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CCIA Submission to Rekabet Kurumu's Inquiry Into the Digital
CCIA Submission to Rekabet Kurumu’s Inquiry into the Digital Economy 27 April 2020 I. Introduction The Computer and Communications Industry Association,1 (“CCIA”) welcomes the opportunity to contribute to the market study into competition and the digital economy by Rekabet Kurumu (“Rekabet”), the Turkish Competition Authority. CCIA commends Rekabet for seeking a better understanding of the legal, economic and policy challenges that arise with the digitalization of the global economy and its significance in the competition analysis. CCIA looks forward to furthering the dialogue with Rekabet in this regard. The tech sector has had transformative effects on the entire economy. Tech has increased efficiency and lowered entry barriers in many markets and allowed the introduction of entirely new business models. Digital media distribution tools have created a space for individuals to broadcast their audio, photo and video content creations to the world. Online retail intermediaries like Hepsiburada and Trendyol allow small and medium sized enterprises to reach consumers and meet demand far beyond their geographic footprint, more quickly and cheaper than ever before. Social media services dramatically lower the cost for advertisers to reach their audience and avoid advertising wastage. Studies suggest that the consumer benefit of free online services is worth thousands of lira per person, per year.2 In order for innovation in the technology market to continue driving the global economy, both competition policy and sound antitrust enforcement must play a crucial role in ensuring that 1 The Computer & Communications Industry Association (CCIA) is a non-profit membership organisation that represents the interests of a wide range of companies in the Internet, technology and telecoms industries. -
Masters Thesis Stojko.Pdf
DEPARTMENT OF INFORMATICS TECHNICAL UNIVERSITY OF MUNICH Master’s Thesis in Information Systems An Information Model as a Basis for Information Gathering to comply with Data Portability according to GDPR Art. 20 Laura Stojko DEPARTMENT OF INFORMATICS TECHNICAL UNIVERSITY OF MUNICH Master’s Thesis in Information Systems An Information Model as a Basis for Information Gathering to comply with Data Portability according to GDPR Art. 20 Ein Informationsmodell als Basis fur¨ die Informationserhebung zur Datenportabilitat¨ nach Art. 20 DSGVO Author: Laura Stojko Supervisor: Prof. Dr. Florian Matthes Advisor: Dipl. Math.oec. Dominik Huth Date: November 15, 2018 I hereby declare that this thesis is entirely the result of my own work except where other- wise indicated. I have only used the resources given in the list of references. Munich, 15. November 2018 Laura Stojko Abstract With the announcement of the General Data Protection Regulation (GDPR) by the Euro- pean Union, data privacy laws shall be harmonized in European countries. In the digital era, personal data is of high significance for companies, especially within customer data- driven industries (e.g. social media platforms). Due to the new importance of personal data and its usage, the awareness for data privacy is increasing among people. Thus, good data privacy management is of high relevance for companies and customers. This thesis focuses on article 20 of the GDPR, which describes data portability as one essential aspect for new rights of the data subject. Data portability enables customers to receive their per- sonal data from companies and transfer it to others. Thereby, a level playing field within the market is supported. -
Natural Language Processing 2018 Highlights
NLP 2018 Highlights By Elvis Saravia 1 Table of Contents Introduction ............................................................................................................................................ 4 Research ................................................................................................................................................. 5 Reinforcement Learning ...................................................................................................................... 5 Sentiment Analysis and Related Topics ................................................................................................ 7 AI Ethics and Security .......................................................................................................................... 9 Clinical NLP and ML ........................................................................................................................... 12 Computer Vision ................................................................................................................................ 15 Deep Learning and Optimization ........................................................................................................ 17 Transfer Learning for NLP .................................................................................................................. 19 AI Generalization ............................................................................................................................... 20 Explainability and Interpretability -
Peertube Has Worked Twice As Hard to Free Your Videos from Youtube !
