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Eurofound is the tripartite EU agency providing knowledge to assist in the development of better social, employment and work-related policies. Access latest research, data and analysis in the areas of living and working conditions.

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Homepage | Eurofound

europa.eu

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Eurofound is the tripartite EU agency providing knowledge to assist in the development of better social, employment and work-related policies

Eurofound

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self.__next_f.push([1,"Europe is experiencing a crisis of unaffordable housing. Since 2010, average sale prices in the EU have risen by 55.4 % and rents by 26.7 %, outpacing income growth for many groups. These averages mask the severity of the problem experienced in some regions and by certain groups. For example, in some EU Member States, prices have more than tripled. And within Member States trends in prices and rents have been highly uneven across regions and degrees of urbanisation. Typically, increases in the cost of housing in urban centres have far outpaced average trends. Many young people in Europe are experiencing this affordability crisis particularly acutely. Their employment earnings are relatively low, and they are more likely to be in temporary or insecure employment than older people. They often struggle to rent a home where they would choose to live. If they want to purchase a home, they may struggle to save for a down payment or qualify for a mortgage. Young people continue to move to urban areas, where employment opportunities are concentrated but housing is least affordable. They are facing these obstacles in a crucial period of their lives, while transitioning to independent adult living and making decisions about education, careers, relationships and family formation. For them, Europe’s current housing affordability crisis is a foundational problem."])

self.__next_f.push([1,"24:T551,The problem of unaffordable housing is not new. In certain European regions and cities, housing costs are a long-standing challenge for many groups. However, in recent years, the problem has become more widespread, affecting larger parts of the population. High energy prices, labour shortages, environmental regulations, zoning laws and the scarcity of land have limited construction activity. There has also been an increase in the use of housing as an investment vehicle. This means that individuals and families are competing with investors in an increasingly tight housing market. While the EU has no direct competence in housing, it exerts a significant influence through relevant guidance, legislation and funding. As Europe’s housing crisis has intensified, the European Commission has responded by, for the first time, including housing as a distinct part of a commissioner’s portfolio. Dan Jørgensen, the new Commissioner for Energy and Housing, is tasked with supporting Member States in addressing the causes of housing shortages and unlocking both public and private financing to invest in affordable and sustainable housing. Other EU bodies, including the European Parliament and the European Investment Bank, are also stepping up to the challenge of uncovering the drivers of the housing crisis, identifying solutions and delivering funding.25:T417,Moreover, aggravated constraints weigh on working parents, due to the closure of schools, kindergartens and creches, combined with the recommendation or even prohibition not to rely on grandparents help, as they are the group most at risk. Several countries have (at this stage) closed their borders for person movement, while the movement of goods remains a priority to secure. This immediate disruption created specific problems for the cross-border workforce (e.g. daily commuters, cross-border care-workers) – both as regards peoples’ endeavours to go to their home country, but also to be able to go back to work. Businesses (and households) in border regions relying on a higher number of cross-national commuters are particularly affected. Also, sectors relying on a seasonal workforce from other countries (in particular agriculture) are anticipating difficulties at this stage. The large disruption in supply chains, work-arrangements, sudden decline of revenue due to the 'stay at home' order has put Europe into an emergency mode. "])

