow, digital skills. And what our main aiming this project is to sort of incorporate in higher education curricula, these sort of skills and competencies that will allow students to get jobs easier. I think from a student's perspective, this is also important in the sense that, you know, our research should be able to show you what actually is needed in the industry and what kind of skills you can develop in order to have better chances of following a career in the industry. So how are we going to do that in the project? Basically, we want to develop modular learning units that can be incorporated in different courses at higher education institutions, ours to begin with, and then obviously they would be shared with everyone else. We want to also introduce innovative pedagogies and we want to to really sort of flip the model from the traditional lecturing setting and promote active learning. So we're trying to engage, you know, students using online educational games and this sort of thing. Then we focus very specifically and you'll see why also from the analysis on past based learning. So we believe that education should also have some relevance to what you might actually face at work. And then we also want to promote the integration of existing infrastructures into teaching, like there are all these sort of like freeware and software out there that, you know, you could actually use for your learning experience and it's not being used as much, at least in the EU. So if my computer allows this, okay, so what are we expecting to get out of this? So basically our aim is multi-fold, like first of all we want to prepare students for what they're going to face in the job market and you'll see some quite surprising results I think from what follows here. Then we also want like one, like our one immediate target group is students, the most immediate target group. But we also want to use this project to sensitize academics with respect to the actual skills that employers are looking for because, you know, there is a case, there are cases, many cases in at university level when, you know, the lecturers and the tutors and everyone are just navigating the class within their disciplinary boundaries but then they don't really take into account what, you know, possibly your employer is going to look for afterwards. Then a very, very important, it's very close to my heart at least, is that we want to raise awareness among employers about the skills and attitudes of graduates of linguistics and language-related degrees because there seems that in the industry people don't really know what linguistics is about and this is something that we hope to fix and, you know, we're partnered up with a lot of companies to do that. We also then want to create engaging modular learning content that will obviously be open access and accessible to everyone and we want to promote active learning, task and research-based learning rather than the traditional, you know, I'm teaching you and you're just getting, you know, you're just getting the knowledge through a lecture. Okay, so how are we going to do that? We have organized our analysis and our research around four main intellectual outputs. First we conduct the needs analysis, we concluded the needs analysis last month and this is what we're going to be talking about today. Then we want to create guidelines on how to better teach students, better prepare them for employment. Then we want to consolidate and create learning content that will be then shared with our institutions and beyond and then we want to see how we can include educational games in order to facilitate active learning. So you may have missed, well it's actually not that you've missed it because you're going to get like a pickover of you today, but we had our first multiplier event in Bologna, but there are three more to come. There is a very high chance that this will happen also online or it will be posted online so, you know, feel free to look us up and follow us. And all this will culminate in a summer school that will take place in Serbia in July 2023 where we will be testing our materials and the whole project will conclude. Okay so basically what I'm going to go through is the different steps that we took in order to identify these particular skills that I need for students and also to give you a bit of an overview of what I guess is expected from a European perspective, at least I can speak about Europe even though we did have some participants from BUS as well. So we went through three basic steps before identifying the profiles that are most needed in the industry these days. I'm going to go quickly through them and then we'll sort of discuss the profiles that we came up with. The first step, and that's because basically we're going to be developing content of our own, was to survey existing educational curricula and see whether the skills that we're looking for, like that we believe that the industry looks for, is looking for can be found in these in existing programs within the European Union. Basically what we, when we applied for the project what we wanted to focus on was research skills, data acquisition skills and data curation skills, like how to deal with data data handling skills as well, and then we wanted to also see how much you know linguistic theory and research management in general features in existing degrees. In order to identify what is the current state of the art in education, we went through a number of European Bachelor and Master's degrees, we created the purpose of them, and we based this basically on the QS World University rankings in the areas of linguistics and other languages. Basically we came up with a list, we developed a list of 535 degrees, and out of this list, like which are practically all the degrees in languages and linguistics that you can find in Europe, and then we in order to analyze the curricula more to the point, we selected 122 degrees which were our present example, and then we also conducted the mini study focusing even more on 12 degrees in order to see what kind of career paths they are focusing on and whatnot. This is just for your information, I mean for what would interest you in this regard is the extent to which existing curricula cover what we believe that the industry needs, and it seems that the focus competencies I referred to before are only represented in just a quarter of all the degrees, which means that basically most degrees are within disciplinary boundaries and do not really look to develop particular technical skills, digital skills, transversal skills, things that would be useful from an industrial perspective. Then we also because our focus is more into technology and digital literacy and this sort of thing, we figured that we also identified that programming machine learning and linguistic theory or interaction of all these almost exclusively, but we'll say predominantly because there are some exceptions, can be found in master's levels courses. And then when we went through all the curricula that we gathered, we saw that we you know our experts in the team identified the three pillars of making a useful degree for graduates to be to keep the degree flexible, to keep it modular so that people have a choice which direction to follow, and to also keep it diverse in the coverage of areas. And you'll see why by looking at the titles of the degrees that we gathered for our corpus, we can see that you know this is a nice word cloud here that we created, and we can see that obviously linguistics and languages and languages are the most important ones or particular languages like English and whatnot, but you can also see that there is a sort of turn at university level to incorporate things like business and enterprise in this sort of thing, mediation, technology, you know you can find