Cambridge Analytica

Cambridge Analytica

Cambridge Analytica Ltd. (CA), previously known as SCL USA, was a British political consulting firm that came to prominence through the Facebook–Cambridge Analytica data scandal. It was founded in 2013, as a subsidiary of the private intelligence company and self-described "global election management agency" SCL Group by long-time SCL executives Nigel Oakes, Alexander Nix and Alexander Oakes, with Nix as CEO. Cambridge Analytica was hired by a variety of political actors, including the Trinidadian government in 2010 and the 2016 presidential campaigns of Ted Cruz and Donald Trump. The firm maintained offices in London, New York City, and Washington, D.C. The company closed operations in 2018 due to backlash from the scandal, although firms related to both Cambridge Analytica and its parent firm SCL still exist. == History == Cambridge Analytica was founded in 2013 as a subsidiary of the private intelligence company SCL Group, which describes itself as providing "data, analytics and strategy to governments and military organisations worldwide". The company was part of "an international web of companies" headed by the London-based SCL Group. Cambridge Analytica (SCL USA) was incorporated in January 2013 with its registered office being in Westferry Circus, London and consisting of just one staff member, director and CEO Alexander Nix (also appointed in January 2015). Nix was also the director of nine similar companies sharing the same registered offices in London, including Firecrest technologies, Emerdata and six SCL Group companies including "SCL elections limited". Nigel Oakes, known as the former boyfriend of Lady Helen Windsor, had founded the predecessor SCL Group in the 1990s, and in 2005 Oakes established SCL Group together with his brother Alexander Oakes and Alexander Nix; SCL Group was the parent company of Cambridge Analytica. Former Conservative minister and MP Sir Geoffrey Pattie was the founding chairman of SCL; Lord Ivar Mountbatten also joined Oakes as a director of the company. As a result of the Facebook–Cambridge Analytica data scandal, Nix was removed as CEO and replaced by Julian Wheatland before the company closed. Several of the company's executives were Old Etonians. The company's owners included several of the Conservative Party's largest donors such as billionaire Vincent Tchenguiz, former British Conservative minister Jonathan Marland, Baron Marland and the family of American hedge fund manager Robert Mercer. The company combined misappropriation of digital assets, data mining, data brokerage, and data analysis with strategic communication during electoral processes. While its parent SCL had focused on influencing elections in developing countries since the 1990s, Cambridge Analytica focused more on the western world, including the United Kingdom and the United States; CEO Alexander Nix has said CA was involved in 44 U.S. political races in 2014. In 2015, CA performed data analysis services for Ted Cruz's presidential campaign. In 2016, CA worked for Donald Trump's presidential campaign as well as for Leave.EU (one of the organisations campaigning in the United Kingdom's referendum on European Union membership). CA's role in those campaigns has been controversial and is the subject of ongoing inquiries in both countries. Political scientists question CA's claims about the effectiveness of its methods of targeting voters. == Data scandal == In March 2018, media outlets broke news of Cambridge Analytica's business practices. The New York Times and The Observer reported that the company had acquired and used personal data about Facebook users from an external researcher who had told Facebook he was collecting it for academic purposes. Shortly afterwards, Channel 4 News aired undercover investigative videos showing Nix boasting about using prostitutes, bribery sting operations, and honey traps to discredit politicians on whom it had conducted opposition research, and saying that the company "ran all of (Donald Trump's) digital campaign". In response to the media reports, the Information Commissioner's Office (ICO) of the UK pursued a warrant to search the company's servers. Facebook banned Cambridge Analytica from advertising on its platform, saying that it had been deceived. On 23 March 2018, the British High Court granted the ICO a warrant to search Cambridge Analytica's London offices. As a result, Nix was suspended as CEO, and replaced by Julian Wheatland. The personal