PeerTube has worked twice as hard to free your videos from YouTube ! Thanks to your donations, we have been developing a software to free us all from YouTube & Co for a year. Why have we gone much further than the first release, (crowdfunded in the spring of 2018), you might ask? Well, that’s because we sincerely believe in the emancipatory power of PeerTube. This article is a part of « Contributopia’s travel journals ». From October to December of 2019, we will assess our many (donations-founded) actions, which are tax-deductible for French taxpayers. Donate here if you can. La version originale (en Français) de cet article est à lire ici. Federation and instances to avoid creating a new tech giant PeerTube’s aim is to create an emancipatory alternative to centralized platforms a la YouTube. In a centralized service, you sign-up with a single address, and each and every of your actions, videos and data are gathered on a single huge computer. For example, Google’s, that hosts YouTube (to be precise, they are server farms rather than huge computers, but on a symbolic level it is the same thing!). Centralisation, CC-By SA Fédération, CC-By SA LILA LILA PeerTube is a software. It can be installed on a server by anyone possessing the appropriate skills; say, for the sake of argument, Bernadette, College X and karate club Y. This is called an instance, i.e. a PeerTube host. In concrete terms, hosting an instance creates a website (let’s say, BernadetTube.fr, CollegeTube.org or KarateTube.net) on which you can watch videos and sign-up, so you can interact or upload your own content. -
Data Transfer Project
Data Transfer Project August 20, 2018 Federal Trade Commission 600 Pennsylvania Ave NW Washington, DC 20580 To Whom It May Concern: Thank you for the opportunity to provide comment on the Federal Trade Commission’s Hearings on Competition and Consumer Protection in the 21st Century. As you may know, Google, Microsoft, Twitter, and Facebook recently announced the Data Transfer Project (datatransferproject.dev). We are excited to share our work on this project, including the thinking behind it, in response to your questions. Data portability is critical for user control and competition. Not only is this project relevant to the questions you raised in your request for comment on these topics, but we also encourage the Commission to consider the importance of portability throughout your process. The mission of the Data Transfer Project is to support direct, service-to-service portability. This will ultimately enable users to transfer data between two authenticated accounts behind the scenes, without having to download the data and relocate it themselves. This is an open-source project that will make it easier for people to switch services, or try new and innovative products, by improving the ease and speed of data portability. We have attached a detailed white paper that describes the technical foundations of the project and explains how our principles guided us toward this approach. The paper also includes detailed descriptions of the security and privacy considerations that are built into the project. Please let us know if you have any additional questions. Thanks, Keith Enright Julie Brill Damien Kieran Erin M. Egan Chief Privacy Officer Corporate Vice Data Protection Officer Vice President & Chief Google LLC President & Deputy Twitter, Inc Privacy Officer General Counsel Facebook, Inc. -
The Future of Data: Adjusting to an Opt-In Economy October 2018
The Future of Data: Adjusting to an opt-in economy October 2018 Prepared for 2 | Oxford Economics 2018 Contents Executive summary ...................................................................... 4 The dawn of the opt-in era ............................................................ 7 Who are these people and what do they want? ............................. 10 Not all consumers are the same .................................................... 15 The rise of the data economy ........................................................ 16 How industries use data ............................................................... 18 Meet the leaders ............................................................................ 21 Life in the data age ........................................................................ 29 The path forward: Calls to action ................................................... 30 Research methodology ................................................................. 31 Contact us .................................................................................... 32 Oxford Economics 2018 | 3 Executive summary 4 | Oxford Economics 2018 In a world increasingly driven by data, We found that consumers have individual consumers suddenly have a lot contradictory views of the information of power. How they exercise this power, economy. They will share sensitive data and the ways companies respond, will be yet do not trust the companies they share a major story for years to come. with, or fully understand how much is -
Challenges in the Decentralised Web: the Mastodon Case∗
