Computer Assisted Review (CAR) is a process of having computer software electronically classify documents based on input from expert reviewers, in an effort to expedite the organization and prioritization of the document collection. The computer classification may include broad topics pertaining to discovery responsiveness, privilege, and other designated issues. CAR may dramatically reduce the time and cost of reviewing ESI, by reducing the amount of human review needed on documents classified as potentially non-material.
The EDRM Search team has prepared a Computer Assisted Review Reference Model (CARRM) to document the steps of the process. This model represents joint efforts of some of the best known providers in Computer Assisted Review – Automony, an HP Company; Daegis; Exterro; Falcon Discovery; FTI Consulting; kCura; KPMG LLP; Kroll Ontrack; NightOwl Discovery; Recommind; and UBIC – as well as leaders from Bowman & Brooke LLP; DLA Piper LLP (US); Littler Mendelson, PC; and Quarles & Brady LLP. Click here for a complete list of EDRM Search members.
Like the EDRM framework, the CARRM framework should be a useful reference for e-discovery practitioners at corporations, law firms and elsewhere; e-discovery services and software providers; and organizations evaluating e-discovery tools.
The Major Steps in the CARRM Process
The process of deciding the outcome of the Computer Assisted Review process for a specific case. Some of the outcomes may be:
- reduction and culling of not-relevant documents;
- prioritization of the most substantive documents; and
- quality control of the human reviewers.
The process of building the human coding rules that take into account the use of CAR technology. CAR technology must be taught about the document collection by having the human reviewers submit documents to be used as examples of a particular category, e.g. Relevant documents. Creating a coding protocol that can properly incorporate the fact pattern of the case and the training requirements of the CAR system takes place at this stage. An example of a protocol determination is to decide how to treat the coding of family documents during the CAR training process.
The process of transferring the review protocol information to the human reviewers prior to the start of the CAR Review.
The process of human reviewers applying subjective coding decisions to documents in an effort to adequately train the CAR system to “understand” the boundaries of a category, e.g. Relevancy.
The process of the CAR system applying the information “learned” from the human reviewers and classifying a selected document corpus with pre-determined labels.
The process of human reviewers using a validation process, typically statistical sampling, in an effort to create a meaningful metric of CAR performance. The metrics can take many forms, they may include estimates in defect counts in the classified population, or use information retrieval metrics like Precision, Recall and F1.
The process of the review team deciding if the CAR system has achieved the goals of anticipated by the review team.
The process of ending the CAR workflow and moving to the next phase in the review lifecycle, e.g. Privilege Review.
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