data collection

In spite of what you may have heard, robots will not be infiltrating the legal profession any time soon. Artificial intelligence (AI) and related technologies like machine learning and natural language processing have attracted rapturous attention over the last year and indeed hold tremendous promise. In fact, many organizations that have invested in these technologies are already reaping real benefits. We are not, however, following an innovation trajectory that will lead to “robot lawyers” replacing their human counterparts, whether we're talking about 2018 or 2028.

Let's be clear: The robot scenario is mostly hype. The hype may generate short-term interest, but it can be harmful in the long term because it detracts from real, significant technological developments that more people in the profession should know about and be benefitting from. These developments are not only poised to transform the industry in the years to come, but are already streamlining legal workflows in surprising ways, and enhancing the productivity and capabilities of lawyers right now.

Advanced technologies are helping lawyers do better work in a couple of key areas: by automating repetitive and/or data-intensive tasks, and by providing lawyers with previously inaccessible information and data-based insights that help them make smarter tactical decisions and develop winning legal strategies. In some cases, these two broad categories of tools can be integrated to create even more powerful synergies. But the best “intelligent” tools based on AI-type technologies are not designed to replace lawyers. Instead, they are dramatically improving the interface between humans and machines so that lawyers can perform the work they already do much more efficiently and effectively, and so they can focus on the most substantive tasks the job entails.

Smart tools are establishing a blueprint for the data-driven lawyer of the future. The emphasis on data is important because much of the innovation we currently see in the profession is, in fact, being driven by the massive and rapidly expanding volumes of data that now underlie legal work in every corner of the industry and at every step in legal workflows. The other important trend driving technological innovation is coming from clients and business executives, who now expect the same levels of efficiency, cost-effectiveness and detailed accountability from their law firms and legal departments as they do from any other vendor or business unit they work with. Legal organizations everywhere face intense scrutiny and cost pressures. They are tasked with providing ever more value for less, and technology will continue to play an important role in addressing that challenge.

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Today's Data-Driven Tools

As we head into a new year, there are plenty of ways in which today's data-driven lawyer is already interacting with technology to address these challenges. Here are a just a few examples:

Decision Tools: Legal analytics involves the use of machine learning and natural language processing to clean, tag, structure and find meaningful patterns in raw historical data from federal litigation, making that data readily searchable by lawyers with no technical background using natural language search queries. Users of analytical tools can instantly access previously unavailable, data-based insights into the past behavior of judges, opposing counsel and parties—and in very specific contexts.

Based on past behavior in similar cases, how likely is a particular judge to grant a specific type of motion? What is the track record of opposing counsel in pursuing cases before certain judges and courts? How has a specific party, or a group of comparable parties, fared in legal matters that resemble your current case? What case damages have been awarded in matters similar to your own? These are the kinds of questions to which legal analytics can provide factual answers in a matter of seconds.

Lawyers are already using analytics to access statistics and easy-to-grasp visualizations that directly inform legal strategy and help with tactical decision-making, including fundamental questions like whether to pursue litigation or enter into negotiations. Analytics is also helping litigators make data-based decisions when selecting outside counsel or recruiting individual attorneys with specific areas of expertise. Data that illuminates current practice area trends is even being used by marketing and business development professionals at law firms to help prioritize investments. As of early 2018, legal analytics covers nine major federal practice areas, and its scope is expanding rapidly.

Sophisticated Search Tools: Legal analytics is hardly the only realm in which better search technology plays a crucial role. Until recently, conventional online legal research focused on precedent tended to rely on keywords and Boolean logic, relying heavily on the technical skills and experience of the researcher. AI technologies have begun to make a big difference in this area, enabling much more effective natural language searching as well as queries about more general legal topics or concepts—even when we don't know much about them and lack the technical vocabulary to execute an effective keyword search.

Machine learning, natural language processing and deep learning technologies are making it possible for computers to understand the content and context of a search query, find and present precise data and specific passages within relevant case law, and anticipate an attorneys' needs—regardless of the complexity of the content or the legal context from which the query arises.

Systems are also being developed that can ask users questions to refine a search and generate sufficient information to present the user with a recommendation or inform a decision. This might involve identifying clusters of similar information and providing suggestions about related points of law. It could also involve a system proactively conducting legal or Internet research to find relevant citations or other information that could credibly support or undermine the user's arguments or case strategy.

Another exciting development that AI technologies enable is integrated searching, whereby an attorney can run a single natural language search query that will generate results from case law and precedent; insights from litigation data about lawyers, firms, parties, judges and venues; in-house data stores containing reusable work product, including language for drafting documents; and sources of online information about other matter-relevant topics, such as business or specific industries.

Personalization: Search is one obvious activity in which machine learning technology can be deployed to generate more targeted results based on what a system has “learned” about an individual lawyer or researcher from inputs and behaviors over time. For instance, search results can be filtered based on a user's role in the organization or on the practice area the user works in. A law librarian, a securities litigator and a partner engaged in business development will likely require different types and levels of information from the same search query, and technology has now evolved to make that possible. Professionals are also able to save search histories and progressions, making it possible to step away from a complicated query and return to it at another time, or even access saved searches from another device. Systems are also being “trained” to generate recommended search queries based on an individual user's past search behaviors and on the searches of team members or other colleagues.

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The Future of Analytic Systems

Where is all of this headed? In the next few years, legal professionals will benefit from a comprehensive technological ecosystem of AI-enhanced research, practice area know-how, workflow and analytics, and these toolsets will be seamlessly integrated in a single intuitive interface. That interface will be accessible via multiple secure devices, including mobile phones, and users will be able to engage in voice-based Q&A search queries from massive sets of enriched legal data and receive specific answers (and links to passage-level documentation) instead of standard search results with links to very large documents that may or may not be relevant.

In 2018, attorneys in client meetings or in a courtroom will be able to pull out a tablet and review the complete track record of opposing counsel in relevant cases and gain insights that will help them anticipate and counter the tactics they are likely to encounter. Legal teams will use advanced technology to collaborate more efficiently, annotating passages and documents within search results, recalling past search histories and internal work product that are relevant to a current matter, and accessing notes and annotations across devices to enable 24/7 remote participation in team activities.

Intelligent analytic systems will be able to predict the likely outcomes of legal strategies in very specific legal contexts, and lawyers will have credible tools to bring to client meetings where they can compare and contrast strategic approaches to a matter based on historical data and current trends, enabling detailed risk analysis based on insights mined from vast stores of litigation data.

Amid all these “smart” toolsets, lawyers will not disappear, but they will do better work in the months and years to come, and they will do it faster and more efficiently. They will make decisions that are less instinctual or reliant on anecdote and more firmly rooted in comprehensive, factual information. That's a positive development for both lawyers and their clients, and we shouldn't let it get lost amid the present hype about “robot lawyers.”

Serena Wellen is a Senior Director of Product Management for LexisNexis and a former trial attorney. Her portfolio includes artificial intelligence, analytics and visualization capabilities for Lexis Advance as well as litigation research products for LexisNexis. She lives and works in San Francisco, CA.