The Impact of Digitalisation and AI on Employment Quality – Challenges and Opportunities

Experts at ILO session discuss digitalisation’s impact on global employment and policy responses

During a session focused on the impact of digitalisation on employment, experts from the International Labour Organisation (ILO) engaged in a comprehensive dialogue about the transformative effects of digital technologies, including artificial intelligence (AI), on the labour market. Ms. Janine Berg, a senior economist at the ILO, presented research on the potential for job automation and augmentation due to AI, using a task-based approach to assess the vulnerability of various occupations. She revealed that 2.3% of global jobs, equating to 75 million, are at risk of automation, with a disproportionate effect expected in higher-income countries, especially within clerical roles.

Ms. Berg emphasised the importance of proactive policies to ensure that digitalisation benefits workers and businesses. She discussed the multifaceted impact of digitalisation on working conditions, including earnings, productivity, working time, employment security, skills, and health and safety at work. The outcomes of these changes can be either positive or negative, depending on how technology is integrated into the workplace and the existing institutional frameworks, such as social dialogue and collective bargaining.

Mr. Sher Verick, an advisor to the Deputy Director-General of the ILO, expanded on the policy implications of digitalisation. He emphasised the need for a comprehensive policy response that addresses both the opportunities and challenges presented by digitalisation to promote decent work. Verick underscored the necessity to apply existing governance frameworks to new challenges, adapt where necessary, and consider the development of new frameworks to ensure the protection of workers’ rights in the evolving digital landscape.

Audience members contributed to the discussion by highlighting the digital divide and the need for governments to incorporate digital measures into national employment policies. They pointed out that progress is possible even with low digital penetration, citing examples from Brazil and Colombia where governments have successfully implemented digital services.

Questions were raised about the collaboration between the education (C4) and employment (C7) action lines, with a call for a stronger connection between the output of educational institutions and the demands of the labour market. The need for ethical guidelines in the development of digital technologies was also discussed, with suggestions that such guidelines should promote fairness, transparency, and accountability, and address biases inherent in AI systems.

The session concluded with a commitment to better connect the education and employment action lines to address the supply and demand of labour effectively. The speakers agreed on the importance of a human-centred approach to the future of work, which includes the integration of digital transformation, the need for skilling and lifelong learning, and the creation of an enabling environment for digital entrepreneurship and formalisation of employment.

Overall, the session provided a nuanced understanding of the impact of digitalisation on employment and the critical role of policy in shaping the future of work. It highlighted the need for collaboration across sectors, the importance of ethical considerations in technology development, and the potential of digital tools to improve services and promote inclusion, particularly for underserved populations.

Ms. Maria Prieto:
Okay All right, great, thanks welcome to this session and We are a little bit late, but it’s fine we can extend the session if if you have the time to to stay with us and So anyways, it’s my great pleasure to be up here with my colleagues from ILO colleagues And we would like to center this discussion on the impact of digitalization on employment and What policy responses? We have seen and also while We’ll we’re going to do this with a couple of presentations. But if you have questions, please Raise your hand and and we’ll be happy to clarify and answer questions at the end of the the presentations and discussions we can take any questions that you have in addition and If you have also information to share, I know ITU is here with us And other colleagues also from the ILO very happy to to accommodate you so These are my two colleagues Janine and Cher. Janine is a senior economist in the ILO very well published researcher in many topics on employment, but and lately a lot on digitalization and issues related to to that She’s not only a researcher or obviously she is an ILO official and as such Provides also capacity building and policy advice to our three constituents governments employers and workers and Cher Verik that is now now the assistant no the advisor to the Deputy Director General of the ILO. He has worked also Previously and currently on Research he was heading the strategies unit in the employment department and has a lot of experience both from ILO and UN in general and also from academia, so let’s start this conversation with our specialists about job quality or how digitalization has affected Digitalization including AI if possible and how this has affected the quality of employment, please