data of up to 87 million Facebook users were acquired via the 270,000 Facebook users who used a Facebook app created by Aleksandr Kogan called "This Is Your Digital Life". This was a personality profiling app and asked simple personality questions similar to other Facebook quizzes. Kogan was a scientist and psychologist, also being an employed lecturer for the University of Cambridge from 2012 to 2018. Alexander Nix claimed they had close to five thousand data points on each person who participated. They also gathered information through other data brokers ending with them acquiring millions of data points from American citizens. Kogan's app exploited a feature of Facebook's Graph API (version 1.0), which permitted any third-party app to access not only the app user's data, but also the full profile data of all of that user's Facebook friends, without those friends' knowledge or consent. This platform-wide design was available to all developers and was used by tens of thousands of apps; Facebook CEO Mark Zuckerberg later told the House Energy and Commerce Committee that the company was auditing "tens of thousands" of apps that had had access to large amounts of user data. Because the average Facebook user at the time had approximately 300 friends, the 270,000 users who installed Kogan's app yielded data on up to 87 million people. Facebook deprecated the friends-data API in April 2014 and shut it down entirely in April 2015, but data already collected by apps remained in developers' possession. Kogan passed this data to Cambridge Analytica, breaching Facebook's terms of service. On 1 May 2018, Cambridge Analytica and its parent company SCL filed for insolvency proceedings and closed operations. Alexander Tayler, a former director for Cambridge Analytica, was appointed director of Emerdata on 28 March 2018. Rebekah Mercer, Jennifer Mercer, Alexander Nix and Johnson Chun Shun Ko, who has links to American businessman Erik Prince, are in leadership positions at Emerdata. The Russo brothers are producing an upcoming film on Cambridge Analytica. In 2019 the Federal Trade Commission filed an administrative complaint against Cambridge Analytica for misuse of data. In 2020, the British Information Commissioner's Office closed a three-year inquiry into the company, concluded that Cambridge Analytica was "not involved" in the 2016 Brexit referendum and found no additional evidence for Russia's alleged interference during the campaign. US sensitive polling and election data, however, were passed to Russian Intelligence via a Cambridge Analytica contractor Sam Patten, Trump campaign manager Paul Manafort, and Russian agent Konstantin Kilimnik, who was indicted during the affair. Publicly, parent company SCL Group called itself a "global election management agency", Politico reported it was known for involvement "in military disinformation campaigns to social media branding and voter targeting". SCL gained work on a large number of campaigns for the US and UK governments' war on terror advancing their model of behavioral conflict during the 2000s. SCL's involvement in the political world has been primarily in the developing world where it has been used by the military and politicians to study and manipulate public opinion and political will. Slate writer Sharon Weinberger compared one of SCL's hypothetical test scenarios to fomenting a coup. Among the investors in Cambridge Analytica were some of the Conservative Party's largest donors such as billionaire Vincent Tchenguiz, former Conservative minister Jonathan Marland, Baron Marland, Roger Gabb, the family of American hedge fund manager Robert Mercer, and Steve Bannon. A minimum of 15 million dollars has been invested into the company by Mercer, according to The New York Times. Bannon's stake in the company was estimated at 1 to 5 million dollars, but he divested his holdings in April 2017 as required by his role as White House Chief Strategist. In March 2018, Jennifer Mercer and Rebekah Mercer became directors of Emerdata limited. In March 2018 it became public by Christopher Wylie, that Cambridge Analytica's first activities were founded on a data set, which its parent company SCL bought 2014 from a company named Global Science Research founded by Aleksandr Kogan and his team present across the world who worked as a psychologist at Cambridge. During Boris Johnson's tenure as foreign secretary, the Foreign Office sought advice from Cambridge Analytica and Boris Johnson had a meeting with Alexander N