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self.__next_f.push([1,"2c:T438,Jorge Cabrita is a senior research manager in the Working Life unit. He is responsible for formulating, coordinating and managing European-wide research, and promoting the dissemination of findings in the areas of working conditions and industrial relations. His main research areas of interest include working conditions and job quality, working time and work–life balance, workers’ health and well-being, gender equality and the socioeconomic impacts of the transition to a climate-neutral economy. He is currently leading research on working time developments and on social dialogue and collective bargaining during the COVID-19 pandemic. Previously, he worked as a researcher at the Centre for Studies for Social Intervention and at the Research Centre on the Portuguese Economy of the Lisbon School of Economics, and as a trainer and consultant in the areas of strategic management, organisational communication, leadership and team building. He holds a BSc in Economics and an MSc in Socio-Organisational Systems of Economic Activity from the Lisbon School of Economics.2d:T4db,We tend to have, yeah, we tend to have a higher share of our employment in smaller and medium sized enterprises. That can be a strength. But again, it's in terms of productivity, a lot of productivity growth actually occurs in larger and larger businesses and productivity growth, productivity levels and growth rates tend to be higher in larger businesses. So that could be part of the answer. There are plenty of other explanations or potential explanations. One of them, which I particularly, I think maybe behind this decline in productivity growth is one that was advanced by an American economist many years ago, William Baumol, who talks about technologically stagnant sectors, sectors where which a lot of our employment now is in contact services, in-person services. Those types of services are very hard to automate. They're very hard to improve the level of productivity in those because they rely on one person doing something for another person. And so they're not amenable to productivity improvements in the way that, for instance, manufacturing or agriculture have been. And because we have a higher share of our employment in those types of sectors, that that could well be one of the things that represents a drag on growth.2e:T514,Yeah, I mean, I think we can over fixate on productivity. It's not the measure of everything. I mean, I think it's certainly right that policymakers pay attention to it and pay attention to the fact that there's been this drift in particular between productivity growth rates between ourselves and the US. That's something that we should look at and we should try and address. But, you know, there are many, many things in Europe which we do well. And you talk about competitiveness at the beginning. There is this tendency to kind of equate competitiveness and productivity. But Europe is, it may be less productive than it was, or at least it's more productive, but it's the rate of growth of productivity is lower than it probably should be and certainly lower than it was 20 or 30 years ago. But we're still competitive. We have a very significant trade balance with the rest of the world. We have higher living standards, you know, probably only comparable to those in the US. So, you know, on many fronts, we have an enviable quality of life. And arguably, part of that is, we actually work fewer hours now than we did a generation ago, in order to generate higher living standards. So there are trade-offs that are made in Europe, which maybe aren't made to the same extent in China or the US.2f:T45b,And one of the questions in the survey this year asks about whether technology is removing tasks from your job or generating new tasks in your job. And there's a much higher figure of people saying that it's adding new tasks to their jobs and removing tasks from their job. And that kind of concords with my general sense that we needn't be worried about technology stealing our jobs anytime soon. I think that's not going to happen. Why the"])

self.__next_f.push([1," emphasis on job quality rather than on technological unemployment? Well, job quality is part of the answer of trying to actually encourage people who are on the margins of the labour market to re-enter the labour market to do jobs that we need done. We know that there are still significant under-representation in the labour market of various groups of people, including women, but also older people, people with disabilities: The long-term unemployed. There is a nexus of job quality which, you know, if you can give people stable, decent, reasonably well-paying jobs, you can encourage them to step off the margins of the labour market and actually contribute to growth.30:T705,"])

self.__next_f.push([1,"Hello, Mary, and thanks for the invitation. I would say that if you look left and right and try to look at what is happening around AI in terms of both research and policy action, you can see that we're in the in the midst of a global race for artificial intelligence. And that is because emerging evidence suggests that, indeed, artificial intelligence holds the promise of massive competitiveness gains, of massive improvements in efficiency, but also of moving our societies and our economies to the next phase of development. So of course, look at it from this perspective: Artificial intelligence is a huge potential amplifier of both economic gains and broader societal gains. And you can see this kind of line of thought in the policy proposal that has come up from the Commission in the past six months or so. So in the beginning of the year, the Commission has put forward the AI action plan which outlines, let's say, the broad context and the broad set of policies that the EU should focus on in the next years or so, and more recently, so to speak, the Commission has put some meat on the bones through the apply AI strategy that comes and tries to actually, let's say, incentivize investment and usage. So not only not only investment, but also usage of AI in European enterprises. So put it all together, there's a lot of interest in the potential gains that the artificial intelligence can bring to our economies, and I would say legitimately so, right, because we've seen from previous waves of industrial and previous waves of investment or technological change and technological revolutions. That technology can actually, you know, move our economies forward, boost productivity, boost efficiency and actually create more jobs, and also contribute to an increase of better jobs."])