Ms. Janine Berg:
Thank you Maria and thank you for the opportunity to be with you today. It’s really a great opportunity So yeah, I wanted to talk a little bit about how Digitalization can affect labor markets and employment in general Most of the discussion that you see in the media is always about, you know a jobs apocalypse and jobs disappearing and we’re gonna all be replaced by robots or now by by generative AI and We at the ILO we’ve done some work on that and I’m going to talk about that in a second But we try to put the emphasis really on how digitalization Transforms jobs so every day I mean what we do today in our jobs is so different from what the way we do our jobs today is so different from What we did 10 years ago or 20 years ago and all of this has impacts on on our working conditions and I think it’s really important to understand that and also To to have policies that are proactive to ensure that these transformations are positive for workers They’re positive for businesses in terms of productivity and positive, you know in general for for societies so first, let me talk a little bit about the impacts of potential impacts of in this case generative AI on Employment and this and then I’ll go to my second part So this is these two graphs which I’m going to explain in a second are based on a study that I did with two colleagues Pavel Gimreck and David Bosconde and we tried to do an analysis of what were the could be the potential exposure of Occupations to generative AI technology So like many of the studies done in the economics profession We take a task based approach and look at occupations and the tasks within them To see what tasks does a person do that could be replaced by in this case generative AI technology? So we did an analysis using what’s called the International Standard on classification of occupations Which is developed by the ILO the ILO is the Secretariat for the International Conference on Labor Statisticians There’s 436 occupations at the four-digit level in the ISCO in the latest ISCO and so we looked at all the tasks that a human had described in the ISCO and then Assessed actually and we actually used generative AI in our assessment assessed We did a scoring from 0 to 1 of what a potential item What would be the potential exposure to automation of these tasks and then we took that and we looked at Basically, we had a an analysis on you know To what extent in a job be if a lot of if most of the tasks that you do are exposed to the technology Then you’re then the chances that you’re going to be automated are really high Whereas if just some of the things that you do can be Are exposed to the technology then you would be augmented So there were some some of your tasks which would be replaced by the technology But you would still carry on other things And so if you think of somebody like myself, we use this technology to do our research. It helped us do our research We were more efficient, but you know, I still do other things and I haven’t been replaced yet So that that’s the idea and then we at the ILO we have the ILO’s micro data repository And we have a labor force survey data for over 140 countries. We were able to derive Global estimates and then estimates also by country income group. So let’s start with just automation What so our kind of big headline finding is that two point three percent of jobs? In the world are potentially exposed to automation so that it doesn’t sound like very much But it is actually 75 million jobs, but big caveat this doesn’t mean that they’re gonna disappear This just means that they’re exposed to the automation that they could be automated But then if you look at it by level of economic development Differences are quite acute and that’s because in countries that are lower income They have fewer jobs that would actually use this technology as more people are employed in in Agriculture or in transport or food vending or those occupations that wouldn’t be using this sort of technology in higher income countries Economies are more diversified