Behavior informatics

Behavior informatics (BI) is the informatics of behaviors so as to obtain behavior intelligence and behavior insights. BI is a research method combining science and technology, specifically in the area of engineering. The purpose of BI includes analysis of current behaviors as well as the inference of future possible behaviors. This occurs through pattern recognition. Different from applied behavior analysis from the psychological perspective, BI builds computational theories, systems and tools to qualitatively and quantitatively model, represent, analyze, and manage behaviors of individuals, groups and/or organizations. BI is built on classic study of behavioral science, including behavior modeling, applied behavior analysis, behavior analysis, behavioral economics, and organizational behavior. Typical BI tasks consist of individual and group behavior formation, representation, computational modeling, analysis, learning, simulation, and understanding of behavior impact, utility, non-occurring behaviors, etc. for behavior intervention and management. The Behavior Informatics approach to data utilizes cognitive as well as behavioral data. By combining the data, BI has the potential to effectively illustrate the big picture when it comes to behavioral decisions and patterns. One of the goals of BI is also to be able to study human behavior while eliminating issues like self-report bias. This creates more reliable and valid information for research studies. == Behavior == From an Informatics perspective, a behavior consists of three key elements: actors (behavioral subjects and objects), operations (actions, activities) and interactions (relationships), and their properties. A behavior can be represented as a behavior vector, all behaviors of an actor or an actor group can be represented as behavior sequences and multi-dimensional behavior matrix. The following table explains some of the elements of behavior. Behavior Informatics takes into account behavior when analyzing business patterns and intelligence. The inclusion of behavior in these analyses provides prominent information on social and driving factors of patterns. == Applications == Behavior Informatics is being used in a variety of settings, including but not limited to health care management, telecommunications, marketing, and security. Behavior Informatics provides a manner in which to analyze and organize the many aspects that go into a person's health care needs and decisions. When it comes to business models, behavior informatics may be utilized for a similar role. Organizations implement behavior informatics to enhance business structure and regime, where it helps moderate ideal business decisions and situations.

Elasticity (computing)

In computing, elasticity is defined as "the degree to which a system is able to adapt to workload changes by provisioning and de-provisioning resources in an autonomic manner, such that at each point in time the available resources match the current demand as closely as possible". Elasticity is a defining characteristic that differentiates cloud computing from previously proposed distributed computing paradigms, such as grid computing. The dynamic adaptation of capacity, e.g., by altering the use of computing resources, to meet a varying workload is called "elastic computing". In the world of distributed systems, there are several definitions according to the authors; some consider the concepts of scalability a sub-part of elasticity, others as being distinct. == Purpose == Elasticity aims to match the amount of resources allocated to a service with the amount of resources it actually requires, avoiding over- or under-provisioning. Over-provisioning, i.e., allocating more resources than required, should be avoided as it may incur extra costs (monetary, energy, operational, etc.) for unused or underutilized resources. For example, if a website is over-provisioned with two cloud computing resources to handle current demand that only requires one resource, the costs of maintaining the second resource would effectively be wasted. Under-provisioning, i.e., allocating fewer resources than required, must be avoided; otherwise, the service cannot serve its users with a good service. For example, under-provisioning a website may make it seem slow or unreachable, because not enough resources have been allocated to meet current demand. == Example == Elasticity can be illustrated through an example of a service provider who wants to run a website on the cloud. At moment t 0 {\displaystyle t_{0}} , the website is unpopular and a single machine is sufficient to serve all users. At moment t 1 {\displaystyle t_{1}} , the website suddenly becomes popular, and a single machine is no longer sufficient to serve all users. Based on the number of web users simultaneously accessing the website and the resource requirements of the web server, ten machines are needed. An elastic system should immediately detect this condition and provision nine additional machines from the cloud to serve all users responsively. At time t 2 {\displaystyle t_{2}} , the website becomes unpopular again. The ten machines currently allocated to the website are mostly idle and a single machine would be sufficient to serve the few users who are accessing the website. An elastic system should immediately detect this condition and deprovision nine machines, releasing them to the cloud. == Problems == === Resource provisioning time === Resource provisioning takes time. A cloud virtual machine (VM) can be acquired at any time by the user; however, it may take up to several minutes for the acquired VM to be ready to use. The VM startup time is dependent on factors such as image size, VM type, data center location, number of VMs, etc. Cloud providers have different VM startup performance. This implies that any control mechanism designed for elastic applications must consider the time needed for the resource provisioning actions to take effect. === Monitoring elastic applications === Elastic applications can allocate and deallocate resources on demand for specific application components. This makes cloud resources volatile, and traditional monitoring tools which associate monitoring data with a particular resource, such as Ganglia or Nagios, are no longer suitable for monitoring the behavior of elastic applications. For example, during its lifetime, a data storage tier of an elastic application might add and remove data storage VMs due to cost and performance requirements, varying the number of used VMs. Thus, additional information is needed in monitoring elastic applications, such as associating the logical application structure over the underlying virtual infrastructure. This in turn generates other problems, such as data aggregation from multiple VMs towards extracting the behavior of the application component running on top of those VMs, as different metrics may need to be aggregated differently (e.g., CPU usage could be averaged, network transfer might be summed up). === Stakeholder requirements === When deploying applications in cloud infrastructures (IaaS/PaaS), stakeholder requirements need to be considered in order to ensure that elastic behavior meets stakeholder needs. Traditionally, the optimal trade-off between cost and quality or performance is considered; however, for real world cloud users, requirements regarding elastic behavior are more complex and target multiple dimensions of elasticity (e.g., SYBL). === Multiple levels of control === Cloud applications vary in type and complexity, with multiple levels of artifacts deployed in layers. Controlling such structures must take into consideration a variety of issues. For multi-level control, control systems need to consider the impact lower level control has upon higher level ones, and vice versa (e.g., controlling virtual machines, web containers, or web services in the same time), as well as conflicts that may appear between various control strategies from various levels. Elastic strategies on in cloud computing can take advantage of control-theoretic methods (e.g., predictive control has been experimented in cloud computing scenarios by showing considerable advantages with respect to reactive methods). One approach to multi-level elastic clouc control is rSYBL.

