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Enabled by recent improvements in generation methodologies, DeepFakes have become mainstream due to their increasingly better visual quality, the increase in easy-to-use generation tools and the rapid dissemination through social media. This fact poses a severe threat to our societies with the potential to erode social cohesion and influence our democracies. To mitigate the threat, numerous DeepFake detection schemes have been introduced in the literature but very few provide a web service that can be used in the wild. In this paper, we introduce the MeVer DeepFake detection service, a web service detecting deep learning manipulations in images and video. We present the design and implementation of the proposed processing pipeline that involves a model ensemble scheme, and we endow the service with a model card for transparency. Experimental results show that our service performs robustly on the three benchmark datasets while being vulnerable to Adversarial Attacks. Finally, we outline our experience and lessons learned when deploying a research system into production in the hopes that it will be useful to other academic and industry teams. ; This work has been supported by the AI4Media H2020 project, partially funded by the European Commission under contract number 951911, and the US Paris Tech Challenge award, which was funded by the US Department of State Global Engagement Center under contract number SGECPD18CA0024.

Decisions on environmental topics taken today are going to have long-term consequences that will affect future generations. Young people will have to live with the consequences of these decisions and undertake special responsibilities. Moreover, as tomorrow's decision-makers, they themselves should learn how to negotiate and debate issues before final decisions are made. Therefore, any participation they can have in environmental decision-making processes will prove essential in developing a sustainable future for the community. However, recent data indicate that the young distance themselves from community affairs, mainly because the procedures involved are 'wooden', politicians' discourse alienates the young and the whole experience is too formalized to them. Authorities are aware of this fact and try to establish communication channels to ensure transparency and use a language that speaks to new generations of citizens. This is where STEP project comes in. STEP (www.step4youth.eu) is a digital Platform (web/mobile) enabling youth Societal and Political e-Participation in decision-making procedures concerning environmental issues. STEP is enhanced with web/social media mining, gamification, machine translation, and visualisation features. Six pilots in real contexts are being organised for the deployment of the STEP solution in 4 European Countries: Italy, Spain, Greece, and Turkey. Pilots are implemented with the direct participation of one regional authority, four municipalities, and one association of municipalities, and include decision-making procedures on significant environmental questions.