With the ascent of machine learning and its reliance on high quality data, there is a need for data agreements which facilitate data sharing both for data providers and data recipients and create a predictable path for training ML models. Recent agreements, such as the CDLA-Permissive-1.0, CDLA-Sharing-1.0, and the O-UDA-1.0, have made good strides towards these goals, but we believe recent developments in the law and the evolving needs of machine learning make it desirable to have an even simpler, more streamlined approach.
This new agreement, the whose use of which we hope will supersede its predecessors, the CDLA-Permissive-1.0 and the O-UDA-1.0, has been crafted with the following objectives in mind:
- A short, straightforward data agreement which enables data sharing and data innovation in a responsible way;
- The use of data under the agreement carries no obligation;
- The sharing of data under the agreement is operationally simple and requires nothing more than making available the text of the agreement;
- Training an ML model based on data under the agreement, even copyrighted data, creates no obligation under the agreement for the use or the distribution of the trained model or for the insights it generates;
- A data provider-friendly agreement, as the sharing of data under the agreement is designed to limit the liability of the data provider(s).