In a recent tweet, Ed Walters, one of the founders of Fastcase remarked:
To gain an understanding of how we got here, and why this time around, we’re finally seeing real innovation in legal research, you think back to the early ‘90s when the first websites came online. Not only were websites hideously ugly and clumsy, but they were flat and one-dimensional — digital versions of their analog counterparts like the billboard or the magazine ad. It wasn’t until nearly a decade later that the technology emerged to make websites interactive platforms for self-publishing, social interaction and sharing.
Legal research followed a similar pattern. For forty years, lawyers relied on LEXIS and Westlaw for computerized research needs. Yet all these systems did was automate the manual search tools – like hard-copy Shepards’ and Decennial Digests and Case Law Reporters – that lawyers of my generation were trained on back in law school. Even now in 2015, one of the metrics for evaluating a legal research tool’s utility is whether it provides pagination from case law reporters — hard copy volumes that have been published the same way for two centuries and that no one reads anymore!
In the late ’90s, the web opened the door to a new generation of legal research – with products like Fastcase, Versuslaw and more recently, Google Scholar . These new products made legal research more affordable and accessible (fun fact: when I started my firm, LEXIS costs $600/month. I couldn’t afford it so used the law library) and finally breached the chokehold that the WEXIS duopoly had maintained for a century. But through early versions of Fastcase and Scholar were significantly cheaper than their predecessors, they were still one-dimensional in that they automated legal research rather than innovated it.
On the heels of low cost legal research came the research analytics craze . Now, instead of trying to forecast the future based on opaque precedent, lawyers can access data on judicial rulings, opposing counsel’s case record and how long it takes for case to wind its way through a particular court. Analytics are cool – and are fast becoming an integral part of legal research portfolio – but until analytics become “smarter” through application of AI or predictive coding, I don’t view data analytics as innovation but rather, an automation of what lawyers were clumsily doing already (if you were ever an associate at a law firm who had to track regulatory developments on a spreadsheet, you know what I am talking about).
Subsequent attempts at innovation in legal research though laudable for effort, fell flat. I have to confess that I didn’t get all of the hoopla around the joint Ravel Law /Harvard Law School cooperative project to scan the Harvard Library and make it accessible online when I could already find most of those cases on Google Scholar for free. Likewise, I can’t say that I was enamored with Casetext’s original business model to crowdsource legal research by inviting lawyers to post comments and notes alongside cases in the Casetext data base because users had no incentive to post quality analysis on someone else’s platform for free .
As the saying goes, the wheels of justice grind slowly – and the wheels of legal research innovation even more, stifled by the WEXIS duopoly and lawyers’ fealty to precedent. Yet, finally we’re moving forward – as is evidenced by some supercool developments by Casetext, that I’ll review in Part II of this post.