self.__next_f.push([1," Yeah. So indeed, as you say, the European Working Conditions Survey was fielded in 2024 and we're already in late 2025. Things might have changed since then because one thing that we know about the uptake of general TV AI is that, unlike with previous technologies. The increase in the number of users since its launch in November 2023 has been exponential, but what we know from 2024, based on the European Working Conditions Survey, is that on average 12% of workers are using generative AI technologies at work. Yeah. So, we're not talking about the use of generative AI technologies in private workspaces. Now when we talk about differences across countries, as with everything that that is in Europe, when we compare European countries, there are massive differences. So in general, the update of generative AI tends to be much lower in Eastern and Mediterranean countries and much higher in continental, in Nordic countries, and the same is valid for sectors such as ICT, banking, tend to have very high levels of uptake of generative AI. But also because this type of technology lends itself to the use in this kind of jobs and this type of occupations, and it's much lower in sectors like constructions and agriculture, where this, this specific type of AI technologies is not as useful. But in addition to the data from the European Working Conditions Survey, we also have data from Eurostat, which looks at the use of artificial intelligence in European enterprises and the data show that, on average, around 13.5% of European enterprises use one type of artificial intelligence system with larger enterprises being much more likely actually to use an AI technology. This is also because of the investments required to use and to buy artificial intelligence systems, but also because of the economies of scale. Larger companies tend to benefit more from artificial intelligence technologies, and in that respect, the recent apply AI strategy that the Commission published last week."])

self.__next_f.push([1,"Just all that I've seen up to this point points actually into the opposite direction. That is, that artificial intelligence is not actually going to destroy massive amounts of jobs, but it's going to reshape the way work is done. So, in the next five years or so, I don't think we're looking at the technological unemployment because of artificial intelligence, but we're looking at significant changes in the way people are carrying out their tasks, the way people are organising their work and the way people are doing in general work within an organisation. So I think this is where the massive impact of artificial intelligence are going to be. That being said, some of the evidence points to specific negative impacts on the number of jobs in particular parts of the labour market, and I'll give you an example. The best example is online labour. Supermarkets where you have lots of freelance workers, people doing job to online platforms, people trying to do fulfil tasks rather than do jobs as bundles of tasks and there in the aftermath of the launch of ChatGPT. We've seen a massive decline in the number of tasks posted by potential buyers because they are not employers, right? And that points to the fact that indeed at the fringes of the labour market we might see a negative effect. Of generative AI in terms of the number of jobs and one particular occupation seems to be very much negatively impacted and that is the job of translators, right? The number of translator jobs have has decreased massively in the in the aftermath of the launch of ChatGPT, and continues to do so because this technology tends to automate very well translation tasks. So, the type of jobs that translators are currently doing on the nature of the translation job has changed significantly since."])

self.__next_f.push([1,"That's a very good question, Mary and I would begin by making a distinction first, because I think that's very important and the distinction is between algorithmic management and artificial intelligence, because I think also sometimes people use these terms interchangeably and this shouldn't be the case. So by AI we mean all those technologies that we are just discussing until now, generative AI, collaborative robots, advanced artificial intelligence that are deployed in factories and so on and so forth by algorithmic management we mean technologies, digital technologies that are used in the workplace to automate management functions. They can be married or put together with artificial intelligence, but they can also function without actually out of artificial intelligence systems. And I think that's an important distinction to make because we don't need to actually necessarily link all the potential negative outcomes that algorithmic management systems can bring to artificial intelligence, right? Those tend to be tend to be linked more that are more likely to be linked with automation of tasks, the use of software to monitor the hours, the use of software to allocate tasks, the use of software to allocate performance targets. And when we look at the European Working Conditions Survey, this is basically where we see the most negative impacts, right? We call it in in house an algorithmic penalty for workers because we see that workers who are subject to algorithmic management in in this way tend to have poorer working conditions across the board."])

