Predicting the Outcome of Legal Cases: How Technology Promises to Help

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Predicting the outcome of a case may be getting easier. The Toronto based product Tax Foresight, part of Blue J Legal, promises to do just that. Users enter facts into the program and an answer is provided.

Professors Benjamin Alarie et al, explain in “Computational Legal Research and the Advocates of the Future that the program’s algorithms are trained on data of thousands of cases. The software analyzes the facts provided by users, then places those in facts in relation to facts in previously decided cases, and produces a prediction about the likely outcome of the case.

It is predicted that tools like this will be available for every major legal area and jurisdiction.

Although I am a proponent of such software, questions must be asked. How do we ensure neutral algorithms? How will data created by these program be used? Will data about the types of users, types of questions asked, and types of answers be sold for profit? Who will guard the privacy interests of users? What role will lawyers’ have in creating these products? Will judges be allowed to use these products? We must also ask what role law societies will have in regulating these products? After all people’s reliance on information from programs with outdated data or biased algorithms could have serious legal and financial consequences.

I predict that Blue J Legal’s software will also expand to other areas of law like insurance. It will allow lawyers and lay people to answer questions and find results within minutes.

Perhaps in the future, litigation will be dominated by disputes about which facts should be inputted into algorithm. For example, in a personal injury case, the focus may be on whether someone really has chronic pain. Once a judge determines the person has chronic pain, the fact is inputted into the algorithm and the algorithm calculates the amount of damages owed.

(Views are my own and do not reflect the views of any organization. This is not a sponsored post.)

 

 

 

 

 

 

 

 

 

 

 

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