Ms. Maria Prieto:
So you have more people who would be in the jobs that that had the higher potential for automation and what we found in general It’s that it’s the clerical support workers where you have the greatest risk of automation So if you think of call center workers, for example, or even other so other sort of kind of assistant type occupations but then the panel above is on augmentation, so these are jobs that have the potential to be Augmented which could be positive. Ideally. It would be positive and become more productive and there you see that really across countries There there could be benefits low-income countries 10.4 percent of employment high income countries 13.4 percent of employment so this This has a lot of policy implications It has implications in terms of you know Our country countries actually have access to the technology to then benefit and we know of course that in lower and lower middle-income countries There’s a lot of bottlenecks in terms of infrastructure both electricity a broadband, but of course digital skills as well So that means a lot of the gains Probably won’t be realized and in fact in a subsequent study that my colleagues have done using data from Latin America where they use Survey data PX survey data of people who use their computer at work They actually found that in Latin America with in terms of the automation jobs There’s a very high incidence of using computer at work, which means it could happen whereas in With respect to augmentation the the usage of computer at work is much less But what I wanted to really the reason why I wanted to put this up wasn’t was partly for these results But it’s really about this this idea that okay So they’re actually there are a lot of jobs that could be potentially transformed and we want that to be a positive transformation And so this leads to kind of my second issue Which is about how does it affect working conditions what are going to be the outcomes? And so the idea here is that you do, you know We don’t want this technology to just come down from heavens and affect workers We want to have a we want to have a system in place Where the the design of technology at the workplace can be done with employers and workers in a sense that that really is Beneficial in terms of productivity and in terms of working conditions. So just very quickly because I don’t want to take up too much time I just wanted to go over some of these dimensions of different types of working conditions and how you can see that Depending on how the technology is instituted and what are the different Institutions in place at the workplace, but also in in the labor markets or in the society You’re gonna have different outcomes. So if we think of earnings you could think of how technology might actually standardize or routinize a lot of the work that people do and so make it in that sense the the skills that somebody brings to to the job then might not be as As rewarded in fact, there was a it was a good nice study that came out looking at how call center workers could use This technology and one of the findings was like well The the entry-level call center workers were much more efficient because they were able to use generative AI technology on the one hand That’s a really good thing on the other hand It could mean that the more experienced workers who actually were earning higher wages would no longer be needed So you can have these these different outcomes depending on how it’s integrated On the other hand We also know that because of the technology there’s going to be a greater demand for certain skills and that could drive up some of the Skills some of the earnings of those workers whose whose whose jobs are in demand The other issue is about well the productivity benefits. We do think there are going to be some important productivity benefits But how are those benefits shared? Is that something that is just going to go to to to to the employers or is that something that can also be shared? With the workers and this is very much the the the outcome of the institutions in place

Ms. Janine Berg:
You know, is there collective bargaining to to address how how profits are shared within a company? Or is there a minimum wage in place? all of these factors are going to depend what the outcomes are going to be and of course that has important implications for for inequality if we turn to working time Thinking just more broadly about digital technologies on the one hand Digitalization has enabled people to to work from home, which is wonderful in terms of flexibility and and work-life balance but it can also mean that you turn into an always-on culture and a worker is expected then to you know to always be at At the beck and call of their employer. So these are two very different outcomes And it depends again on on the institutional setup, which is why social dialogue at the workplace is really so important With respect to employment security digitalization allowed companies to To continue working during the crisis during the COVID-19 pandemic It’s hard to imagine what would have happened had the pandemic hit let’s say 10-15 years ago What what the consequences of that would have been for labor markets and for and for the macro economy luckily? We were ready The world was already at a digitization level that allowed a lot of businesses to continue and to adapt In some ways in ways that were very positive. That is something that certainly was beneficial in terms of employment security. The flip side of that could be that technology can fragment tasks from fragment jobs into tasks and lead to this kind of more of a gig work type employment. So again, another outcome that could go either ways. With respect to skills technologies, digital technology could take on the more routine work, allowing time for workers to do the more interesting work, the more creative work. That’s one of the phrases that people hear a lot, and it certainly can be true, but it could also render obsolete people’s skills and they’re out of a job. So those are two ways to think about it. Another important part of skills is also how it could enhance the potential for training because of digital means. And this is something that they know that’s quite important. With respect to safety and health at work, digitalization does have a lot of promise in terms of taking on some of the dangerous, dirty, and health-limiting work so it can create safer and healthier work environments. However, there’s also potential for more grave injuries if the machinery isn’t working well. It can also lead to greater work intensification if one isn’t careful. On the other hand, it also can monitor working conditions that could negatively affect workers’ health. So this is a positive thing. And then finally, with respect to the social environment, it can be more positive in the sense that it can get rid of some of the drudgery, but it could also be more negative if you’re just interacting with a system and you’re not interacting anymore with your colleagues or with your manager. So the workplace, the more human it can be, usually the more favorable it is for workers. So there’s no one way here. It can be positive, it can be negative, and it really does depend on the institutions in place and this ability to have social dialogue at the workplace. And that could be through unionization, but it can also be just through a more engaged working environment where you actually do have workers participate in the design of the technology and the feedback of how it is integrated into our work life. So my final statement is just really the importance of if we want to ensure that this digital transformation is positive for the world of work, the need to really give attention to this issue. Thank you very much. Thank you, Janine.