keywords even in the titles which means that you know there is already this sort of trend to go towards workplace, so to say when devising particular courses. Okay and then when it comes to future career prospects, we also identified we also found out that most of the degrees that we were looking for that we were looking at did not actually include any particular career path advice, and you know just one of the exceptions was that from the Royal Hollywood University of London where again even though you know there is a description of how you're going to find employment after studying linguistics, it's kept rather general rather than more specific, so as a modern linguist you'll have excellent communication, analytical and research skills combined with proven ability to communicate fluently alongside practical skills such as translation and interpretation, you will have developed the kind of sensitivity to different cultures that is highly prized in the workplace, however again it doesn't give you like a particular route or choice of routes that you would be able to follow after graduation, so this is something that we want to generally fix let's sort of say with our own project. Okay then the next step and this is I guess the only the last boring bit of what we did, we had to go back to the literature and figure out how you know what exactly is considered you know the best you know preparation in higher education for you to get a career and in order to do that we looked at language industry surveys, a whole bunch of them, these are some representative examples, we also looked at institution position papers and reports and we inevitably also looked at colleagues work, academic works and how they suggest that you know education can lead to a successful career, particularly specifically in relation to linguistics, so to take them one at a time in turn, I think it's a, okay so let's start up with key themes in the language industry, I do apologize there was supposed to be a transition here but you know the PDF doesn't work, so looking at language industry surveys the general trend seems to be and this is actually identifying you know from a quote here that for example in the domain of translation services and more generally when it comes to you know pure linguistic work that has to do with content creation and whatnot, prices for basic services are in wicked plummeting while those foreign delivery services will become more enumerative due to lower availability of adequately adequately skilled resources, this effectively means that even though you are starting to become a linguist or you are starting to become a translator and whatnot, chances are that you might not actually do exactly what you've started to do, chances are that you will be in a position where you will have to curate and sort of oversee the lower level work that might be done by machines and whatnot, so what seems to be important in the language industry service which are dedicated for companies in the business world is that the most important things are datafication and data management so there is a huge need and actually it has been noted time and again in these reports that you know salaries are going really high up when it comes to people who can manage data and analyze data but not, there is a huge need for all the more all the better machine translation software, digital marketing and content creation is also of the rise and then some more general sort of roles that linguists would be would be very suitable for our project management positions and positions that have to do with customer care, client relations and so on and so forth. Also linguists and language specialists are very much preferred when it comes to quality control processes so even when it comes to let's say you know you have a system that creates a translation automatically and then you have to sort of proof it in order to identify what it is and one another important thing that came up through our analysis has to do with the dimension of gender and basically it seems that even in the language industry that often noted gap between men and women remains I mean even though there are a lot more women working in this particular industry the salary gap remains quite considerable and it seems that men are preferred for in-house jobs so this is something that we also want to tackle and sort of sensible companies to avoid. Then when it comes to institutional themes again here what we have is you know verification of our original you know thought that basically the easier the task that has to do with language that the more likely it will be to be taken over by by machines by an intelligent system and whatnot and basically this leads us to the conclusion that when as we're moving on in the 21st century or whatnot the most important skills would be not just to translate or analyze or whatnot but to basically critically process information in conjunction with others and by using machines as well and obviously UNESCO also you know highlights entrepreneurship as a particularly important aspect for employment opportunities. Then turning to the European Commission's report a critical thinking problem solving creativity communication collaboration data literacy and basic understanding of AI are considered indispensable for the market so we can easily see like even from these states that you know digital skills become quite important quite early on and you know it seems that education needs to follow through and sort of prepare students by giving them the right means to understand AI not to do AI but basically to understand and be able you know to be cognizing of the rules and be able to work with that. Then when it comes to language education and more generally what we are interested in as academics the basic problem that is always identified and with which we agree as well is that there is a quite significant branding problem for linguistics and language degrees I mean usually when someone needs a linguist there are there is a good chance that if they're not you know familiar with linguistics or not they won't even know what linguistics is about so one of the things that we are aiming for at the project and one of the things that we think should you know the whole like educational system should aim for is to sensitize the industry and companies with regards to the particular skills that a linguist has and as you'll see later on from our focus interviews these skills are really highly you know required in the industry. Then another important aspect that's raised by the institutional reports is that when you're studying linguistics you're not necessarily and I'm pretty sure that this will have come up you know quite a few times in the discussions over the last few days which I of course recorded the verses but anyway so you're not you know you're studying linguistics you're expecting to work as a linguist but chances are you won't work specifically on the particular topic that you focused on to begin with right and then there is also a mention that of language services and especially technologically supported and you know AI based language services that are growing and this is a pattern that we also notice even in our survey and later as well and then finally when it comes to academic research in the area if my computer key academic things basically what is identified in the literature in the academic literature in the field is that there are currently and you know within the 21st century we see the emergence of new roles for language experts and these roles are not necessarily you know the ones that you have traditionally thought about when studying linguistics but they are things that you can consider as a possible career option and actually a career option that will boost your career quite easily quite early on because these are