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Government by algorithm [1] (also known as algorithmic regulation, [2] regulation by algorithms, algorithmic governance, [3] [4] algocratic governance, algorithmic legal order or algocracy [5]) is an alternative form of government or social ordering where the usage of computer algorithms is applied to regulations, law enforcement, and generally any aspect of everyday life such as ...
Articles and categories about government by algorithm, which is also known as algorithmic regulation, regulation by algorithms, algorithmic governance, algorithmic legal order or algocracy. Subcategories
Algorithm certification involves auditing whether the algorithm used during the life cycle 1) conforms to the protocoled requirements (e.g., for correctness, completeness, consistency, and accuracy); 2) satisfies the standards, practices, and conventions; and 3) solves the right problem (e.g., correctly model physical laws), and satisfies the ...
In December 2018, Canada and France announced plans for a G7-backed International Panel on Artificial Intelligence, modeled on the International Panel on Climate Change, to study the global effects of AI on people and economies and to steer AI development. [53]
From Wikipedia, the free encyclopedia. Redirect page. Redirect to: Government by algorithm; Retrieved from " ...
Algorithmic regulation may refer to: Government by algorithm, use of algorithms in government; Regulation of algorithms, rules and laws for algorithms
In futurology, cyberocracy describes a hypothetical form of government that rules by the effective use of information. The exact nature of a cyberocracy is largely speculative as, apart from Project Cybersyn, there have been no cybercratic governments; however, a growing number of cybercratic elements can be found in many developed nations.
Automated decision-making involves using data as input to be analyzed within a process, model, or algorithm or for learning and generating new models. [7] ADM systems may use and connect a wide range of data types and sources depending on the goals and contexts of the system, for example, sensor data for self-driving cars and robotics, identity data for security systems, demographic and ...