Ms. Maria Prieto:
So thanks for giving us that outline of challenges and opportunities as an outcome of impact on technology, of technology. Now Cher will share with us some reflections and on what policy makers, and that is for the ILO normally, that is our tripartite constituents, our government employees and workers, but policy makers and other stakeholders, we can say, how to respond to these implications that Janine presented to us. Cher, please.

Mr. Sher Verick:
Great. Well, thank you very much. It’s a real pleasure to be with you here today. I think Janine updated you in terms of the latest insights from ILO’s research and thinking on these issues in terms of how digitalization, including AI, is impacting the world of work. You heard about how that augmentation potential is likely to be greater than the automation one in terms of AI. And also, of course, the importance of looking at working conditions more generally. I think this is a very important issue because more broadly, the debate is about job losses, this argument inside of a scenario that all jobs will be lost. This is giving some insights on that, but it’s absolutely critical from an ILO perspective and a decent work perspective to look at those different dimensions. And before coming to some of the different policy areas, I just wanted to stress three other dimensions in terms of the broader implications of digitalization for the world of work. I mean, firstly, and this is also other colleagues at the ILO who do a lot of work on this, is the workers who are mostly in the global south and who are involved in the training of AI systems. So all that work that goes on into developing AI systems, which creates opportunities, but also challenges in terms of working conditions. A second dimension I wanted to flag is, of course, the broader issue of digital divide. And this is something, of course, very much discussed in the ITU and in your forums, including this one. And as ITU data shows, around two-thirds of the world’s population is online. We have growing numbers of internet users, etc. But of course, there’s an important question to ask, what are the implications when it comes to the use of AI? And Janine referred to that new work being done for Latin America and the Caribbean, which looks at the importance of having access to computers, obviously, to benefit from any augmentation potential. But when looking at the digital divide, it’s also critical to look at implications within countries. You know, we talk often about the skills part, and I’ll come to an example of that, which is, of course, linked to incomes and wages, skills premiums, etc. But gender, we saw also that augmentation versus automation results, that women were more exposed to that automation part due to the type of professions they were in, in particular clerical work. And other different dimensions they need to look at when looking at inequality within countries. And so a big debate, of course, as many of you would be aware at the moment is, you know, does the adoption of AI lead to shrinking of inequality, particularly if you look at it from a skills perspective, if that type of technology is going to substitute for high income, then it could reduce inequalities, otherwise not. And I think there was one interesting experiment done by the Boston Consulting Group, which showed that the benefits of adopting ChatGPT were greater for the lower skilled workers and the higher skilled workers, so they were able to catch up a bit. So within a company, you saw some catch up for the, you know, the lower skilled workers. I mean, this is one very specific context, I wouldn’t want to extrapolate that more broadly. But I think this is a very crucial area to look at in terms of implications for inequality. A third one that I want to flag before coming to some of these policy issues is not only the impact of digitalization AI, but how we harness it to improve the services that we deliver in the world of work, right. So one key area in that regard is employment services. So that includes all the job search assistance matching that is done through employment services, often public, but over the recent years, you know, a huge part of that is also done private through private employment services. That’s one key area where you’ve seen impact of digitalization and AI for some years, and ILO also works in that area. Another one is labor inspection. A very interesting use can be seen of AI in terms of improving the targeting of labor inspection. And there’s something that’s been shown in a EU funded ILO project in Albania, where actually, you know, the use of data mining and machine learning led to a 30% increase in effectiveness of their targeting of the inspection services. There’s also another aspect is on formalization, the use of digitalization to promote formalization. This is something the ILO calls e-formalization, and my colleague Juan Chacotana is here. He’s the leading expert on that and hopefully has a chance to also contribute to this discussion. So just wanted to add some of those aspects to give you an even broader picture in terms of implications of digitalization for the world of work. It’s not just impact, but also how we can use those tools within the services. So I know we don’t have a lot of time, but when you think about all of these issues, there are complex issues ranging from what we heard from Janine in terms of augmentation versus automation, but also there’s working conditions. I’ve added a few others and, you know, the list could go on. But this tells us how complex the implications are for the world of work, which also means the policy response is not confined rather to one specific area alone in order to address both the opportunities and the challenges and to promote decent work. And, you know, from an ILO perspective, it’s very important to look at a comprehensive approach to do that, and we package this often within what we call employment policies that link different parts of the labor market, from the demand and supply side, the impact of technology, to providing a package. But obviously here, in the context of digitalization more broadly, but AI more specifically, there’s a lot of discussion, including yesterday at the AI Governance Day about implications for governance framework. So I think just three quick points on some of these policy issues, as highlighted in our governing body meeting in March, the high-level segment on AI, but also in the UN system white paper on AI governance, we need to look at applying our existing governance frameworks to address the challenges that arise out of the adoption of digitalization and AI more specifically. So for the ILO, that’s about international labor standards, especially those that relate to the fundamental principles and rights at work. But also looking more specifically at issues around discrimination, the importance of consultation and collective bargaining, as Janine had also already referred to. Of course, at the same time as everyone recognizes, we need to look at how frameworks can be adapted and new ones have evolved to address the issues that are arising out of this transformation that we’re witnessing in the world of work. And just for information, the ILO has a standard setting process, as we call it, to look at how to respond in terms of decent work in the platform economy, which is, of course, a key part, but it’s not everything that’s going on in this space, but one of those key areas. So just let me then finish in terms of the policy issues around skilling, and that’s typically a key pillar within the employment policy space that we look at. But not only, I mean, there are others, but just let me flag this, because I think, you know, from a digital divide perspective, we really, you know, need to look at carefully at the use of, you know, of skilling policies, lifelong learning, as the ILO phrases, that lifelong learning and skilling strategies for equipping individuals with the skills that they need to participate in the digital economy. And here there are many issues linked to that in terms of public-private partnerships, the engagement of sector skills councils and financial incentives. But we also need, in terms of the digital divide, we also need to look at the small businesses, the resources they have and the skills they have to adopt AI to enhance their productivity and performance, while ensuring that decent work is also promoted. And one could continue in a list of different policy issues, but let me stop there, since we don’t have a lot of time, just to flag some of those and look forward to having a discussion with you on this further. Thank you. Thank you, Cher. And indeed, all these issues are extremely

