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Regulation of algorithms, or algorithmic regulation, is the creation of laws, rules and public sector policies for promotion and regulation of algorithms, particularly in artificial intelligence and machine learning. [1] [2] [3] For the subset of AI algorithms, the term regulation of artificial intelligence is used.
Regulation is now generally considered necessary to both encourage AI and manage associated risks. [19] [20] [21] Public administration and policy considerations generally focus on the technical and economic implications and on trustworthy and human-centered AI systems, [22] although regulation of artificial superintelligences is also ...
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 ...
It covers all types of AI across a broad range of sectors, with exceptions for AI systems used solely for military, national security, research and non-professional purposes. [5] As a piece of product regulation, it does not confer rights on individuals, but regulates the providers of AI systems and entities using AI in a professional context. [6]
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 ...
Current research around algorithmic transparency interested in both societal effects of accessing remote services running algorithms., [4] as well as mathematical and computer science approaches that can be used to achieve algorithmic transparency [5] In the United States, the Federal Trade Commission's Bureau of Consumer Protection studies how ...
The Support Threshold is 30%, Confidence Threshold is 50%. The Table on the left is the original unorganized data and the table on the right is organized by the thresholds. In this case Item C is better than the thresholds for both Support and Confidence which is why it is first. Item A is second because its threshold values are spot on.
Regulation of algorithms, rules and laws for algorithms Topics referred to by the same term This disambiguation page lists articles associated with the title Algorithmic regulation .