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The Digital Standard is an ambitious, open, and collaborative effort to create a digital privacy and security standard to help guide the future design of consumer software, digital platforms and services, and Internet-connected products.

The standard for public code is a set of criteria that supports public organisations in developing and maintaining software and policy together

"The Coalition for Content Provenance and Authenticity (C2PA) addresses the prevalence of misleading information online through the development of technical standards for certifying the source and history (or provenance) of media content. C2PA is a Joint Development Foundation project, formed through an alliance between Adobe, Arm, Intel, Microsoft and Truepic. "

"SoLiD is a proposed set of conventions for building decentralized social applications on the Linked Data stack. SoLiD is modular and extensible. It relies as much as possible on existing W3C standards. SoLiD applications are somewhat like multiuser applications where instances talk to each other through a shared filesystem, and the Web is that filesystem. "

Inspiration for standard labelling like creative commons

inspiration and experience for iot signals

"A direct interpretation of the Internet of Things concept refers to the usage of standard Internet protocols to allow for human-to-thing or thing-to-thing communication."

The makers of the We-Vibe, a line of vibrators that can be paired with an app for remote-controlled use, have reached a $3.75 million class action settlement with users following allegations that the company was collecting data on when and how the sex toy was used. Standard Innovations, the Canadian manufacturer of the We-Vibe, does not admit any wrongdoing in the settlement finalized Monday.

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.

"A proposed standard which allows websites and services to disclose information about their usage of analytics software and user tracking. "

Simpler, Stronger, Authentication. The Mission of the FIDO Alliance is to change the nature of online authentication

"As the Web Monetization ecosystem grows, an increasing number of researchers are studying, exploring, and writing about Web Monetization. Read and discover their findings on this shelf within the Web Monetization Resource Library."