positions or you know expertise areas that that you know that nobody has at the moment like they're very few people so you know they're very high paid so you know becoming an advocate for multilingualism as a globalization tool and this has to do with all sorts of platforms even social media and whatnot then managing large-scale global initiatives that require transcreation I mean we do have even now in COVID times obviously you know you have all these multilingual resources and rules and guidelines and whatnot and linguists are needed for this sort of thing so these are opportunities that we can capitalize on as as linguists then bringing linguistic knowledge to interdisciplinary teams of developers and service providers so that they can design and adapt AI systems to the needs of new registers styles and languages the problem here the problem I think that the challenge here is that generally you have teams of dedicated marketing you know advertising companies and whatnot who are doing their thing but then as linguists we do have the sensitivity by having studied the functionality by having studied different registers and styles to sort of give them information about how they can target a group more specifically so this is another role that you know seems to be emerging as a byproduct of your linguistics training sort to say and then obviously and this was actually underlined by I think an 85 to 90 percent of all our employees linguists are needed not just to program and you know run the AI stuff but to evaluate AI technologies so basically for example if you have like a machine automatic machine translation system you know somebody needs to check that it works well and you know who better to check that then a professional translator can say right or someone who speaks the language and knows how to analyze it so that they can pinpoint what the problem is with the AI system and then basically you know and then another I now just you know quickly go over this another important aspect of the literature is that they do seem to you know to promote they want to advance the notion of research-based curricula of project-based work where students are engaged and they also develop a lot of important translation skills like collaboration skills data management skills you know and whatnot so that they can sort of so that education sort of mimics the you know the the environment that you're going to face in your workplace yeah so our third step and this is you know where we went deep into the actual world of business and whatnot and we wanted to check you know how the employment market views linguists you know combines three types of research that we carried out three types of studies first of all we analyzed job ads that were posted online then we went through we sent out surveys and uh due to companies and we targeted managers basically so as to get a bit of a more nuanced idea of how you know the view linguistics and what they need from a linguistics graduate and then finally before we we did run 12 focus interviews with representatives from these from these companies all of whom were you know general managers and above so let me start off quite quickly with the corpus-based analysis of job ads basically we collected a bunch of job ads I'll go quickly because I think I'm running out of time and I have to to focus on the profiles then we we looked at the skills and competencies that are mentioned as requirements in in particular job posts and we also looked to see what are the tasks that are usually associated with a position for the linguist our sources were from all over the place you know linguist lists career linguists linked in like general purpose employment platforms technological companies like Amazon, Apple, Google and whatnot and we did select given our focus on digital literacy we did select we did select all the jobs that involve language and linguistics related tasks that require some digital competence or research skills in order to to get the position so we didn't we didn't include in our search just content creation jobs or just translation jobs per se but you know translation jobs that require cut knowledge like cut to automatic computer assisted translation technology and we also excluded all the job ads where a degree in in one of the stem fields was a requirement rather than a degree in linguistics so we want to focus so we learn those companies that really look for linguists and and you know but thereafter basically so just to give you a bit yeah we gathered 200 almost 200 job ads from our hundred companies and and you can find you will find in the slides the actual link to the purpose if you want to play around with it generally when it comes to formal education requirements it seems that 40 percent of the jobs that we looked at approximately 40 percent of the jobs are looking for someone with at least a bachelor's degree in linguistics or language related area 35 percent actually you know are looking for a master's degree and only 10 percent are looking for PhD people combining the bachelor and the master's like you know 58.9 percent of all the job posts required either a bachelor's or a master which means that there is still a hierarchy absorption of students with just a bachelor's degree in the industry. Then when it comes to skills competencies and tasks the most important I would say the most transparent like skills and competencies that we identified in the job posts where data skills and research skills where you know potential employees will be requested to analyze data to collect data extract information and also to conduct research market research or whatnot because we're talking about the business world obviously and then support research and development of a particular product. Then technical skills are always underlined but this is also you know byproduct of our selection criteria of jobs knowledge of a programming language and it seems that more often than not this is Python these days the ability to build language models the ability to analyze test or improve performance of tools and this relates actually to the you know to the sort of consultant role rather than the programming role that the linguist can have that I mentioned before and then when it comes to disciplinary knowledge you get the usual you know areas of linguistics with the emphasis on computation and P and localization this sort of thing but you know you also get post sports semantics for discourse and whatnot and obviously you know when it comes to transversal skills communication and organizational skills are also quite important so you need to have good communication skills you need to be able to pay attention to detail good organization skills and this is actually really important and I'm going to return to this later on ability to thrive in a fast-paced environment and this is something that you probably know already but you haven't you know you you you don't necessarily you know realize how important it is when it comes to to to you know to find a job in a company so moving on on the basis of the corpus of job ads we we then distribute the survey of the you know survey to representatives from the business sector we contacted 70 businesses which range from language service providers to marketing and finance so we try to identify all sectors you know we sleep with our employee and you know you can see that there was a quite healthy distribution like almost one third of our companies were just small companies like of 10 employees startups and whatnot then another the other third was large companies you know you know size of google or or lion's breeds or you know the big conglomerates and whatnot and then the other third was small and medium ones and basically we we did for this for the purpose of this we communicated with employers from digital data intensive