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Trustworthy AI
Trustworthy AI is a programme of work of the ITU (United Nations Specialized Agency for ICT) under its AI for Good programme. The programme advances the standardization of a number of Privacy-enhancing technologies (PETs), including homomorphic encryption, federated learning, secure multi-party computation, differential privacy, zero-knowledge proof. Privacy-Enhancing Technologies are complex and the working can be considered counterintuitive. For instance, homomorphic encryption enciphers data, yet if this data is numerical, it is still possible to compute on this data (the outcomes still being encrypted but decryptable by the data owner). Other PETs exhibit similar characteristics. Often these technologies are developed with the explicit goal of enabling their analysis in juristictions different from the data creation (under e.g. GDPR). As such, the programme being led by two international organizations develops international standards to work in this context. The PETs are used ...
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AI For Good
AI for Good is a year-round digital platform of the United Nations, where AI innovators and problem owners learn, discuss and connect to identify practical AI solutions to advance the UN Sustainable Development Goals, SDGs. The impetus for organizing global summits that are action oriented, came from existing discourse in artificial intelligence (AI) research being dominated by research streams such as the Netflix Prize (improve the movie recommendation algorithm). AI for Good aims to bring forward Artificial Intelligence research topics that contribute towards more global problems, in particular through the Sustainable Development Goals. AI for Good came out of the AI for Good Global Summit 2020 which had been moved online in 2020 due to the COVID-19 Pandemic. AI for Good is organized by the Standardization Sector of ITU (ITU-T). Since moving online, AI for Good developed into three main programme streams: Learn, Build, and Connect. AI for Good also helps organize ITU's Global Stan ...
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ITU-WHO Focus Group On Artificial Intelligence For Health
The ITU-WHO Focus Group on Artificial Intelligence for Health (AI for Health) is an inter-agency collaboration between the World Health Organization and the ITU, which created a benchmarking framework to assess the accuracy of AI in health. This organization convenes an international network of experts and stakeholders from fields like research, practice, regulation, ethics, public health, etc, that develops guideline documentation and code. The documents address ethics, assessment/evaluation, handling, and regulation of AI for health solutions, covering specific use cases including AI in ophthalmology, histopathology, dentistry, malaria detection, radiology, symptom checker applications, etc. FG-AI4H has established an ad hoc group concerned with digital technologies for health emergencies, including COVID-19. All documentation is public. The idea for the Focus Group came out of the Health Track of the 2018 AI for Good Global Summit. Administratively, FG-AI4H was created by ITU ...
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Information Privacy
Information privacy is the relationship between the collection and dissemination of data, technology, the public expectation of privacy, contextual information norms, and the legal and political issues surrounding them. It is also known as data privacy or data protection. Data privacy is challenging since attempts to use data while protecting an individual's privacy preferences and personally identifiable information. The fields of computer security, data security, and information security all design and use software, hardware, and human resources to address this issue. Authorities Laws Authorities by country Information types Various types of personal information often come under privacy concerns. Cable television This describes the ability to control what information one reveals about oneself over cable television, and who can access that information. For example, third parties can track IP TV programs someone has watched at any given time. "The addition of any informati ...
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Data Science
Data science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract or extrapolate knowledge and insights from noisy, structured and unstructured data, and apply knowledge from data across a broad range of application domains. Data science is related to data mining, machine learning, big data, computational statistics and analytics. Data science is a "concept to unify statistics, data analysis, informatics, and their related methods" in order to "understand and analyse actual phenomena" with data. It uses techniques and theories drawn from many fields within the context of mathematics, statistics, computer science, information science, and domain knowledge. However, data science is different from computer science and information science. Turing Award winner Jim Gray imagined data science as a "fourth paradigm" of science ( empirical, theoretical, computational, and now data-driven) and asserted that "everything about sc ...
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MPEG
The Moving Picture Experts Group (MPEG) is an alliance of working groups established jointly by International Organization for Standardization, ISO and International Electrotechnical Commission, IEC that sets standards for media coding, including compression coding of audio compression (data), audio, video compression, video, graphics, and Compression of Genomic Sequencing Data, genomic data; and transmission and Container format (digital), file formats for various applications.John Watkinson, ''The MPEG Handbook'', p. 1 Together with Joint Photographic Experts Group, JPEG, MPEG is organized under ISO/IEC JTC 1/ISO/IEC JTC 1/SC 29, SC 29 – ''Coding of audio, picture, multimedia and hypermedia information'' (ISO/IEC Joint Technical Committee 1, Subcommittee 29). MPEG formats are used in various multimedia systems. The most well known older MPEG media formats typically use MPEG-1, MPEG-2, and MPEG-4 AVC media coding and MPEG-2 systems MPEG transport stream, transport streams an ...
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JPEG
JPEG ( ) is a commonly used method of lossy compression for digital images, particularly for those images produced by digital photography. The degree of compression can be adjusted, allowing a selectable tradeoff between storage size and image quality. JPEG typically achieves 10:1 compression with little perceptible loss in image quality. Since its introduction in 1992, JPEG has been the most widely used image compression standard in the world, and the most widely used digital image format, with several billion JPEG images produced every day as of 2015. The term "JPEG" is an acronym for the Joint Photographic Experts Group, which created the standard in 1992. JPEG was largely responsible for the proliferation of digital images and digital photos across the Internet, and later social media. JPEG compression is used in a number of image file formats. JPEG/Exif is the most common image format used by digital cameras and other photographic image capture devices; along with JPEG ...
