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“We’ve had artificial-intelligence tools and bots since 2002, and we’ve had a team dedicated to machine learning since 2017,” Selena Deckelmann, Wikimedia’s chief technology officer, told me. “They’re extremely valuable for semiautomated content review, and especially for translations.

The key premise of algorithms is efficiency. Algorithms optimise data for decision-making that we previously did not have before. But humans are not efficient. We are messy and inherently flawed, which makes us human. We value serendipity, community and experiences, which may not be efficient but is impactful.

the Wikimedia Enterprise initiative, which launched in 2021. It offers paid, enterprise-grade APIs suitable for building commercial solutions on top of Wikipedia content. And Google is one of its first customers (the second is the Internet Archive).

Specific AI system regulations, such as the European AI Act or the AI Bill of Rights in the United States (both of which have yet to be adopted), may include rules that govern the development and management of AI training datasets. Other laws are also applicable. The Digital Services Act, recently adopted in the European Union, requires platforms t... See more

Licensing rules, technical measures, and regulations all interact in ways that alto -gether create a governance structure for AI training datasets. For example, stat -utory limitations on high-risk AI systems seek to impose behavioral constraints similar to those imposed by RAIL-type licenses

We’ve seen Wikipedia, Mozilla, Internet Archive, Electronic Frontier Foundation, Public Library of Science. These are infrastructure-type companies, but they’re not-for-profits.

As Luis Villa phrases it in his review of the paper, “”open” is not a magic bullet to the heart of power.”