sectors who obviously do not necessarily identify language and linguistics graduates as their future employees but could potentially consider them as well so we we looked for companies that have an interest in language but not necessarily look for linguistics in that respect so is to get their opinion on on on employment of linguistics graduates now 80 percent of the people who communicate have dedicated positions that they explicitly assign or they require someone who also has a linguistics degree so to say and then what was really surprising was that 60 percent of the people we were communicating said that their company plans to add more dedicated positions specifically for graduates I won't say just linguistics but also language experts and there's a difference between a language expert and the native speaker of a language. Now the main does the main roles as you can see here that you know exist in these companies are language specialists obviously you know it's a linguist computation linguist and language engineer project manager coordinator but of linguistic data analytical or data linguist and research associate now the main tasks that these companies require their employees with a linguistics background to carry out is to be you know they they want them to work with data obviously language data they also want them to be familiar with technological tools and software and another important thing is that obviously communication like they need to be part of the team to be able to communicate with the team and to also be able to communicate with clients and vendors and this will relate a bit to perhaps a misconception like if you're if you're hired as a linguist you're not going to be working just as a linguist you will have multiple roles to fulfill within your your workplace and obviously you know another important aspect is is the maybe to contact research and to manage projects that lead to particular products. Then if it okay I will just skip this I think then when it comes to skills I mean what we what we did in the survey we we we asked our respondents to identify the level of importance that each of these skills has and then to also identify which of these areas need most improvement when it comes to linguistics graduates as opposed to what the computer scientists or or some other type of graduate and it seems here that problem solving skills is actually the most important one alongside communication skills but problem solving skills which include independence and quick learning and and versatility in taking decisions and whatnot is the one that needs to be improved the most in other cases we found another notable result here is that creativity for example was not being as important but it was being as something that needs to be improved a lot and we believe that this also has to do a bit with how linguistics graduates you know follow a course that is just lecture based and whatnot then moving on to the knowledge and experience it seems yeah the linguistics knowledge is obviously the most important one but it's also the one that doesn't need to be improved as much what seems to be what was actually standing out throughout this process and we hadn't even thought about before applying for the project is the project management is something that is considered essential and it doesn't necessarily have to do with language right it's it's it's a more general skill sort to say so in order to summarize a bit it seems that the knowledge and experience that companies look for the most are first of all you're a linguist so you need to be a specialist of language and that doesn't necessarily mean of a specific language but someone who can explain language or describe language in a very sussing way then it's very important you know another part of knowledge and experience is the ability to not only translate because we're not talking about translation interpreters but also to localize content so to bring it to the cultural standards of a particular community and then obviously there is a huge rise in computational linguistics positions as well right to be able to play around with tools to engage it in AI and whatnot then the skills that are most needed or you know what you're expected to have at least some knowledge of in order to be able to enter the field would be data analysis and language technology tools and this includes not just you've been able to programming but basically you've been able to use tools that are available and you know diversify them and sort of adapt them to their needs programming is also quite important managing terminology or managing you know big databases is also very important again project management was you know all over the place and your knowledge of linguistics is expected is something that's highly valued now here the uplier for us was project management because we were assuming that you know this is not the role that would be targeting linguists per se but the rationale of most of our responses was that project management these are shapes like their project managers should have a solid linguistics background because they are the ones who oversee the whole process so you know it's a role that's you know that is really important for the companies and something that the linguists can very easily get if they have the right qualifications if they have the right skills and other skills so on the basis of this survey we run a number of focus interviews with job market stakeholders we actually interviewed for an hour each 12 job market stakeholders who came from 11 different companies two came from the same one but it was a big multinational company and they participate in one one interviews the domains from which in which these interviewees work vary so we had representatives of the language service providers of the automotive industry language technology and even insurance services and the area of engagement was not just computational linguistics we also had people from translation localization companies or speech recognition and speech synthesis companies as well now what we focused on during these interviews were three main questions the first one has to do with the employability of the graduates now this was supposed to be a bit more interactive but if the PDF it doesn't look as such but anyway so it seems I will just take them you know I'll just take them in turn there is a healthy demand in the industry and actually if I may say so most of the interviewees suggested that there will be a rising demand for linguists and the important thing here is that even though there will be a rising demand for for linguists these linguists need to also have additional you know skills so apart from the specialized language related expertise you also need like a student of linguistics or a graduate of linguistics would also need to have some technical know-how we're not talking about high-level programming skills or you know anything extravagant but just a healthy knowledge of of how AI works or machine learning works or you know how programming works so that you can sort of ease into the position so the then the ability like as a linguist your basic trait would be that you are able to deal with a big use in a structured data so make sense of from a mess of language you know how this particular system works and whatnot and then another important thing that they also hinted at before is that people linguists who are who seek to enter the you know the industry for companies on language need to be willing to to take on hybrid roles so being hired as a linguist doesn't mean that you will work like your 40 hour week just doing a linguistics task or a language related task I mean they need versatility in the sense that you might have to communicate with clients you need you might have to like set up meetings with the team and decide on