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Rethinking Open Source Generative AI: Open-Washing and the EU AI Act
⚡FAccT'24 paper⚡ Liesenfeld, Andreas, and Mark Dingemanse. 2024.
Openness is key for fundamental research, for fostering critical computational literacy, and for making informed choices for or against deployment of instruction-tuned LLM architectures. Open alternatives provide ways to build reproducible workflows, chart resource costs, and lessen reliance on corporate whims. However, openness does make original research possible, including efforts to build reproducible workflows and understand the fundamentals of instruction-tuned LLM architectures.
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