By Michael SimonOur modern lives are filled with black boxes, things that we understand in terms of the inputs they require (click the mouse, turn the wheel, insert slice of bread) and the outputs we receive (your computer beeps, your car turns, you get toast!). Yet between the input and the output there are a whole bunch of things happening that we can’t see, can’t explain, and – most importantly – don’t actually need to explain to accomplish our desired task. As long as the inputs are understandable and the outputs are what we expect, what lies in between can be completely opaque. I don’t need to know how my toaster works, as long as I get my toast.So why is the fact that machine learning (a/k/a “predictive coding”) is a black box such a problem? Is it because human review of documents (i.e., an eyes-on-all-docs full review) is somehow more transparent? Of course not. We have study after study of the greater accuracy and effectiveness of review assisted by machine learning (when used properly).
News, views, discussions and data associated with the field of electronic discovery.
Information Governance (InfoGovernance) is the specification of decision rights and an accountability framework to encourage desirable behavior in the valuation, creation, storage, use, archiving and deletion of information. It includes the processes, roles, standards and metrics that ensure the effective and efficient use of information to enable an organization to achieve its goals. Information governance should be an element in planning an enterprise's information architecture.
(Gartner Hype Cycle for Legal and Regulatory Information Governance, 2009, December 2009).
An Engagement Area (EA) is an area where the commander of a military force intends to contain and destroy an enemy force with the massed effects of all available weapons systems.
(FM 1-02, Operational Terms and Graphics, September 2004).
