A data science team is developing a proprietary fraud detection model that will be a core component of a commercial SaaS product. The team intends to use a large, publicly available dataset for training. They must select a dataset with a license that does not obligate them to release the source code of their derivative model or the enveloping application. Which of the following data licenses would pose the most significant legal risk to the company's goal of keeping its model and application proprietary?
The correct answer is Creative Commons Attribution-ShareAlike (CC BY-SA). The 'ShareAlike' (SA) provision is a 'copyleft' clause, which mandates that any derivative works must be distributed under the same or a compatible license. In the context of machine learning, a model trained on data licensed under CC BY-SA could be legally interpreted as a derivative work. This would create a significant legal risk, potentially forcing the company to release its proprietary model under the same CC BY-SA terms, thereby compromising its commercial strategy.
Apache License 2.0 is a permissive license that allows for use in proprietary, commercial works without a reciprocal 'ShareAlike' obligation. It requires attribution and notice of changes but does not compel the derivative work to be open-sourced.
Creative Commons Public Domain Dedication (CC0) places the data in the public domain, waiving all copyright and related rights. This license imposes no restrictions and is ideal for commercial use, posing no risk.
Creative Commons Attribution (CC BY) is a permissive license that only requires attribution to the original creator. It allows for commercial use and the creation of derivative works without a 'ShareAlike' requirement, so it does not pose the same risk as CC BY-SA.
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