self.__next_f.push([1,"34:T508, That's a very good question again. And I think from our case studies, we do not see, at least in Europe, organisations trying to actually move towards full automation of tasks. On the contrary, I think we're at the stage when organisations experiment with new technologies and try as much as possible to involve workers in the decisions that lead to the adoption of a new technology. So, the case studies that we've seen in Eurofound reveal that when organisations try to involve workers in the piloting phase, try to have work a worker, say when the technology is being deployed across the organisation, but also when the when decisions are linked to how the technology is embedded into current work processes. This results basically in a successful adoption On the contrary, when technological deployment is a unilateral decision of the employer, this tends to result in favour. However, we haven't seen this kind of behaviour because I think organisations themselves understand and recognise the value of the workers themselves, so I don't think we're in this kind of 0 sum game scenario in which technology technologies are deployed by organisation. Just because there is availability, but they are deployed because they can actually bring significant improvements for both of them. 35:T477,Target their inspections or they are using mobile inspection applications or they are even using chat bots that can automate the routine tasks and provide information to or relevant parties. Currently we are having several examples in Member States of implementation in these fields and also the inspector is should rethink the internal structure to encourage collaboration between host experts, data scientists and legal advisors, and finally stakeholder engagement is key because we have identified that enforcement should also focus on education and facilitation with enforcement powers. As the last resort for Labour inspectorate and workers organisation, social partners partners could play, could be part of the strategy. I think also we're also collaborating with the the senior Labour Inspector committee and we have seen and that actually they are all. We're also working on this area. They have developed a paper on digitalisation and the use of machinery and robotics using AI, presenting several case studies in order to inform labour inspectors, and this could be used as a training machine material for labour inspectors as well.36:T6f4,"])

self.__next_f.push([1,"Social effects and the AI should be assistive, not substitutive, supporting human decision rather than replacing it, particularly when humans are affected. For example, in our case study one of our case study, we have seen a manufacturer who used the AI as an assistive tool allowing workers to retain control over final decision worker participation from start is crucial. When workers are engaged in the design, deployment and evaluation of the AI systems, outcomes are far better for both performance and safety and this also promotes acceptance from the worker side and successful integration. And we have identified in these cases there were given names to the robots. So it looked that there was a good spirit of collaboration between them. Skills development was also found to be a key issue. Training was found to be very important and not only in terms of the hard skills and this risk healing procedure, but also in terms of soft skills, communication and development of critical thinking as well because there are several things that. Humans cannot afford losing further or more, as automation can leave behind fragmented manual tasks. Risk killing is both a challenge, but also an opportunity where the procedure can increase stress to workers. Also, AI based systems can.  Should comply with legal and ethical standards included in transparent decision making. Nowadays, we are having apart from the Framework Direct Directive, that is a fundamental legislative provision for Occupational Safety and Health. This system should also comply with the machine regulation, the AI Act, the Data Act, while at the same time GDPR should be respected and human oversight is of high importance, as responsibility cannot be sifted or served with the AI system for this purpose. "])

self.__next_f.push([1,"37:T472, For this purpose we have developed, when it comes to for example the automation of tasks in noir, a tool that the enterprises, especially small and medium enterprises could use in order to be able to identify all those risks that are reported in our studies. They can implement those measures in order to mitigate this kind of risks at the same time, since the labour inspectorates and the authorities who have adequate training, as well as workers, representatives and the unions have a more active role and workers participation on this. This could create a climate that could assist with all these good practises enterprises in order to successfully introduce this kind of technologies and automations. At this point I would just like to come back to the issue of trust mentioned earlier. And building trust in AI at work requires transparency, fairness and human oversight. From our point of view, especially when systems influence task allocation, performance evaluation or decision making and without clear accountability and working involvement, AI can feel unclear and disempowering, undermining confidence and increasing stress.38:T591,"])

