Predictive Coding Technologies and Protocols: Fall 2021 Survey

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Editor’s Note: EDRM is proud to support the seventh semi-annual Predictive Coding Technologies and Protocols Survey conducted by ComplexDiscovery.

Legal, information technology, and business professionals involved in organizational activities involving the use of predictive coding are encouraged to complete the short five-question survey.

The initial six surveys provided detailed feedback from approximately 384* legal, business, and technology professionals on the use of specific machine learning technologies in predictive coding and also highlighted the usage of those machine learning technologies as part of example technology-assisted review protocols. This iteration of the survey continues to focus on predictive coding technologies, protocols, workflows, and uses across the eDiscovery ecosystem. Originally consisting of four core questions, beginning in the fall of 2020 the survey included one new question on the prevalence of predictive coding usage as part of eDiscovery workflows.

Predictive Coding Technologies and Protocols (Survey)

A Five-Question Survey

Pleasee click here to take the simple five-question survey designed to capture the current application of technologies, protocols, workflows, and uses of predictive coding in the eDiscovery ecosystem.

Legal, information technology, and business professionals involved in organizational activities involving the use of predictive coding are encouraged to complete the short five-question survey.

Results of the survey (excluding responder contact information) will be aggregated and published on the ComplexDiscovery blog for usage by the eDiscovery community.

Take the survey here.

Author

  • Mary Mack is the CEO and Chief Legal Technologist for EDRM. Mary was the co-editor of the Thomson Reuters West Treatise, eDiscovery for Corporate Counsel for 10 years and the co-author of A Process of Illumination: the Practical Guide to Electronic Discovery. She holds the CISSP among her certifications.

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