Add RAI statement

README.md

@@ -39,6 +39,30 @@ Example here.
 
 FAQ.
 
+## Responsible AI Transparency Documentation
+
+An AI system includes not only the technology, but also the people who will use it, the people who will be affected by it, and the environment in which it is deployed.
+Creating a system that is fit for its intended purpose requires an understanding of how the technology works, its capabilities and limitations, and how to achieve the best performance.
+Microsoft has a broad effort to put our AI principles into practice.
+To find out more, see [Responsible AI principles from Microsoft](https://www.microsoft.com/en-us/ai/responsible-ai).
+
+### Use of this code
+Our goal in publishing this code is
+(1) to facilitate reproducibility of our paper and
+(2) to support and accelerate further research into foundation model for atmospheric forecasting.
+This code has not been developed nor tested for non-academic purposes and hence should not be used as such.
+
+### No guarantees about quality of predictions
+Although Aurora was trained to accurately predict future weather and air pollution,
+Aurora is based on neural networks, which means that there are no strict guarantees that predicts will also be accurate.
+Altering the input to Aurora, providing a sample that was not in the training set,
+or even providing a unlucky sample that was in the training set may result in arbitrarily poor predictions.
+
+### Data
+The models included in the code have been trained on a variety of publicly available data.
+A description of all data, including download links, can be found in [Supplementary C of the paper](https://arxiv.org/pdf/2405.13063).
+
+*Note:* The documentation included in this file is for informational purposes only and is not intended to supersede the applicable license terms.
 
 ## Developing Locally