self.__next_f.push([1,"And I think clearly, I mean, you're making the point here that this is a growing emerging issue that we have to monitor on an ongoing basis. And I think Dragos you made that point earlier also about the change even over a period of a year that we could expect to see in terms of take up and impact. And the trust issue I mean is fundamental in in all areas of our lives and work. And certainly, if this is going to impact on trust in the workplace, then it is something that needs to be addressed and you've raised many of the issues that of the contributory factors that could be brought to play in the workplace. But I think I would like to bring it back up again just to sort of saying, why is this important because you know, I suppose we have to move away from the individual workplace that wants to see greater productivity and competitiveness. But really to the global stage where we're seeing Europe placed against the other major trading blocs and we've, as we said at the start, Dragos, we've looked at you know other trading blocs and how they're moving forward. And I know we've put investment into AI or we're planning to put it in according to President von der Leyen and in a in a massive way or what we would consider to be a massive way, but I understand that's actually kind of like tuppence worth when it comes to the other trading blocks in terms of the investment that's been made in, in, in those areas."])

self.__next_f.push([1,"39:T493,Yeah, I think that's particularly the issue for Europe because we're in a in a catch, we're in a position where we try to catch up with the big two other big blocks that are investing in. Yeah. And that's the United States and China. Just to give you an example of the scale of investments in artificial intelligence in the United States, last year, private investment in the technology was in the range of €500 billion, right. Moreover, that sort of investment which is much higher. When compared to previous cycles of investments in new technologies accounted for about 80% of economic growth in the United States. So that gives you a kind of an idea of what we're up against in the UK when it comes to artificial intelligence. So it's no small task, basically, A - to catch up with this big competitors including China and B - to kind of develop the type of artificial intelligence systems that we would like to see. Because it's important to mention that we already in Europe have a a framework of artificial intelligence that are that emphasising key principles such as transparency, unbiased data and so on and so forth, that lie at the core of the way we think. 3a:T739,"])

self.__next_f.push([1,"AI is going to benefit our societies, which is very different basically to how both the United States and China are currently thinking about AI. So, we want AI for social good, and that's big tasks in itself, not to speak about the amount of investment that we need to put into that, so the policy initiatives that you've seen over the past year coming at the at the European level, try to fulfil exactly those goals, A - to kind of develop an European AI that is fundamental on the principles that we have, and B - incentivize more businesses. More companies, including the public sector, to use artificial intelligence even more because you know this the goals that we have at the moment that are driven by digitalization. Are interconnected with the goals that we're pursuing in other domains, be that greening, be that dealing with demographic change, be that trying to have better public services and so on and so forth. So you know AI is let's say, if you want a transversal theme that that cuts across various kind of domains that we care about. But as societies and the other thing that I wanted to say is to go a bit back at the discussion on productivity, because I think to me at least the issue of productivity on the issue of productivity lies everything, right? So, if AI ends up increasing productivity, improving working conditions, then we're in the best-case scenario, right? And there's a massive promise there, right? There's a lot of research currently being done on the issue of productivity that shows that there's a lot of, let's say, quite a few unfulfilled promises if you want. When it comes to artificial intelligence, there's, you know, randomised control trials that look at the impact of artificial intelligence and productivity, find massive improvements. So, in the range of 40 to 60%, improvements in productivity. "])

self.__next_f.push([1,"There's so many known knowns, unknown knowns, and unknown unknowns, Dragos. So, in this world, and I suppose the danger that we also have as European level is that we have, you know, so many strategies. We have the Apply AI Strategy, we have the AI innovation package, we have various other directions and initiatives that are being brought into play, but without them being embedded in a really active way. As you say, we're not really going to see the results bearing fruit and that's something that we will have to monitor on into the next phase if we're going to see the kind of benefits we want to reap from this and particularly if we're in competition with the other trading blocks, as you say you have invested and many billions more into this and then we have been able to do so far and so look as you know and as you can see, we could talk about this really probably for the rest of the week and we could come back next week and do the same again. But I would like to just if you like close this off as we do with each of our podcasts, and really, if I could ask you very briefly and really do be succinct on these, what are your three recommendations if you had policymakers in front of you to maximise the benefits of AI at the workplace while protecting workers from the emerging risks to their working conditions and two job quality. What would they be? Talk to me in 3 Ioannis. "])

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