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AI-Powered Dispute Settlement
The objective of this project is to develop an algorithmic system, trained on both public legal data and proprietary negotiation data, that will provide tailored predictions of likely court-based dispute resolution outcomes and optimal settlements. In the proposed sub-project, a team of interns (JD students) will be modelling and labelling dispute-resolution data on complaints against hospitals and municipalities. We anticipate that a first dataset, ready for algorithmic model testing, will be completed by the end of the internship.
Faculty Supervisor:
Samuel Dahan;Maxime Cohen
Student:
Arash Rouhi;Mercy Liu;Dilina Lallani;Caroline Ross
Partner:
Borden Ladner Gervais LLP
Discipline:
Law
Sector:
University:
Program:
Accelerate
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