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With the emergence of new data usage and privacy laws, most notably the GDPR and Privacy Shield in the EU, ventures are forced to revisit their data to determine if and how the new laws, policies, and practices affect their own internal resources and processes. Digging through corporate documents and databases to ensure legal compliance will become an increasingly more daunting task for any corporation, particularly Internet-based ventures with global footprints and ambitions. Our Machine Learning and Privacy project will develop the processes to allow ventures, large or small, to sort through its documents and database and determine if and where its documents and processes might run afoul of data usage and privacy laws and practices.
This project will also lead students through the development of a workflow process to assist startup entrepreneurs and small businesses identifying potential GDPR compliance risk areas. Students will convert the workflow into a structured, interactive chat dialogue that will interrogate users following the designed workflow to flag risk areas.
The skills and processes learned in the context of European privacy laws will then be applied to automate and apply machine learning techniques to other areas of legal concern (e.g., understanding and extracting data from a broad array of legal documents; parsing through and reconciling potentially conflicting open source and other licensing schemes).
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