different things and whatnot so basically what they're looking for is someone who is technologically you know cognizant so they have some knowledge of technology and some digital skills and also someone with good organizational skills and can you know do like fulfill multiple roles in the company and then it seems that there is because that's another like aspect of most people who are working in the industry as linguists there seems to be an imbalance between freelance opportunities and in-house full-time contracts it seems that by being just a dedicated linguist who's just an expert on language and can only analyze the data and whatnot chances are that there will not be as many chances for you to get an in-house full-time employment as opposed to doing freelance work which is again you know there are many companies that employ freelancers and you will never start but again there's no job security per se in that so it seems that digital literacy and the ability to work with tools and whatnot is quite important actually for this sort of thing then when it comes to most out most short out skills and knowledge I'll just skip this slide and you can look at it later on and the third question which was really important for us and I think it would be important for you too because you can then check how your curriculum sort of meets the requirements of the of the workplace it seems that more than half of our interviewees stated that higher education offers lacks the goal oriented character of industrial work so basically yes you become linguists where experts in particular research field but then you're lacking often lacking technical and transferable skills like problem solving so it's not just a matter of getting a very high grade in your semantics class let's say where you're doing formal logic it's also being able to transfer this knowledge into more practical tasks the industry plays emphasis on on a potential employees versatility so don't be surprised if you don't know anything about programming but you get hired because you have proven that you can like coordinate the team and then to project management they do like x number of things and then company offers you some training in programming or whatnot there is a need to provide quantitative data analysis training traditional linguistics has been like theoretical linguistics and formal linguistics has not really been statistics but not it seems that there is an increasing need in the industry to engage with quantitative analysis rather than political analysis and obviously a very important aspect that the old interviewees underlined was that we need to include in our curricula courses that have to do with data handling not just how you analyze the data but also how you can get like I don't know twenty hundred thousand words worth of content that need to organize in a way that can be analyzed later and also how to manage a project so like work more with task based with task based problems that that you know people can solve in groups or whatnot so all in all all interviews believe that what seems to be lacking the most from existing curricula in linguistics is specialized training that will enable graduates to think outside the box and come up with their own solutions to typically to typical industry workflow problems and I think that this is a very very important take home message because effectively when you're studying you know you want to solve a problem and you know you're doing great at it but then when you go into into a company they will just tell you oh we have a problem above in this particular problem or we have a problem with this particular client who wants to x and y you need to to be able to think for a solution on your own like you won't find it in the books you'll find it in forums you'll find it in you know you need to be creative and I think that this is something that really needs to be included more in the curricula that you're currently studying in order for you to be able to be more employable now finishing off what we did and that this whole purpose of this project was of this needs analysis was to identify and again the transition is lost so you're going to see everything it's a bit messy now that anyway what we wanted to identify is a profile for the linguist of the 21st century basically what we call this person is the language data and project specialist this is not the title of a job this is basically how we envisage you know someone who would be very employable and very you know easy to get a job in the career what kind of competencies they would need to have and these competencies include not just the ability to analyze language but also the ability to handle data and the ability to run projects and oversee projects as a coordinator or whatnot now in order in terms of the knowledge skills and competencies we identified seven different areas of skills and competencies that are needed so apart from disciplinary which would be your linguistics you know your linguistics background the knowledge of a specific language you want to work on or translation interpreting or what not you also need to have data oriented knowledge skills and when we're talking about data here again these are general categories you don't need to have all of these in order to find the job I mean it's a mix and match situation so by data oriented skills we are talking about your ability to collect, manage, curate and analyze language data knowledge of statistics and familiarity with data standards which is actually quite important came up in the interviews as well like your knowledge of particular rules and legal frameworks that apply when it comes to to working with data more generally then we identified this really important in the cultural skills which were highlighted by many of the companies perhaps because some of them were also you know localization companies and translation companies where you need to have an awareness of specific cultural context and cultural differences and you need to accept the cultural agility which is actually really important because when working with language you know messages can just fly around very easy then transversal skills these apply these are not just specific to linguistics graduates creative and innovative thinking problem solving skills presentation skills writing for different audiences are highly important then technical skills obviously here we're talking about resources technologies NLP perhaps knowing a programming language or being familiar with how programming works is also really important research oriented skills this is what you actually have the most I would imagine being linguists and you know knowing how to create to design an research project being able to come up with hypotheses analytical thinking and all this stuff and then accessing and processing information critically and finally organizational skills which are more related to project management and entrepreneurship and this sort of thing that are really important these are all the skills that you know collectively would make you know a very successful career but then in order to identify particular roles that graduates of linguistics might be able to graduate linguists might be able to you know to fulfill and take on when joining the workforce we identified four different profiles for particular for particular job positions and these again are not mutually exclusive but we sort of think that these are gradually going from an entry level position for more higher level position so let me just start with the first one the first one we we call the language data and project specialist and this we we think is a more you know entry-level position so here we can see that what we're talking about is someone who can work with data so collect data transcribe audio files annotate linguistic data