In recent news, Thomson Reuters has announced a new Westlaw Edge tool that will use artificial intelligence to track legislation and predict the likelihood that a bill will pass. Furthermore, the tool will also readily identify the industries that new bills would likely impact.
The artificial intelligence was created by a New York AI company called Skopos Labs. Skopos Labs regularly predicts the impact of policymaking on companies and markets. The tool is designed to use at least 250 internal and external factors that will ultimately generate a “probability of enactment” score for each bill. The internal factors are based on the current makeup of the house and senate, other political variables, and the president that is currently in office, etc. Some of the external factors the tool considers are natural disasters and GDP.
Now that we’ve walked through the nitty-gritty, are you ready for a translation? To put it into simpler terms, this tool combines the developed AI with Westlaw’s historical database to predict the law’s likelihood of passing, and if it does, what companies will be affected and how much. There are several goals for this tool, one of which is to give lawyers a better understanding of how certain changes in the legislature will affect companies, clients, agencies, and industries as a whole. As you can imagine, this tool doesn’t just benefit lawyers, it benefits the companies. With this tool, companies will be able to track former and future legislative changes across the country and in their home states, giving them an opportunity to make more educated plans about the future direction of the company.
As you can probably tell, if this artificial intelligence is truly as capable as we’re told, it will be groundbreaking for the legal world. Lawyers across the nation will now have a tool that will help them to make better plans and adjustments to benefit their client’s future. Skypos labs are continuing to work with third party companies to refine the technology, however, there is currently not a set date for its release.