Ms. Maria Prieto:
interesting. And one thing that I was thinking while you were talking, in fact, I was like, there is also opportunities in technology to improve some of the practices in institutions. And this is something that we should add to the list of the plus side of the opportunities. But I wanted to open the floor for any questions and remarks you want to make. And also to mention quickly, before I hand it over to you, that the ILO is the facilitator of Action Line 7 on e-employment. So this work will be reflected in that part of WSIS. So I see, Juan, you’re like, do you want to add something to the e-formal

Audience 1:
Okay, you have mentioned me twice. Yes, okay. So I would like to highlight the point by Cher on the possibility of enhancing services, especially in the employment angle. We have observed like a couple of things here, which seems to be like, I can call it like fear of doing things, right? Okay, so let me explain. So the first thing is the effects of digital technology, the impact of digital technology does not only affect the private sector, but also the public sector. So we know less about that. So, and governments, as Cher has been explaining, have made some progress on specific services as public employment services, connection with private, including inspection, etc. And yet, when we observe the national employment policies as such, we observe like 15 to 20% of them have measures or provisions on digital. So that means that we are doing things, but we are not backing it into a policy. And that is something that we have tried to understand. People usually say, hey, but we have a lot of problems with the digital divide. And okay, yes, that is true. But then we observed also that some governments that now have a very well-developed system started when they had 6% or 7% of digital penetrations. So it’s not that I need to wait to have 100% of digital penetration to do things in the government. So those are two elements that I think I needed to add.

Ms. Maria Prieto:
Thank you, Juan. Can you give an example of who would have very high penetration and very low? I know we were talking about the example of Brazil, how it went from very low to high, so that people can relate to that in terms of country.

Audience 1:
For example, Brazil, they have a very well-known system of cold, mono-tributo, mono-only tax. So they started manually, like in the 2000s. But in time, that has evolved into being a digital service, and now it’s very well-developed. Colombia as well, they started with electronic registration of social security, and then they have expanded to other services as well. So it’s not that I have to wait to do all the services at once. So you have to start with something.