Challenges in the Decentralised Web: The Mastodon Case∗ Aravindh Raman1, Sagar Joglekar1, Emiliano De Cristofaro2;3, Nishanth Sastry1, and Gareth Tyson3;4 1King’s College London, 2University College London, 3Alan Turing Institute, 4Queen Mary University of London faravindh.raman,sagar.joglekar,[email protected], [email protected], [email protected] Abstract cols to let instances interact and aggregate their users to offer a globally integrated service. The Decentralised Web (DW) has recently seen a renewed mo- DW platforms intend to offer a number of benefits. For ex- mentum, with a number of DW platforms like Mastodon, Peer- ample, data is spread among many independent instances, thus Tube, and Hubzilla gaining increasing traction. These offer al- possibly making privacy-intrusive data mining more difficult. ternatives to traditional social networks like Twitter, YouTube, Data ownership is more transparent, and the lack of centralisa- and Facebook, by enabling the operation of web infrastruc- tion could make the overall system more robust against techni- ture and services without centralised ownership or control. cal, legal or regulatory attacks. Although their services differ greatly, modern DW platforms mostly rely on two key innovations: first, their open source However, these properties may also bring inherent chal- software allows anybody to setup independent servers (“in- lenges that are difficult to avoid, particularly when consid- stances”) that people can sign-up to and use within a local ering the natural pressures towards centralisation in both so- community; and second, they build on top of federation pro- cial [12, 49] and economic [42] systems. -
Written Testimony of Keith Enright Chief Privacy Officer, Google United
Written Testimony of Keith Enright Chief Privacy Officer, Google United States Senate Committee on Commerce, Science, and Transportation Hearing on “Examining Safeguards for Consumer Data Privacy” September 26, 2018 Chairman Thune, Ranking Member Nelson, and distinguished members of the Committee: thank you for the opportunity to appear before you this morning. I appreciate your leadership on the important issues of data privacy and security, and I welcome the opportunity to discuss Google’s work in these areas. My name is Keith Enright, and I am the Chief Privacy Officer for Google. I have worked at the intersection of technology, privacy, and the law for nearly 20 years, including as the functional privacy lead for two other companies prior to joining Google in 2011. In that time, I have been fortunate to engage with legislators, regulatory agencies, academics, and civil society to help inform and improve privacy protections for individuals around the world. I lead Google’s global privacy legal team and, together with product and engineering partners, direct our Office of Privacy and Data Protection, which is responsible for legal compliance, the application of our privacy principles, and generally meeting our users’ expectations of privacy. This work is the effort of a large cross-functional team of engineers, researchers, and other experts whose principal mission is protecting the privacy of our users. Across every single economic sector, government function, and organizational mission, data and technology are critical keys to success. With advances in artificial intelligence and machine learning, data-based research and services will continue to drive economic development and social progress in the years to come. -
People's Tech Movement to Kick Big Tech out of Africa Could Form a Critical Part of the Global Protests Against the Enduring Legacy of Racism and Colonialism
CONTENTS Acronyms ................................................................................................................................................ 1 1 Introduction: The Rise of Digital Colonialism and Surveillance Capitalism ..................... 2 2 Threat Modeling .......................................................................................................................... 8 3 The Basics of Information Security and Software ............................................................... 10 4 Mobile Phones: Talking and Texting ...................................................................................... 14 5 Web Browsing ............................................................................................................................ 18 6 Searching the Web .................................................................................................................... 23 7 Sharing Data Safely ................................................................................................................... 25 8 Email Encryption ....................................................................................................................... 28 9 Video Chat ................................................................................................................................... 31 10 Online Document Collaboration ............................................................................................ 34 11 Protecting Your Data ................................................................................................................ -
Technology Stack for Decentralized Mobile Services
