Quantitative Legal Prediction – or – How I Learned to Stop Worrying and Start Preparing for the Data Driven Future of the Legal Services Industry

Quantitative Legal Prediction – or – How I Learned to Stop Worrying and Start Preparing for the Data Driven Future of the Legal Services Industry. Katz, D. M. December, 2012.

Paper abstract bibtex

Do I have a case? What is our likely exposure? How much is this going to cost? What will happen if we leave this particular provision out of this contract? How can we best staff this particular legal matter? These are core questions asked by sophisticated clients such as general counsels as well as consumers at the retail level. Whether generated by a mental model or a sophisticated algorithm, prediction is a core component of the guidance that lawyers offer. Indeed, it is by generating informed answers to these types of questions that many lawyers earn their respective wage.

@misc{katzQuantitativeLegalPrediction2012,
	address = {Rochester, NY},
	type = {{SSRN} {Scholarly} {Paper}},
	title = {Quantitative {Legal} {Prediction} – or – {How} {I} {Learned} to {Stop} {Worrying} and {Start} {Preparing} for the {Data} {Driven} {Future} of the {Legal} {Services} {Industry}},
	url = {https://papers.ssrn.com/abstract=2187752},
	abstract = {Do I have a case?  What is our likely exposure? How much is this going to cost? What will happen if we leave this particular provision out of this contract? How can we best staff this particular legal matter?  These are core questions asked by sophisticated clients such as general counsels as well as consumers at the retail level. Whether generated by a mental model or a sophisticated algorithm, prediction is a core component of the guidance that lawyers offer. Indeed, it is by generating informed answers to these types of questions that many lawyers earn their respective wage.},
	language = {en},
	urldate = {2023-06-12},
	author = {Katz, Daniel Martin},
	month = dec,
	year = {2012},
	keywords = {algorithmic justice, big data, law, legal prediction, legal services, machine learning, prediction, quantitative legal prediction},
}

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