“Code is Law” – three famous words of Professor Lawrence Lessig back in 1999, when the Internet as the first important “cyberspace” emerged. This raised fundamental questions about how Code will impact our legal environment. Since then IT has further moved into our lives and now eventually reaches out to the legal profession. Major questions raised since then are still valid. Apart from fundamental questions how to effectively regulate Code, the legal profession needs to position itself: Shall we embrace IT, shall we avoid it, or just wait and see?
Smart text mining is a critical and meanwhile established tool in the tool-box of modern law firms. Out of the box mining requires a lot of training of statistic AI algorithms. A semantic layer in law firms’ text mining approach could unlock a huge step forward but requires more work on the user interface. Here is a wish-list to the semantic AI community from a law firm’s perspective.
I will introduce the concept of 'Semantic AI', which is based on a fusion of NLP, machine learning (ML) and semantic knowledge graphs. We will take a look at two concrete use cases: How to improve ML-based classifiers for legal documents with semantic enrichment. How to combine various entity extraction methods, partly based on ML, to identify complex rules and restrictions from legal documents.