Building Open-Source AI

MCML Authors

Stefan Feuerriegel

Prof. Dr.

Principal Investigator

Artificial Intelligence in Management

Abstract

Artificial intelligence (AI) drives innovation across society, economies and science. We argue for the importance of building AI technology according to open-source principles to foster accessibility, collaboration, responsibility and interoperability.<br>The computer science community has a long tradition of embracing open-source principles. However, companies increasingly restrict access to AI innovations. An example is OpenAI, which was founded to make scientific research openly available but which eventually restricted access to research findings. Although such a strategy reflects a company’s legitimate incentive to obtain financial returns, such protection increases concentration of power, restricting access to AI technology. Further down the road, concentrated power could lead to growing inequality in AI research, education and public use. Here we discuss why proprietary AI technology should be complemented by open-source AI across the essential components for building AI technology: datasets, source codes and models.

article

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Nature Computational Science

3.11. Oct. 2023.

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Authors

Y. R. Shrestha • G. von Krogh • S. Feuerriegel

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Links

DOI

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Research Area

 A1 | Statistical Foundations & Explainability