The use of artificial intelligence otherwise shortened as AI and big data to collectively make up data science is a new concept in legal services that is also transforming the delivery of legal advice. These features, which can also be referred to as legal analytics aim to bolster the efficiency of tasks that have been cumbersome to execute in the past, and mines loads of data to identify insights that were previously unheard of.
These are some of the programs that Zuka, an industry-driven higher education in Data Science startup based in Nairobi promises to deliver. The firm, which was founded a couple of months ago by Victor Mutua, who also serves as its Director, mainly focuses on data analytics, machine learning, and AI has been offering classes that lean towards industry needs and standards, as well as personalized career services by partners.
“In a first of its kind in Africa, Zuka is Launching a Legal Data Science program. Lawyers have traditionally competed by combining two key skills: legal research and reasoning. But now there’s a third leg to the law practice stool. Legal Analytics enables lawyers to gain a critical advantage in the business and practice of law. Zuka will be helping lawyers and firms in their Data Strategy,” said Director Mutua.
Zuka aims to make legal analytics mainstream in the Kenyan space. A data-based approach to addressing legal issues, such as whether a complaint can develop to lawsuits, improves speed and efficiency of handling cases, unlike archaic practices that involve a team of lawyers and analysts that examine court documents and records to make an informed legal decision. The latter takes months or years to complete. A data-based approach that leverages powerful algorithms could extract relevant text and present it to analysts.
Possibly, the course will mark a departure from legal practices that have been slow to adopting data-based systems for their day to day operations. However, it is inevitable that in the digital era where data is the new oil, legal institutions that fail to take advantage of the space will be unable to match the capabilities of those that will do so.
This just sounds like basic research, not data science. There are too many uncontrollable variables to draw out any concrete findings.
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