DIANNA
Deep Insight And Neural Network Analysis, DIANNA is the only Explainable AI, XAI library for scientists supporting Open Neural Network Exchange, ONNX - the de facto standard models format.
The goal of this project was to develop a tool that distills the number of obligations contained in each and every item of European law ever adopted in the EU’s history (some 180,000 acts adopted from 1952-2023). Since existing studies on EU regulation only count the number of laws adopted without accounting for their actual contents, a more fine grained measurement of the number of obligations specified in EU law greatly advances the debate. In other words, existing research has used pretty bad proxies for measuring regulatory density.
Using this tool, developments over time can be observed, as well as between policy areas. One key finding (which has been outlined in two papers that are still under review) is that the number of EU laws has steadily gone down over the past 30 years, while the number of obligations rises consistently. This finding advances the debate in itself, in addition to the measurement which allows for many more fine-grained and large-scale analyses of the development of EU regulation.
This project specified four objectives:
The target audience – for the time being – is political scientists specializing in EU affairs. Only once more research has been carried out using the collected data (or the tool) as a source, communication to the general public would be an obvious next step.
Explainable AI tool for scientists
Discovering new patterns in Dutch court decisions
Deep Insight And Neural Network Analysis, DIANNA is the only Explainable AI, XAI library for scientists supporting Open Neural Network Exchange, ONNX - the de facto standard models format.