Dimensions CM

Dimensions CM is a software change and configuration management product developed by OpenText Corporation. It includes revision control, change, build and release management capabilities. Since 2014 (v14.1) Dimensions CM includes PulseUno module providing Code review and Continuous integration capabilities. Starting with the version 14.5.2 (2020) it can also serve as a binary repository manager. == History == Previous product names: PCMS Dimensions (SQL Software) PVCS Dimensions (Merant, Intersolv)

MyPoolin

Mypoolin is a mobile peer-to-peer and group payment application. Their software allows the settling of debts and group-expenditure for events and activities. The software utilizes Unified Payment Interface of India to collect and settle daily expenses with friends. Users can also plan and pay together for group-gifting, movies, vacations, concerts, events, and parties. == Service == Mypoolin is a mobile payment provider that lets its users transfer money to other users via their mobile number. A user can create an account by verifying an OTP code which is sent to his mobile phone. It also allows the users to track their friends’ activities on the app. == History == Mypoolin was founded by Rohit Taneja (IIT Delhi) and Ankit Singh (FMS Delhi) in 2014 as a medium to aggregate money for various purposes in a hassle free and quick manner. Prior to the mobile app launch, Mypoolin was initially launched as a web application. == Funding == Mypoolin has been seed funded by angel investors. As winners of the QPrize 2015, Mypoolin jointly received an additional funding of $250,000 from Qualcomm Ventures. == Growth == Mypoolin reached INR 10 lakhs in revenue during its first four months of the web application launch, and was listed in the "Top ten free apps" in its category within the first 5 days of the Android app launch. It was one of the Top 50 start-ups in Asia at the Echelon Asia Summit held in Singapore. And among the top 3 start-ups in 1776 Cup Challenge 2016. Apple Inc also featured the app on their app store in India. == Features == Users are able to collect and share money on the app for daily uses like movies, events and trips. The money collected can then be redeemed in the form of an online voucher redeemable across several e-commerce sites. The amount can be redeemed also in the form of an offline debit card delivered to the address or in the form of a wire transfer. == Media coverage == Mypoolin was featured in The Economic Times and The Hindu Business Line after winning the Qualcomm Ventures' QPrize 2015. Digit magazine featured them recently as the app of the week. The app has mostly grown organically so far in the Indian urban millennial space.

