Roland Vogl is the executive director and lecturer in law for the Stanford Program in Law, Science & Technology, and the co-founder and executive director of CodeX – The Stanford Center for Legal Informatics.

More than ever before, lawyers in the U.S. and other parts of the world pay attention to legal innovation. Many firms have hired chief innovation officers and/or put a partner in charge of tracking innovation pertaining to the firm’s particular area of business. They are also hiring more and more legal project managers who are tasked with making sure that a firm’s expertise is packaged and made available to the clients in the most cost- and time-efficient way possible. At the same time, corporate legal departments are hiring legal operations professionals who specialize in the many ways that technology can make legal processes more efficient. In recent years, we have also witnessed an explosion of legal tech startups that provide a broad range of services to law firm or in-house customers. Generally speaking, we see innovation in legal research technologies, in big data analytics, in legal expert systems, in legal infrastructure (such as practice management and lawyer-client match-making marketplaces), and in online dispute resolution. At times, law firms and corporate legal department find themselves overwhelmed with the sheer number of new offerings in the legal tech space, sometimes resulting in a reluctance to try out new solutions.

CodeX — the Stanford Center for Legal Informatics — is focused on researching and developing technologies in the realm of computational law. Computational law is the branch of legal informatics concerned with the automation and mechanization of legal analysis. To that end, it leverages rule-based as well as statistical AI-based techniques (e.g., machine learning and Natural Language Processing). The former rule-based techniques are used to create new “TurboTax”-like solutions for specific areas of the law or for computable self-executing contracts. The latter statistical AI techniques are used to conduct analytics in legal settings, including so-called “predictive analytics.” In essence, predictive analytics is the use of data, statistical algorithms, and machine learning techniques to identify the likelihood of future outcomes based on historical data. The CodeX LegalTech Index, an open source database that at this point counts more than 730 legal tech companies, currently includes more than 38 companies in the analytics space. Those companies are innovating in search, eDiscovery, judicial/litigation analytics, contract analysis, IP analytics, legislative prediction, predictive policing, and lawsuit financing. The use of predictive analytics in law raises important questions. First, there are questions around technical feasibility. Getting access to high-quality training data to build predictions is challenging because most legal documents are in unstructured text form. Secondly, there are questions around transparency and explicability. These become problematic when data is used to not only show trends or patterns to a lawyer, but also to predict legal outcomes or to automate certain legal decisions. Systems that leverage predictive analytics and mechanize certain aspects of legal decision-making must be transparent and verifiable.

We are also seeing an increasing use of multi-sided lawyer platforms to foster new ways of finding or collaborating with clients or other lawyers. Some companies provide both platforms for lawyers as well as predictive analytics capabilities for their users (e.g., contract life cycle management solutions that also provide contracts analytics aimed at predicting risk in transactions; or lawyer client match-making platforms using machine learning and big data analytics to make the perfect match).

Adopting new legal technologies in any legal operation — be it in a law firm, corporate legal department, in government, or the judiciary — is a non-trivial undertaking that frequently reveals the challenges a particular organization faces when undergoing change.

There is no doubt in my mind that future legal professionals will have to approach legal solutions through the lens that an engineer might use when solving a computational problem. In addition to providing their legal expertise, they will have to think about how technology can be leveraged to distribute their expertise in the most efficient and cost-effective way. There will be technologies that replace certain tasks that are currently handled by human legal professionals, and there will be technologies that enhance human legal professionals. In any event, this is the time to rethink how the business of law can work. And there are already many great examples out there that show how legal services can be provided to clients in efficient and cost-effective ways, while still being profitable for lawyers.