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VCEG
The Video Coding Experts Group or Visual Coding Experts Group (VCEG, also known as Question 6) is a working group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with standards for compression coding of video, images, audio, and other signals. It is responsible for standardization of the "H.26x" line of video coding standards, the "T.8xx" line of image coding standards, and related technologies. Administratively, VCEG is the informal name of Question 6 (Visual, audio and signal coding) of Working Party 3 (Audiovisual technologies and intelligent immersive applications) of ITU-T Study Group 16 (Multimedia and related digital technologies). Its abbreviated title is ITU-T Q.6/SG16, or more simply, ITU-T Q6/16. The goal of VCEG is to produce ITU-T Recommendations (international standards) for video coding and image coding methods appropriate for conversational (e.g. videoconferencing and video telephony) and non-conversational (e.g., streaming, broadcast, file d ...
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ITU-T Study Group 16
The ITU-T Study Group 16 (SG16) is a statutory group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with multimedia coding, systems and applications, such as video coding standards. It is responsible for standardization of the "H.26x" line of video coding standards, the "T.8xx" line of image coding standards, and related technologies, as well as various collaborations with the World Health Organization, including on safe listing (H.870) accessibility of e-health (F.780.2), it is also the parent body of VCEG and various Focus Groups, such as the ITU-WHO Focus Group on Artificial Intelligence for Health. Administratively, SG16 is a statutory meeting of the World Telecommunication Standardization Assembly (WTSA), which creates the ITU-T Study Groups and appoints their management teams. The secretariat is provided by the Telecommunication Standardization Bureau (under Director Chaesub Lee). WTSA instructed ITU to hold the Global Standards Symposium as a part of ...
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Geneva
Geneva ( ; french: Genève ) frp, Genèva ; german: link=no, Genf ; it, Ginevra ; rm, Genevra is the List of cities in Switzerland, second-most populous city in Switzerland (after Zürich) and the most populous city of Romandy, the French-speaking part of Switzerland. Situated in the south west of the country, where the Rhône exits Lake Geneva, it is the capital of the Canton of Geneva, Republic and Canton of Geneva. The city of Geneva () had a population 201,818 in 2019 (Jan. estimate) within its small municipal territory of , but the Canton of Geneva (the city and its closest Swiss suburbs and exurbs) had a population of 499,480 (Jan. 2019 estimate) over , and together with the suburbs and exurbs located in the canton of Vaud and in the French Departments of France, departments of Ain and Haute-Savoie the cross-border Geneva metropolitan area as officially defined by Eurostat, which extends over ,As of 2020, the Eurostat-defined Functional Urban Area of Geneva was made up of 9 ...
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Homomorphic Encryption
Homomorphic encryption is a form of encryption that permits users to perform computations on its encrypted data without first decrypting it. These resulting computations are left in an encrypted form which, when decrypted, result in an identical output to that produced had the operations been performed on the unencrypted data. Homomorphic encryption can be used for privacy-preserving outsourced storage and computation. This allows data to be encrypted and out-sourced to commercial cloud environments for processing, all while encrypted. For sensitive data, such as health care information, homomorphic encryption can be used to enable new services by removing privacy barriers inhibiting data sharing or increase security to existing services. For example, predictive analytics in health care can be hard to apply via a third party service provider due to medical data privacy concerns, but if the predictive analytics service provider can operate on encrypted data instead, these priva ...
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ITU-T Study Group 17
The ITU-T Study Group 17 (SG17) is a statutory group of the ITU Telecommunication Standardization Sector (ITU-T) concerned with security. The group is concerned with a broad range of security-related standardization issues such as cybersecurity, security management, security architectures and frameworks, countering spam, identity management, biometrics, protection of personally identifiable information, and the security of applications and services for the Internet of Things (IoT). It is responsible for standardization of i.a. ASN.1 and X.509, it is also the parent body of the Focus Group on Quantum Information Technology (FG-QIT). The group is currently chaired by Heung Youl Youm of South Korea. Administratively, SG17 is a statutory meeting of the World Telecommunication Standardization Assembly (WTSA), which creates the ITU-T Study Groups and appoints their management teams. The secretariat is provided by the Telecommunication Standardization Bureau (under Director Chaesub L ...
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Secure Multi-party Computation
Secure multi-party computation (also known as secure computation, multi-party computation (MPC) or privacy-preserving computation) is a subfield of cryptography with the goal of creating methods for parties to jointly compute a function over their inputs while keeping those inputs private. Unlike traditional cryptographic tasks, where cryptography assures security and integrity of communication or storage and the adversary is outside the system of participants (an eavesdropper on the sender and receiver), the cryptography in this model protects participants' privacy from each other. The foundation for secure multi-party computation started in the late 1970s with the work on mental poker, cryptographic work that simulates game playing/computational tasks over distances without requiring a trusted third party. Note that traditionally, cryptography was about concealing content, while this new type of computation and protocol is about concealing partial information about data while comp ...
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