Ms. Maria Prieto:
Great point. Very well taken, I think. So I have one question here. Madam, please say your name and where you’re from.

Audience 2:
My name is Manal Fadli from Ministry of Education in Qatar. My question is, as you mentioned here in C4, actually C4 is employment, how you can integrate it or collaborate with C4, which is education? And is there anything related to labor market? The output of education is going to the labor market, right? Is there any collaboration between C4 and C7? Thank you.

Ms. Maria Prieto:
I can’t say. OK. I think, well, under WSIS, yes, we’ve had some collaboration with ITU on this. And maybe I can ask Jenny, who is here, to address that question. Thanks. Thank you. Thank you so much, Maria.

Jenny Arana :
Thank you for your question. And I wanted to just start by sharing a little bit of the work that we’ve done together between ITU and ILO on a joint program with the support of the African Union that’s called Boosting Decent Jobs for Use in Africa’s Digital Economy and also Enhancing Skills. Thank you to the speakers. They’ve already shared some input on the benefits and the challenges of the impact of digitalization on employment quality. Through our program, which is basically targeting a number of countries in Africa, Cote d’Ivoire, Kenya, Nigeria, Rwanda, Senegal, and South Africa, and quickly expanding to a few others, such as Ethiopia, Egypt, and Uganda, we’ve identified several challenges, such as high unemployment rates, working poverty, informal employment in Africa is very high. There’s digital skills shortages and lack of access to relevant training opportunities. But we see a lot of opportunities in empowering use with digital skills to participate in the digital economy and creating really an enabling environment for digital entrepreneurship. For us, that’s also a very, very important part. Not only is the skilling side, but a support on entrepreneurship and innovation. And now the program works on different interventions on the labor demand by promoting policies for job creation and entrepreneurship, facilitating the transition of use into formal employment. On the labor supply side, by supporting governments to enhance the supply of digital skills through improved curricula and training settings. Then we also have labor intermediation, which is focusing on preparing public and private employment services to adapt to new technologies. Now we recommend really for stakeholders, the support to employers for digital transformation on the demand side, to provide financial incentives and technical support for digital adoption, implementing upskilling and reskilling programs for employees, the support for skills to job matching some suggestions are on the development or digital platforms to connect skill use with job opportunities, but also very important on the promotion and regulation. There is a need to create regulatory frameworks to protect economy workers, for example, and promoting digital inclusion policies to ensure that there is a widespread access to digital tools and the internet, for example. Now, some of the examples of the work we’ve done on the digital skills supply and demand, is working on training and capacity building. The program really emphasizes the training on digital skills to meet the demands of the digital economy, providing access to digital tools and fostering entrepreneurship. And we think that governments should really focus on a few key areas, such as, as I’ve mentioned, strengthening digital education, but promoting inclusive access is very important. We think that ensuring affordable and reliable internet access, particularly in rural areas to bridge the digital divide and to enable use from all the regions to participate is key, fostering digital entrepreneurship through grants, access to finance, incubation programs, also implementing labor intermediation services and supporting transition. The transition of use from informal to formal employment is very key. And last but not least, encouraging public-private partnerships. We believe that fostering these collaborations between several actors, such as government, private sector, international organizations, really is important to develop and implement the digital skills trainings, job creation programs. And I think I also, I think it was you, Maria, you were mentioning something about what can be done, what, if I understood correctly, technology creators can be done, what measures can be taken to kind of tackle the negative impact of digitalization and also of AI. And one thing that I consider very important is that perhaps we need to start thinking of a need to incorporate ethical guidelines into the design and the development of digital technologies that can prioritize fairness and transparency and accountability, thinking also of the biases that we can find in some of these technologies.

Ms. Maria Prieto:
Thank you. Thanks. I think that’s quite interesting, particularly, well, the ethical angle of it. And obviously the ILO, since a few years, we are advocating for a human-centered approach to the future of work, but that includes digital transformation, of course. Would you have any questions from the, any other questions from the, you want to? No, maybe some reflections on the questions. Yeah.