Exercism

Exercism is an online, open-source, free coding platform that offers code practice and mentorship on 77 different programming languages. == History == Software developer Katrina Owen created Exercism while she was teaching programming at Jumpstart Labs. The platform was developed as an internal tool to solve the problem of her own students not receiving feedback on the coding problems they were practicing. Katrina put the site publicly online and found that people were sharing it with their friends, practicing together and giving each other feedback. Within 12 months, the site had organically grown to see over 6,000 users had submitted code or feedback, and hundreds of volunteers contribute to the languages or tooling on the platform. In 2016, Jeremy Walker joined as co-founder and CEO. In July 2018, the site was relaunched with a new design and centered around a formal mentoring mode, at which point Katrina stepped back from day-to-day involvement. == Product == In the past, the website differed from other coding platforms by requiring students to download exercises through a command line client, solve the code on their own computers then submit the solution for feedback, at which point they can also view other's solutions to the same problem. Since its second relaunch in 2021, solutions can be edited and submitted through a web editor, though the command line client remains available. Exercism has tracks for 74 programming languages. Among the notable languages taught: ABAP, C, C#, C++, CoffeeScript, Delphi, Elm, Erlang, F#, Gleam, Go, Java, JavaScript, Julia, Kotlin, Objective-C, PHP, Python, Raku, Red, Ruby, Rust, Scala, Swift, and V (Vlang). In 2023, the site launched a "12 in 23" challenge for users to learn the basics of 12 different languages - one per month in 2023. == Open source == The Exercism codebase is open source. In April 2016, it consisted of 50 repositories including website code, API code, command-line code and, most of all, over 40 stand-alone repositories for different language tracks. As of February 2024 Exercism has 14,344 contributors, maintains 366 repositories, and 19,603 mentors.

Open Data Center Alliance

opendatacenteralliance.org appears to have been closed down. The Open Data Center Alliance is an independent organization created in Oct. 2010 with the assistance of Intel to coordinate the development of standards for cloud computing. Approximately 100 companies, which account for more than $50bn of IT spending, have joined the Alliance, including BMW, Royal Dutch Shell and Marriott Hotels. "The Alliance's Cloud 2015 vision is aimed at creating a federated cloud where common standards will be laid down for those in the hardware and software arena." == Usage Model Roadmap == The organization sees a growing need for solutions developed in an open, industry-standard and multivendor fashion, and has thus created a usage model roadmap featuring 19 prioritized usage models. The usage models provide detailed requirements for data center and cloud solutions, and will include detailed technical documentation discussing the requirements for technology deployments. To further its roadmap development, the steering committee established five initial technical workgroups in the areas of infrastructure, management, regulation & ecosystem, security and services. The organization delivered a 0.50 usage model roadmap to Open Data Center Alliance technical workgroups in Oct. 2010, and delivered a full 1.0 roadmap for public use in June 2011. == Membership == The steering committee consists of BMW, Capgemini, China Life, China Unicom Group, Deutsche Bank, JPMorgan Chase, Lockheed Martin, Marriott International, Inc., National Australia Bank, Royal Dutch Shell, Terremark and UBS. Other members include AT&T, CERN, eBay, Logica, Motorola Mobility Inc. and Nokia. "The demands on the IT organisations are coming at such an alarming rate that there are many, many different solutions being developed today that maybe don't work with each other. We need one voice, one road map, so that companies are able to say to manufacturers here is a clear vision of what they should be developing their product to do." says Marvin Wheeler, of Terremark, chairman of the Alliance. "While it's unclear how successful this alliance will be, it is at least shedding the spotlight on cloud interoperability, a big emerging issue," said Larry Dignan of ZDNet.