Anticipatory Governance
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Anticipatory Governance
Anticipatory profiling, is the practice used by the state to collect information and data about its citizens in order to assess events or behaviours in a predictable manner based on the knowledge gathered. Anticipatory governance is also a method of decision making that uses predictive measures to anticipate possible outcomes to then make decisions based on the data provided. Anticipatory governance is a system of governing that is made up of processes and institutions that rely on foresight and predictions to decrease risk and develop efficient methods to address events in their early conception or prevent them altogether.   History and applications Anticipatory governance is a concept that has been derived from terms of similar meaning, like forward engagement and forward deployment, which was a primary focus for decisions made by the North Atlantic Treaty Organization (NATO). More recently, anticipatory governance has become data oriented practice which allows citizens and ...
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NATO
The North Atlantic Treaty Organization (NATO, ; french: Organisation du traité de l'Atlantique nord, ), also called the North Atlantic Alliance, is an intergovernmental military alliance between 30 member states – 28 European and two North American. Established in the aftermath of World War II, the organization implemented the North Atlantic Treaty, signed in Washington, D.C., on 4 April 1949. NATO is a collective security system: its independent member states agree to defend each other against attacks by third parties. During the Cold War, NATO operated as a check on the perceived threat posed by the Soviet Union. The alliance remained in place after the dissolution of the Soviet Union and has been involved in military operations in the Balkans, the Middle East, South Asia, and Africa. The organization's motto is ''animus in consulendo liber'' (Latin for "a mind unfettered in deliberation"). NATO's main headquarters are located in Brussels, Belgium, while NATO ...
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Big Data
Though used sometimes loosely partly because of a lack of formal definition, the interpretation that seems to best describe Big data is the one associated with large body of information that we could not comprehend when used only in smaller amounts. In it primary definition though, Big data refers to data sets that are too large or complex to be dealt with by traditional data-processing application software. Data with many fields (rows) offer greater statistical power, while data with higher complexity (more attributes or columns) may lead to a higher false discovery rate. Big data analysis challenges include capturing data, data storage, data analysis, search, sharing, transfer, visualization, querying, updating, information privacy, and data source. Big data was originally associated with three key concepts: ''volume'', ''variety'', and ''velocity''. The analysis of big data presents challenges in sampling, and thus previously allowing for only observations and sampling. ...
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Impact Of Nanotechnology
The impact of nanotechnology extends from its medical, ethical, mental, legal and environmental applications, to fields such as engineering, biology, chemistry, computing, materials science, and communications. Major benefits of nanotechnology include improved manufacturing methods, water purification systems, energy systems, physical enhancement, nanomedicine, better food production methods, nutrition and large-scale infrastructure auto-fabrication. Nanotechnology's reduced size may allow for automation of tasks which were previously inaccessible due to physical restrictions, which in turn may reduce labor, land, or maintenance requirements placed on humans. Potential risks include environmental, health, and safety issues; transitional effects such as displacement of traditional industries as the products of nanotechnology become dominant, which are of concern to privacy rights advocates. These may be particularly important if potential negative effects of nanoparticles are ov ...
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Predictive Analytics
Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modeling, and machine learning that analyze current and historical facts to make predictions about future or otherwise unknown events. In business, predictive models exploit patterns found in historical and transactional data to identify risks and opportunities. Models capture relationships among many factors to allow assessment of risk or potential associated with a particular set of conditions, guiding decision-making for candidate transactions. The defining functional effect of these technical approaches is that predictive analytics provides a predictive score (probability) for each individual (customer, employee, healthcare patient, product SKU, vehicle, component, machine, or other organizational unit) in order to determine, inform, or influence organizational processes that pertain across large numbers of individuals, such as in marketing, credit risk assessment, fraud detecti ...
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Predictive Policing
Predictive policing is the usage of mathematics, predictive analytics, and other analytical techniques in law enforcement to identify potential criminal activity. A report published by the RAND Corporation identified four general categories predictive policing methods fall into: methods for predicting crimes, methods for predicting offenders, methods for predicting perpetrators' identities, and methods for predicting victims of crime. Methodology Predictive policing uses data on the times, locations and nature of past crimes to provide insight to police strategists concerning where, and at what times, police patrols should patrol, or maintain a presence, in order to make the best use of resources or to have the greatest chance of deterring or preventing future crimes. This type of policing detects signals and patterns in crime reports to anticipate if crime will spike, when a shooting may occur, where the next car will be broken into, and who the next crime victim will be. Algorith ...
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Data Collection
Data collection or data gathering is the process of gathering and measuring information on targeted variables in an established system, which then enables one to answer relevant questions and evaluate outcomes. Data collection is a research component in all study fields, including physical science, physical and social sciences, humanities, and business. While methods vary by discipline, the emphasis on ensuring accurate and honest collection remains the same. The goal for all data collection is to capture quality evidence that allows analysis to lead to the formulation of convincing and credible answers to the questions that have been posed. Data collection and validation consists of four steps when it involves taking a census and seven steps when it involves sampling. Regardless of the field of or preference for defining data (Quantitative method, quantitative or Qualitative method, qualitative), accurate data collection is essential to maintain research integrity. The selectio ...
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