and explore language data and analyze them so these are yeah these are some skills then being able to engage in low-level analysis of the data such as translation interpreting localization post editing developing and analyzing and testing software technological tools and whatnot so this is the technical aspect of this position research oriented position research oriented skills would have to do with language data research the 21st century linguists would easily work as a language data and project specialist and for this they would need technical data oriented organizational and research oriented skills here you may be wondering where the disciplinary skills these are you know these are actually all over the place like unless you're linguist unless you have specialist knowledge you wouldn't be able to work with with data over this short then when moving on yeah here are the four sub profiles that I was talking about before and here we'll see what kind of skills you would need more in order to to to be able to sort of get this position in the industry when we're talking about the language data analyst we're talking about someone who would be dealing more with language data collection and notation and analysis this is usually thought of as an entry-level position and for this the most important thing I'm hoping I mean yeah it was supposed to be a whole transition so on my slides but anyway the most important skill here would be data oriented competencies ability to collect, manage, curate and analyze, use the data, statistics, familiarity with data standards and whatnot so this is the most important one that's the full line around it then you would need disciplinary skills obviously because you would be dealing with language data intercultural skills are quite important and transversal skills are important too and technical skills are quite important because you need to be able to work with tools in order to analyze you know annotate and collect this sort of data here research oriented skills are not as important because you would be engaging in an analyst's role so you wouldn't be thinking a lot about the research designer or the bigger picture you would just have the data you have to analyze and organizational skills seem to be even less important to us because effectively you'll be working as part of a team that does the analysis and then someone else you know sort of collects and consolidates all the data so this is an entry level position and we think that this entry level position with the right sort of you know help and development of more skills can lead to the position of a language data scientist and here we're talking again about linguistic data and analyzing linguistic data but here we're talking about having a birds eye view of the data that you're analyzing or processing so here what's most important is the research oriented competence like it took for you to be research oriented in the sense that you would be able to sort of consolidate the analyst's outputs and then critically processing information that you get from there obviously equally important here data data orientation and technical knowledge is you know is indispensable for this role because you have to not only get the output of the analyst but also synthesize it in a coherent way so you need to have these skills too and then obviously you know disciplinary intercultural transferral skills are equally important too again organizational skills are not as important for this particular role because you're not dealing specifically with how you know to do how to spread out the tasks across the team the fourth profile the third profile apologies is that of the language data manager and here is where organizational skills start going a bit higher up now here we're talking about a different like okay so the specialist is a higher level role in relation to the analyst the manager is someone who deals a lot more with organization rather than the research so you're not thinking about what's going to come out of this particular project that you're working with right about this particular thing that you're dealing with but you're basically thinking about how to organize everyone in order to come up with results so organizational skills are important not as important again the main thing here is data orientation like to have to be able to deal with data and to know how to distribute it and how to to curate it and analyze it technical knowledge against again really importance and this remains stable however here you're talking about a more organizational role as opposed to a more research oriented one and the final profile that we came up with is that of a language project manager and here we're talking about the person who does not really deal with the technical details or is not interested so much in what the outcome of the process is going to be so research goes back again but is the one who organizes everyone and needs to have very strong project management skills in order to be able to come up with a quality product and whatnot so organizational skills here are really important and I think that from the industry these are the most important sort of positions that you know these are the higher paid not important sorry apologies these are the higher paid positions because these involve a lot of responsibility and you're managing a lot of people so basically the salary goes up through this one again this requires and I'm pretty sure that from the mixes and all that most people who are working as project managers would have told you that requires you know you're taking baby steps in order to reach this level but here everything is pretty much important the only thing that sort of fades a bit is your you know your your your research curiosities or to say like you have to to make sure that the project goes through so this takes like it's a specialist who will try and make sense of how it works again all the skills are important but not to the same extent I think that with this I'm mistaken more than I think I can you know thank you all for your attention I would like to invite you all to follow us on Facebook and on Twitter we will be posting stuff as things come out and if you want to have a look at the stuff that I talked about today we have a bunch of reports in our website on our website again you'll find the the link on the on the slides when they're posted and the profiles are actually discussed in much more detail in our main report which is the cumulative report here thank you very much for your attention I do apologize for all the technical mishaps and I'm ready to take I don't know what's going on here probably it's summertime and everybody's going crazy great thank you so much that was super interesting I have to say this is the first time I've seen data collection that really bears out what we've been saying to people over the last several years I think the organizers of the LCL and other career linguists have been saying the same sorts of things that you are showing us is actually part of the data so saying things like you need to have a range of skills project management is super important you're not going to find jobs necessarily with linguists in the title it's so much broader than that it's amazing to see this actually shown up as you know research that you've done so this is amazing for me the most for me the most like mind numbing sort of thing was that you know I came into the mixtures I you know I heard people talk and whatnot and I heard experiences and then every time I sort of like maybe unbiased because I've been conducting this research not for a year but every time it was sort of like confirming what we had already found and I can really remember that particular part of the research where this was found and what for me was really surprising because you know don't