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ZENODO
Report . 2024
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2024
License: CC BY
Data sources: Datacite
ZENODO
Report . 2024
License: CC BY
Data sources: Datacite
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Free Software and AI openness: Overcoming challenges in the licensing world

Authors: Lasota, Lucas; Singhal, Niharika;

Free Software and AI openness: Overcoming challenges in the licensing world

Abstract

The convergence of AI and Free Software is briefly analysed in this paper from the perspective of licensing, especially considering the necessity to promote openness respecting the historical principles of software freedom. Some challenges in achieving openness in the licensing scheme of AI are highlighted. Inparticular, the uncoordinated growing proliferation of licences claiming to be “free and open source” but imposing extra limitations on software freedom may lead to licence incompatibility, a well-known challenge faced by the Free Software community.This paper clarifies why using licences to address behavioural and usage restrictions may affect distribution of control over AI technologies, and how the complexities of non-free licences in multi-source software development can affect compliance efforts.In conclusion, three recommendations are proposed:• Preserving openness in AI by safeguarding the four freedoms of software. Restrictions on software freedom disable control, transparency and oversight over technology. This results in a negative impact on people’s digital autonomy, distribution of powerin the society and ultimately the democracy.• Keeping licensing of AI technologies cohesive and interoperable with Free Software licences by avoiding licence proliferation, increasing legal interoperability and simplifying licence adoption.• Encouraging engagement with civil society actors in initiatives aimed to make AI more open, accessible, transparent and auditable.

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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