January 22, 2013
Editor’s note: This month we have asked technologically savvy attorneys to share their thoughts on the future of legal technology. Big Data, Mobile, and Cloud Computing are all on the docket, but first a look at how far legal technology has come in the last fifteen years.
Week 1: A Look Back
Week 2: Key Trends
New technologies have long changed the ways in which lawyers both provide and market their legal services. Personal computing, data digitization, the Internet, e-mail, search engines, and so on: These are all technologies that have greatly aided—or, depending on your perspective, hindered—the provision of legal services over the last 25 years. As one considers the budding technologies of today, and the potential technologies of tomorrow, it’s worth considering how those technologies will project onto lawyers over the next five or ten years. Three of those technologies—social media, machine-learning, and cloud computing—promise to offer both rewards and create pitfalls for legal professionals and offices.
Facebook, LinkedIn, Twitter: These web-based communications and networking platforms are all household names today, but five years ago, each of them barely existed. Now, they are ubiquitous social media tools that have become ingrained in the daily lives of hundreds of millions of people. For lawyers they also present both opportunities and challenges in the future.
Lawyers in traditional law firms can only do their jobs if they have clients. Traditionally, lawyers have gained clients through two primary sources, their own personal networks and referrals from existing clients and contacts. In order to continue to market their services now and in the future, however, lawyers and law firm will need to meet clients where they are. And that will require networking with new and existing clients through social media platforms.
Social media presents a different challenge for legal professionals in corporate and government offices. While they may not have the same need to use social media to develop client relationships, they often have the burden of ensuring that their organization establishes reasonable and defensible social media policies, and effectively monitors and enforces those policies.
In addition, social media sites are, at their essence, forums for communication. And the status of social media communications create new—and, in many cases, undefined—legal issues that will confront lawyers as those technologies mature. The collection and production of social media communications in discovery; the preservation of attorney-client privilege and attorney work product protection in social media forums; and the overlapping and conflicting boundaries of ownership of social media assets are all open questions that lawyers will need to sort out as those platforms continue to play a greater role in society in the future.
Despite the mass proliferation of electronic data over the past 25 years, lawyers—and the courts—continue their struggle to tame the beast otherwise known as e-discovery. E-discovery is costly, time-consuming, and, in many cases, the vast majority of it is unfruitful in prosecuting litigation.
In the past, and still today, e-discovery processes are performed in a more or less routinized way that involves some basic technologies, including mass electronic data recovery, keyword searches, and tedious individual review of electronic documents.
The application of machine-learning technology to litigation—also known as predictive coding—is the latest attempt to alleviate some of e-discovery’s traditional headaches. To do this, predictive coding trains computers to automatically determine how documents should be identified in litigation with limited human input. By setting specific parameters and coding a sample of documents, lawyers can review thousands of documents in the time that it used to take them to review hundreds.
Predictive coding, however, is not an e-discovery panacea. The technology—as applied in litigation—is still in its infancy, and its early adoption has, in some cases, resulted in protracted discovery disputes. Nor have parties been required to use it in place of other acceptable e-discovery technologies that they prefer. Yet, as machine-learning technology continues to improve in the near-future, predictive coding is one possible way out of the e-discovery morass.
Cloud computing has been one of the biggest buzzwords in technology over the past few years. In its most basic form, cloud computing represents a movement away from individual organizations maintaining their own massive data infrastructures and allowing cloud services companies to maintain that data for them. This provides some key benefits, including outsourcing information technology, and the scalability and accessibility of data, to companies that have the resources to specialize in providing those information services.
There are, however, some key limitations as well. First and foremost of these is a loss of control over an organization’s data. This can present problems for legal professionals and those that they serve. Lawyers, of course, have a duty to maintain the confidentiality of their clients’ information. By storing client information in the cloud, however, lawyers give up some control over how the confidentiality of their clients’ information is maintained. Any data breach at a cloud computing company storing a lawyer’s client information would result not only in major technological problems for that lawyer, but major client confidentiality problems as well.
These three technologies—social media, machine-learning, and cloud computing—are all in their early stages of adoption by the legal community. Over the coming years, however, they promise to play an ever-increasing role in how lawyers provide their services.