ALL THINGS DATA by 1000ml
Predicting Legal Outcomes
Most law offices & legal professionals go through common or similar cases, when they work on a case they look for prior arguments, prior cases, and precedents, allowing an automatization process to be implemented since it makes it searchable and usable information. Today we discuss the art (or science) that goes into the automation of Predicting Legal Outcomes.
They use a sort of search tool and it’s generally only a keyword search tool, since someone with a lot of experience, will know that in each case what to look at, the specific set of keywords that is pretty unique and doesn’t usually happen in the rest of them. Of course, that other hand has some trouble since limiting to only those keywords you could lose relevant other information.
So when you need to know the exact keywords in order to search for precedent and prior cases. Imagine that there is the need to understand all of these details and information to really build a case up so that it’s possible to understand what people have said in the past, what’s worked and what hasn’t, these being the material facts of the case.
The other thing that you really can’t do without actual live debates and trials is to judge the strength of the argument, so this type of judging will obviously going to rely on the entirety of that package. In order to really understand and get to a point where there is confidence in an argument it really benefits everybody to, have sort of a score about it, so when there is an argument with a high degree of confidence, that there is the conviction that will or power up that case over the other side.
There’s an opportunity here to make it more scientific and that’s where we shine quite a lot in getting into the AI for legal decisions of courts and obviously also pushing the envelope and innovation in the world of witness readiness and witness prep.
In order to get to a world where you can build an AI program you’re going to have to build up your internal capabilities and knowledge because you’re dealing largely with unstructured texts, for example, images and video, those are definitely unstructured, but you can structure them by pre-processing in text. You can do the same, you can turn extreme, extremely large pieces of content, whether they are legal decisions.
Let’s cut through the jargon, myths and nebulous world of data, machine learning and AI. Each week we’ll be unpacking topics related to the world of data and AI with the awarding winning founders of 1000ML. Whether you’re in the data world already or looking to learn more about it, this podcast is for you.
