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.
The regulation of artificial intelligence refers to the development of public sector policies and laws for promoting and regulating artificial intelligence (AI). It is part of the broader regulation of algorithms. The regulatory and policy landscape for AI is an emerging issue in jurisdictions worldwide, including for international organizations without direct enforcement power like the IEEE or the OECD.
Algorithmic curation is the selection of online media by recommendation algorithms and personalized searches. Examples include search engine and social media products such as the Twitter feed, Facebook's News Feed, and the Google Personalized Search. Curation algorithms are typically proprietary or "black box", leading to concern about algorithmic bias and the creation of filter bubbles.
Algorithmic radicalization is the concept that recommender algorithms on popular social media sites such as YouTube and Facebook drive users toward progressively more extreme content over time, leading to them developing radicalized extremist political views. Algorithms record user interactions, from likes/dislikes to amount of time spent on posts, to generate endless media aimed to keep users engaged. Through echo chamber channels, the consumer is driven to be more polarized through preferences in media and self-confirmation. Algorithmic radicalization remains a controversial phenomenon as it is often not in the best interest of social media companies to remove echo chamber channels. To what extent recommender algorithms are actually responsible for radicalization remains controversial; studies have found contradictory results as to whether algorithms have promoted extremist content.