“AI” has become an ever-present marketing buzzword in many sectors, not least of which in the legal arena. Machine learning applications are promising to deliver remarkably accurate software and data solutions while downplaying the critical intersection with the human component. Itai Gurari discusses and illustrates his approach for applying AI to the delivery of accurate legal research by having a human in the loop who is continuously iterating on the technology. In this scenario, the users can rely on a person whenever the problem gets too hard and the technology starts to fail, rather than on an overarching one-size-fits-all machine learning solution.
Legal AI pioneer Itai Gurari’s article is a commentary and a lessons learned that is critical to our communities of best practice as we seek to effectively assess both the promise and significant drawbacks of artificial intelligence and machine learning in the context of the legal sector. As Gurari clearly articulates, building reliably intelligent legal software requires more than just the application of the latest trendy tools. It requires building systems that are robust and that respect the use cases for which they are designed.