Technology Stack for Decentralized Mobile Services Matouš Skála Technology Stack for Decentralized Mobile Services by Matouš Skála to obtain the degree of Master of Science at the Delft University of Technology, to be defended publicly on Monday August 31, 2020 at 3:00 PM. Student number: 4893964 Project duration: November 15, 2019 – August 31, 2020 Thesis committee: Dr.ir. J.A. Pouwelse, TU Delft, supervisor Dr. J.S. Rellermeyer, TU Delft Dr. N. Yorke-Smith, TU Delft An electronic version of this thesis is available at http://repository.tudelft.nl/. Preface When I was choosing my thesis topic, I originally came up with an idea of designing a decen- tralized social network. After realizing how ambitious that goal was, I later decided to focus on more fundamental issues first and create a library that would allow for building any de- centralized applications, running purely on an overlay network consisting of smartphones. Rather than reinventing the wheel, I took inspiration from an existing networking library de- veloped at TU Delft over the last decade and created its wire-compatible implementation in Kotlin. Interestingly, in the end, I have even implemented a trivial social network to demon- strate the usage of the library, returning back to the original idea. I would like to thank my supervisor Johan Pouwelse for an endless stream of fresh ideas and valuable feedback, and to PhD students of the Delft Blockchain Lab for numerous coffee meetings and for serving me as a walking documentation of the existing codebase. Matouš Skála Prague, -
What If Cities Took a Central Role in Returning Citizens' Personal Data To
mesinfos.fing.org “WHAT IF CITIES TOOK A CENTRAL ROLE IN RETURNING CITIZENS’ PERSONAL DATA TO THEM?” 2020 THE “MESINFOS - SELF DATA ACKNOWLEDGEMENTS: CITIES” TEAM AT FING: Special thanks to Virginie Steiner (La Rochelle), Manon Molins, Chloé Friedlander, Guillaume Jacquart, Sylvie Turck (Nantes Métropole), and Maria-Inés Léal Fanny Maurel // Sarah Medjek for MyData France. (Grand Lyon), as well as to Guillaume Chanson, Cécile What if cities took a central role in returning > an analysis of the relevant governance models Christodoulou, Aurialie Jublin, and Mathilde Simon. citizens’ personal data to them, so their citizens can when considering how to share personal data with individuals; TRANSLATION: Jianne Whelton use personal data to make their lives easier, get to know each other better, contribute to territorial > a survey of cities efforts to share data, including decision making or participate in public interest some examples to draw inspiration from (and some CREATIVE COMMONS projects? to avoid); > illustrated methodologies you can use to This document is available under a Creative Commons Attribution 4.0 License (France): For the past year, Fing has been working with three https://creativecommons.org/licenses/by/4.0/deed.fr. implement a Self Data initiative in your region major French cities — Nantes Métropole, (the energy (plus examples drawn from our work with Nantes You are free to share — copy and redistribute the material in any medium or format — and adapt — remix, transform, and build upon the material for transition), La Rochelle (sustainable mobility), and Métropole, La Rochelle and Greater Lyon): identify any purpose, even commercially — under the following terms: attribution — you must give appropriate credit, provide a link to the license, and indicate Greater Lyon (social welfare) — to enable them to the relevant personal data, imagine use cases if changes were made. -
NOTICES ET PORTRAITS DES DÉPUTÉS DE LA Xve LÉGISLATURE
NOTICES ET PORTRAITS DES DÉPUTÉS DE LA XVe LÉGISLATURE PRÉSENTATION PAR GROUPE - Dernière modification le 30 Septembre 2021 - Les Républicains 3 La république en Marche 29 Les Constructifs : républicains, UDI, indépendants 108 La France insoumise 118 Nouvelle Gauche 124 Gauche démocrate et républicaine 133 Mouvement démocrate et apparentés 138 Non inscrit 151 Index alphabétique 157 Les Républicains 3 Les Républicains Ain - Circonscription n° 5 Drôme - Circonscription n° 4 M. Damien Abad Mme Emmanuelle Anthoine Les Républicains Les Républicains Né le 5 avril 1980 à Nîmes (Gard) Née le 2 juillet 1964 à Saint-Vallier (Drôme) Sans profession déclarée Avocate Membre du conseil départemental (Ain) Membre du conseil départemental (Drôme) Élu à l'Assemblée nationale le 20 juin 2012 Élue à l'Assemblée nationale le 18 juin 2017 Réélu le 18 juin 2017 Vaucluse - Circonscription n° 5 Var - Circonscription n° 3 M. Julien Aubert Mme Edith Audibert Les Républicains Les Républicains Né le 11 juin 1978 à Marseille (Bouches-du-Rhône) Née le 7 mars 1948 à Hyères (Var) Magistrat à la Cour des Comptes Retraitée Conseiller régional (Provence-Alpes-Côte d'Azur) Élue à l'Assemblée nationale le 18 juin 2017 Élu à l'Assemblée nationale le 20 juin 2012 Remplacement d'un député ayant démissionné pour Réélu le 18 juin 2017 cause d’incompatibilité prévue aux articles LO 137, LO 137-1, LO 141 ou LO 141-1 du code électoral 4 Les Républicains Réunion - Circonscription n° 3 Aube - Circonscription n° 2 Mme Nathalie Bassire Mme Valérie Bazin-Malgras Apparentée au groupe Les Républicains Les Républicains Née le 22 janvier 1968 à Saint-Pierre (Réunion) Née le 31 octobre 1969 à Romilly-sur-Seine (Aube) Retraitée de l'enseignement Commerçante Conseillère régionale (Réunion) Élue à l'Assemblée nationale le 18 juin 2017 Élue à l'Assemblée nationale le 18 juin 2017 Meurthe-et-Moselle - Circonscription n° 4 Marne - Circonscription n° 1 M.