forget I'm also a linguist I'm working as an academic so I don't have a lot to do with industry I'm just I just have an interest in tools and technology and this sort of thing is that you know it's really surprising to see that you have this idealized version when you're studying like you know which is the academic dreams are to say but then it seems that you don't need to be like a straight A student in order to be able to to to maximize your career opportunities like you need to be versatile you need to be like quick thinking quick on your feet and that's the most important thing yeah absolutely yeah the versatility is great I would like to encourage people to post their questions yeah in in the chat I want to ask you one thing though before we we jump to maybe Joti you know you mentioned early on that one of the goals the long-term goals is to sensitize industry yeah you have plans for that like do you have a strategy for doing that because we want to do that too here in the U.S. and we're trying to figure it out so any contributions that you guys have we would very much like so in sources so basically the way to do this I mean I'm I don't know maybe it's might be the training way of thinking but I think but there are enough people will get you anywhere so basically what we've done is when we applied for for this funding we did ask particular companies I think Google included even though they never signed up in the end but anyway they are sort of partners in the more general sense to act as associate partners and by associate partners basically they would give us internships and this sort of thing then how we are tackling this right now is that because we're creating this learning content I've asked most of them and most of them have agreed to give us like timing bits of their workflows like something that that you know that we can include in our curricula like instead of me coming up with a task for statistics you know why not get a task from Lionsbridge that they do every day and then I just change the numbers and the description and it becomes something that would introduce students to what they would face if they like you have a deadline for tomorrow and you need to to pass these numbers you know find the solution something like this so this to Mimi and I think that by including them and involving them I mean I don't know how it's going to pan out because you know we started like they just learned about this two months ago and we're having our first meetings until September I think that this way because my impression is that they don't really know what a linguist is right I mean they do understand that NLP is important they do understand the computer science and if you have some linguistics in it is really nice but I think that the other way around it's not as widely you know because this is an IT sector basically so I think by identifying these and including them in the process of creating the curriculum and all this stuff they they're starting to also realize at least in our cases our partners and starting to also realize that yes a linguist is really important during the interviews it was actually surprising that two of the partners did tell us that yeah we're getting a lot you know problems with our with our employees because they don't really know how to like they understand that there is a problem with something but they don't know how to call it and you know the moment they show it to you it's like oh yeah this is a morphology issue exactly yeah so and then you can see them like sparking oh my god so there is a term for this because I didn't even know what that was so I think that by engaging in discussion with them and inviting them in events I mean that's what we're doing basically and telling them listen give us a short description of something that your employees do like it does need to be like confidential or you know something that's that's weird like an everyday thing and then we'll try and include it in the curriculum so I think that it's you know I think that this is the way to go about it and then obviously I think that getting like in touch with with with industrial partners and and sort of asking them to offer an internship it's like showcasing that students can do what they have in mind like in Malta we have a dedicated undergraduate human language technology program so by by by getting partners from the industry to give placements to students we are actually you know we're actually making our presence felt to to the industry so our graduates get jobs easier that way that's great that's so good Joti did you have a question you can unmute yourself there yeah thanks Stapros this was just incredible I mean my mind is blown I just I think that nobody does this kind of self-reflexive work inside academia and certainly other disciplines are not as interested like I can't imagine showing this to my friends in sociology I don't know if people are interested in this sort of thing and I think it you know it's funny it made me think about how as linguists I think we often say oh you know my my family or the industry or no one knows what I do but then I'm realizing that I also don't know what what people do and this was kind of interesting to learn which skills are are valuable in which you know in which context and so I'm curious about the I'm well I'm curious and a bit intimidated by the the centrality of project management and and things like that um what were the three like I think yeah I mean yeah I just I'm I'm wondering you know like it seems like one of those things project management and related skills are our skills that a lot of people linguists and non-linguists would would have or can claim to have and and how do you showcase that in a way that actually makes you stand out so basically what what transpired from our survey because we did have a question that I mean we have like a particular question and what not one question was would you prefer to have someone who has like pure linguistics like you know expertise in the domain theoretical or the language like a native speaker of a language who's considered the language expert just because they were born and they speak I don't know Portuguese or whatnot right and it seemed like most of the companies opted most of the companies I can speak for everyone but but the general pattern seems to be that most of the companies often opted for the cheaper solution which would be someone who does have a degree but is a native speaker and then they run into troubles late into trouble later on because they couldn't again describe what it is that they were doing like they would do the task well but then they needed like specialist knowledge in order to be able to to talk to that now the other thing when it comes to project management I think that the misconception is that we cannot possibly like even as educators I cannot like create a project manager out of you what I can do is I can create a curriculum like you know many universities do that say okay team up you're going to be the leader and sort of you know bring me this assignment which involves like four parts within a month or something like this and this sort of gives you an aptitude for this I think that the project manager even in the actual like this I don't know how the US works but at least in the U usually you need to have experience in order to be able to tackle big projects so basically you start off with an analyst role which is sort of like an entry-level position or an annotator or whatnot and then the more involved you get with the team and what not it will give you more responsibilities which eventually will mean that they might tell you okay now we have this standalone thing and a team of three minus them and see what happens I think that it's not something like you should be like intimidated from the get go but for