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This Working Paper considers the implications for cloud accountability of current proposals under the draft General Data Protection Regulation to modernise the EU Data Protection Directive. It makes recommendations aimed at improving the technology-neutrality of the proposals and their appropriateness for cloud computing, with a view to ensuring that the proposals will maintain or enhance protection of personal data for data subjects while not unduly deterring cloud computing.

"Instead of requiring a typed password or a fingerprint, this security software asks the user to speak or mouth a password directly at a device's camera."

"Dropbox is "proposing to copy the keys to your house, move in and live with you.""

Google came under fire this week after its new Photos app categorized photos in one of the most racist ways possible. On June 28th, computer programmer Jacky Alciné found that the feature kept tagging pictures of him and his girlfriend as "gorillas."

Wearable technology's evolution is not about the gadget on the wrist but what is done with the data they collect, says computational biologist

"Facebook's News Feed-the main list of status updates, messages, and photos you see when you open Facebook on your computer or phone-is not a perfect mirror of the world. But few users expect that Facebook would change their News Feed in order to manipulate their emotional state."

Privacy is a hot-button issue in the tech world. How will it fare in the age of pervasive computing - a world of billions of connected devices, systems, and services exchanging personal data?

"If you need to reverse-engineer a USB protocol on a computer running Linux, your work is easy because you control everything on the target system - you can just look at the raw USB data. If you'd like to reverse-engineer a USB device that plugs into a game console, on the other hand, your work is a lot harder. Until now."

The blind application of machine learning runs the risk of amplifying biases present in data. Such a danger is facing us with word embedding, a popular framework to represent text data as vectors which has been used in many machine learning and natural language processing tasks. We show that even word embeddings trained on Google News articles exhibit female/male gender stereotypes to a disturbing extent. This raises concerns because their widespread use, as we describe, often tends to amplify these biases. Geometrically, gender bias is first shown to be captured by a direction in the word embedding. Second, gender neutral words are shown to be linearly separable from gender definition words in the word embedding. Using these properties, we provide a methodology for modifying an embedding to remove gender stereotypes, such as the association between between the words receptionist and female, while maintaining desired associations such as between the words queen and female. We define metrics to quantify both direct and indirect gender biases in embeddings, and develop algorithms to "debias" the embedding. Using crowd-worker evaluation as well as standard benchmarks, we empirically demonstrate that our algorithms significantly reduce gender bias in embeddings while preserving the its useful properties such as the ability to cluster related concepts and to solve analogy tasks. The resulting embeddings can be used in applications without amplifying gender bias.

"Solar Protocol is a web platform hosted across a network of solar-powered servers set up in different locations around the world. A solar-powered server is a computer that is powered by a solar panel and a small battery."

"Croquet eliminates dedicated servers and server-side code from online multiuser apps. Instead, users connect through our worldwide network of public reflectors. Every input is mirrored by the reflector to a shared virtual computer that runs bit-identical across every client, so everyone stays perfectly in sync"

"As technology-especially computer, information, and Internet technology-permeates all aspects of our society, people who understand that technology need to be part of public-policy discussions. We need technologists who work in the public interest. We need public-interest technologists. Defining this term is difficult. One Ford Foundation blog post described public-interest technologists as "technology practitioners who focus on social justice, the common good, and/or the public interest." A group of academics in this field wrote that "public-interest technology refers to the study and application of technology expertise to advance the public interest/generate public benefits/promote the public good.""

"There are many articles circulating about all the privacy incursions of Facebooks new messenger app but I don't think they could all be true. "