 Good morning ladies and gentlemen. First, I would like to thank the WPC for inviting me to such a high-level event and second, I would like to thank you all for being here despite the time issue. My name is Metilde Paak and I'm an economist at the OECD. I am working in the labor market work stream in the economics department and today I am very happy to share with you some insights about how digital transformation is reshaping jobs. Based on a paper I wrote with co-authors on the gig economy platforms. I unfortunately couldn't be here on Friday and attend a session about preparing children and youth for jobs in the 21st century. But I hope I will complement this session by bringing some optimism to the young generation and the more experienced ones about the future of work. Ladies and gentlemen, have you ever dreamed of a world where you would be matched with a perfect employer to do a job that fit perfectly your constraints and would highlight your skills? Well, ever since I started working on the gig economy platforms, I couldn't help thinking that this dream could one day be true. Are gig economy platforms the new superior business models, a boon, or will they be a bane for workers that will be just left with scraps? To address this question, I will present you the macroeconomic effects of gig economy platforms based on key features of their business models and then I will present also their flaws that needs to be addressed. But first, I would like to give you a quick picture about what gig economy platform exactly cover. So gig economy platforms, they use digital technologies to match workers to customers on a per task basis, the gigs. And there is really a wide range of services and tasks. They can be physical and local, like Uber and Handy, or online and worldwide. They can be routine tasks, or that doesn't require any specific qualification, like adding keywords on images for Amazon Mechanical Turk, or they can be high-skilled tasks, which requires specific professional diploma, like for consulting or web designing, in the case of Upwork. And so all this wide range of services and tasks for workers to do, for businesses to outsource, for consumers to enjoy. And also note, gig economy platforms, they intermediate labour. So this excludes any kind of digital platforms that intermediate other kinds of services, like accommodations. Or trade goods. Now, I will move to present you some, a selection of economic impacts of gig economy platforms on macroeconomic variables. I won't bore you with the technical details. It's early and it's in Sunday morning. But you have to know that we developed a stylised theoretical model and that we tested some of these, the conclusions empirically. So there are two key features to the business models that need to be accounted for when we want to assess the potential effects of economic, sorry, economic effects of gig economy platforms. First, they develop trust-building mechanisms, like curator of entry or exit to platform, reputation rating systems, customer support and insurance, payment intermediation. And this lower barriers to work because there are some alternatives to formal qualifications that should normally stand for quality check for the customers. These in turn give more job opportunities to unemployed and people that are weakly attached to the labour market, which in the end would raise total employment. Second, they rapidly match supply of labour to fluctuations of demand, by using digital matching algorithm, self-employed contractors and search pricing, in the case of Handy and Uber for instance. This would increase matching efficiency at employment level, at given employment level, which in turn would raise productivity. But be careful because gig economy platforms, they tend to raise total employment, so this really erodes the productivity gain. So in total, the effect on productivity is a bit ambiguous. So far, gig economy platforms, they seem to be some excitingly innovative thing. Well, I hope that's how you feel. But like every innovation, they are not perfect right away, and they have flaws that need to be addressed. And this is a challenge for policymakers, so that in order to really get all the potential gains in productivity or employment, that the public policies need to be adapted. So for instance, the gig economy platforms, they reveal the weaknesses in the market failures and services, which means that the traditional rules may have become obsolete, like for instance, the occupation licensing. And then we have to really promote level playing field because we don't want to realise that gig economy platforms were successful because basically they just exploit some regulatory or legal loophole, and not because of their technological innovation. And so the regulation need to be applied to all providers on equal footing, and social contribution and value added taxes, they need to be harmonised across platforms. And then there's regulatory sandboxes, which can be provided to test whether really the innovation part of the platforms explained as success. Then strong product market competition. This would limit the emergence of dominant players. And this could be helped by promoting mobility of workers across platforms, like for instance, by limiting abusive clauses to prevent switching from one platform to another, or allow the transfer of reputation ratings across platforms since these reputation ratings will stand for qualifications. And also the scope and the scale of data collected by the incumbent platforms, they will feed their matching algorithms. And so this could also be like an entry barrier to new entrants because they don't have access to these data and would have maybe less performing matching algorithms. Strong competition product markets would also help preventing the emergence of dominant players in labour markets. But to really improve working conditions of workers, there needs to be some adaptation of labour market regulations, rules on collective bargaining, access to social protection and training. And so now the second challenge for policy makers is to address these flaws rapidly to keep up with the rapid development of the economy platforms. So what will the future look like? I don't know. Perhaps we won't be talking about dream jobs or jobs in the 21st century, but rather about dream tasks, dream gigs, that would pick through really this big pool of possibilities and through very performing matching algorithms. Or perhaps by outsourcing the tasks we don't want to do or that are routine, by outsourcing them to machines or other platform workers, perhaps we can free our mind and come up with some creative ideas to create some other kind of tasks which don't exist for now and which we can't imagine now but which will require human intelligence. Thank you for your attention. Thank you.