In the last year there has numerous articles, blogs, presentations and panels discussing the legal perils of “Bring Your Own Device” or BYOD policies. BYOD refers to the policy of permitting employees to bring personally owned mobile devices (laptops, tablets, and smart phones) to their workplace, and to use those devices to access privileged company information and applications. The problem with BYOD is company access to company data housed on the device. For example, how would you search for potentially relevant content on a smartphone if the employee wasn’t immediately available or refused to give the company access to it?

Many organizations have banned BYOD as a security risk as well as a liability when involved with litigation.

BYOC Equals Underground Archiving?

Organizations are now dealing with another problem, one with even greater liabilities. “Bring your own cloud” or BYOC refers to the availability and use by individuals…

Much has been written in the last several years about Predictive Coding (as well as Technology Assisted Review, Computer Aided Review, and Craig Ball’s hilarious Super Human Information Technology ). This automation technology, now heavily used for eDiscovery, relies heavily on “machine learning”,  a discipline of artificial intelligence (AI) that automates computer processes that learn from data, identify patterns and predict future results with varying degrees of human involvement. This interative machine training/learning approach has catapulted computer automation to unheard-of and scary levels of potential. The question I get a lot (I think only half joking) is “when will they learn enough to determine we and the attorneys they work with are no longer necessary?

Is it time to build in some safeguards to machine learning? Thinking back to the days I read a great deal of Isaac Asimov (last week), I thought about Asimov’s The Three Laws…