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Daily links from Cory Doctorow

Aug 18, 2023 - pluralistic.net
The article discusses the concept of "openwashing" in the context of AI, where large AI companies portray themselves as ethical and committed to openness to avoid regulation and criticism. The author argues that the term "open" in "open AI" is misleading, as it does not promote the transparency, reusability, and extensibility associated with open-source software. Instead, it serves as a tool for these companies to create a two-tier system where they enjoy broad freedom while the users only have the ability to understand how the software works. The author also criticizes the notion that "open AI" promotes safety through auditability, arguing that transparency alone does not guarantee safety without the establishment of auditing institutions.

The article also highlights the exploitation of the "open" narrative by the AI industry to resist regulation, arguing that the "open" projects that lawmakers value do not deliver a level playing field, competition, innovation, and democratization. The author suggests that "open AI" is best understood as "free product development" for large AI companies, conducted by developers who are unable to escape these giants' proprietary compute silos and opaque training corpuses. The author concludes by suggesting that truly open AI projects, such as those by EleutherAI and some academic institutions, are overshadowed by the dominant industry players.

Key takeaways:

  • The term "Open AI" is often misleading, as it is used by large AI companies to evade regulation and neutralize critics, while their products are neither "open," "artificial," nor "intelligent."
  • Openwashing is a new kind of -washing, where capital cloaks itself in liberatory, progressive values, while still serving as a force for extraction, exploitation, and political corruption.
  • Open AI is often used as a wordgame that exploits the malleability of "open," but also the ambiguity of the term "AI".
  • Open AI is best understood as "free product development" for large, well-capitalized AI companies, conducted by tinkerers who will not be able to escape these giants' proprietary compute silos and opaque training corpuses.
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