Ms. Janine Berg:
In addition to the ethical guidelines, there’s some people talking about also the need for computer scientists to be, to integrate ethics courses for computer scientists, which I think actually is a very important thing to do. But what I wanted to talk about a little bit, and this is kind of just my own reflection, a little bit about this intersection between how education is changing and how jobs are changing. What we see with our analysis is that in many, what with generative AI in particular is it’s a very good assistant. And when you think of career paths, I think myself, you start off kind of as a research assistant and then you kind of move up. And if, or if you think of like in the legal profession, legal secretary is a job that’s disappearing, but even some of the junior legal work that people used to do, such as you get out of law school and your first job is to do due diligence. Well, now the AI software can do due diligence quite well. So it means then that you have to kind of rethink about kind of career paths for certain occupations. And a lot of that will mean that you will need to be integrating AI training or the use of AI into education, into university programs. So then a law firm will be more interested in hiring a young lawyer who’s coming out of law school, but who knows how to use these digital skills, has these digital, knows how to use the digital tools really well and has an understanding of the technology and what it can do and what it can’t do, because a lot of things are, what the limitations are, that the more senior lawyers won’t know. But yet, of course, you still need the senior lawyers to negotiate with the clients and who have the wealth of knowledge that they’ve accumulated over their careers. So I think that there is a really important reflection that needs to be done with respect to career paths of certain occupations that could be affected.

Mr. Sher Verick:
Yeah, well, thank you for those comments. Just firstly, on this overall issue on national employment policies that Juan raised, these are these comprehensive policy frameworks that the ILO works on with our member states. And I think it’s important to look at to what extent these issues are addressed within those policy documents and processes, more importantly, in terms of their implementation, but also looking at other entry points. I think you have to trade that off with what other entry points there are through the digitalization, the digital transformation strategies that countries are developing in terms of how they address decent work issues. So trying to find the right policy entry point is actually very key. This is something we’re looking at carefully also from the employment department, how best to target these issues, either through the employment entry point or through the digital entry point. But we need to innovate there. This is what we’ve recognized in recent years on digitalization as we have seen on climate change and other areas. And this issue of linking education and employment, I mean, in those contexts of those employment policies that I talked to mention and also Juan referred to, they are at the center of what we do. We have to look at the demand and supply side. We have to look at the different types of intervention. So my question is in the WSIS context, how can we collaborate? Because I’m best familiar with the WSIS processes. I’m very happy now to be participating in terms of C7, but with C4, how do we bring that perspective? It’s not just about a supply side view, but it’s also about what’s going on in the labor market, what employers need, how to create jobs. Because most countries, the number one issue is job creation, right? They spend a lot on skilling, but jobs are not being created. So the big, big question for most low and middle income countries is how do we create jobs? So I pose that also for Maria, but also for ITU, how do we connect this? And just finally, on inclusion, I think it’s very important. And we heard a bit more about that in the context of the joint ILO-ITU-Africa project. And I would also refer to the work we’re doing under the Prospects program, Dutch funded program, which looks at inclusion for forcibly displaced persons, refugees, but also the host communities. There’s eight countries, five in Africa. I won’t test my memory to give you the full list, but very important there is to see what solutions can be adapted to these underserved populations, right? So it’s very easy to think about all the flash AI stuff that we can see also across the road, but what matters for these people who are in the most vulnerable positions? And this is, when we look at the labor market, these are the ones who have very poor access to jobs in general, skilling at hardly anything. So how do we try to use these tools? How can we apply these tools to improve their outcomes

Ms. Maria Prieto:
and their access to decent work? Great, thank you. I think there was an extensive reply to your question. I think, yes, it’s a challenge then for us for Action Line 7 on e-employment and for skills to really connect supply and demand of labor. And also, as was mentioned, I think by Cher, looking at the intermediation of that employment services, public and private, et cetera. And so with that, I think if there are no further questions, no, we will end here. And then we will do our homework and report on this important demand to connect the two action lines. And unless my colleagues want to say anything else. Yeah, let’s connect the two action lines. Let’s connect. Let’s connect. Okay, great. Thank you so much for coming. Thanks. Thank you. Thank you.