me it's not even like a like an educational thing it's more of a life sort of you know attitude thing right I mean be ready to collaborate be ready to be open to ideas like I know and I know because it was like that 20 years ago you know the moment someone talked about statistics I would be like oh no but you know now that I'm open to it now that I have some familiarity I'm not a statistician or an I'll never be a statistician because I'm a theoretical linguist but then the extent to which you can understand how something works you don't need to make it work if you understand how programming or machine learning works just not like the basics then you already have the first step like they will see that you're not good at machine learning but as long as you can like coordinate a team of people who are really experts in this they don't really care that's that's about the versatility we're talking about so yeah I think it's more about transversal skills and it's more about you know having people come out of their shell and being able to try and test out and being able to say even no right I mean you know you're not expected to know everything like have a healthy attitude towards the business and then the business will and I can I can tell even from the discussions in the mixers and the office hours and whatnot most employers do not expect you to be a python expert they do not expect you to be a project manager they do not expect anything of you other than having you know showing that you're capable and that you want to learn and that you want to contribute I think that's my get like that that's my point I wanted to mention you know we as the the linguistics beyond academia actually did a survey of career linguists Alex if you want to talk about that for a minute and it's a beginning to start that but I mean outside of what upskills is doing and what we're doing there is not a lot of data on this I know yeah yeah it's it's really it's really you know it's really possible to find stuff yeah Alex do you want to talk about that for a second sure really briefly because we're nearing the end of our time together but I I love how the work that we've done as the linguistics career launch organizing committee and as the linguistics beyond academia group really compliments Stavros's achievement Stavros was serving corporations across Europe and departments language and linguistics programs across Europe what we've done has been to survey the career linguists primarily in the US North American space and find out from them where they are what they're doing what their titles are what their career paths are what their degrees were and sort of chart those career paths through their can we share notes somehow absolutely and I want to refer everybody here to that first session we did on the on day one Emily Payson I present the results of that survey in career opportunities for linguists and we absolutely those slides are up we'll share them with you Stavros yeah yeah slides up later thank you absolutely thanks so much I think Paulina has a question sure Paulina yeah hi thank you first of all thank for all of this work it's very insightful it's very inspirational it's something that I kind of would like to get younger and hope for this kind of program to come up to live and study it but I think about that I wonder if the the project would involve a certain research on or if it's not involved what it would be your opinion about who will be in charge of teaching this kind of program because nowadays we don't like like for example here that we have already PhD students, master's students, even bachelor students that we don't have those skills so we cannot just apply to get a like professional position to do that so what do you think about that? So basically one of the one of the main sort of aims of the EU these days it seems I mean like we're the highest sort of like ranked program I think when we applied and whatnot and it's because we're tackling employability like it's looking at other projects that can thought think it seems that what what seems to be like the visit the rat on these days is a modular approach which means that we can create all these like basically because it's an EU program we will have to develop our materials and then share them with the world so everybody would be able to to take them on and and adopt them and use them for their own courses. Now modularity means in this in this sense that you know I don't necessarily think that you know every program can have project management, entrepreneurship, machine learning, programming I mean otherwise you won't be doing linguistics right but I think that it's important to to have you know to to be able to blend in stuff so for example if you're a linguist you should have an option at least to do some machine learning or some programming or some localization course or something you know something that would give you some skills depending on your own needs so we are resizing all this as more of electives I would imagine in a program of study when it comes to who would be able to give them I think that generally I think that the system at least I don't know I'm pretty sure in the US even more so than in Europe you know there is versatility like we can get I'm pretty sure that I don't have like machine learning experience but I can easily ask someone from artificial intelligence to come over and give like three lectures so what we're envisaging for these courses are you know bite-sized project-based teaching that will give you an appreciation of the field rather than you becoming an expert in python or whatnot right you've been able to sort of recognize how it works like you know figure out how it works and then if you want there are a lot of self-study things out there and MOOCs and whatnot that you can get the knowledge from but I think that what we need to find in the first instance is the fear of statistics the fear of programming the fear of all that because we're dealing normally we'll deal with art students and humanities who you know who select these like degrees because they are sort of us afraid of hard science and whatnot and I you know I think that you know this is we need to tread lightly I don't I don't expect you know a program to just become computation I wouldn't want it even like for my own sake like but when it comes to teaching them I think that like the way we are developing this is going to be blended learning and we should eventually I don't know whether we will but eventually we should be able to sort of compare notes and even contribute to each other's programs like if someone from Belgrade asks me to give like three sessions I would normally do it even if they were the part of a project so I don't see why that wouldn't be a problem that would be a problem yeah so I'm sorry to cut off this great chat um I have one more extremely quick question and then I'm going to close this up Stavros the thing that you mentioned in Serbia that's happened yeah is that going to be in English or multiple languages it's actually going to be okay so it's it's going to be in English basically uh I'm not sure how we are how we're gonna get like we have funding for this sort of thing so students from all of our universities will be able to attend it I'm not sure how it's gonna go but but if you follow us on these links here uh and uh we will get more information let me just stop sharing as well um uh yeah this this will happen in July 2023 and it should be open I mean hopefully COVID you know okay great just and the other just another just the final like this is also supposed to be blended learning which means that it will be an online version too so I'm hoping that we'll be able to set up like even a virtual school right after the summer that's great okay excellent thank you so much this has been terrific