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On The Exactitude Of Big Data: La Bêtise And Artificial Intelligence, Noel Fitzpatrick, John D. Kelleher Dec 2018

On The Exactitude Of Big Data: La Bêtise And Artificial Intelligence, Noel Fitzpatrick, John D. Kelleher

Articles

This article revisits the question of ‘la bêtise’ or stupidity in the era of Artificial Intelligence driven by Big Data, it extends on the questions posed by Gille Deleuze and more recently by Bernard Stiegler. However, the framework for revisiting the question of la bêtise will be through the lens of contemporary computer science, in particular the development of data science as a mode of analysis, sometimes, misinterpreted as a mode of intelligence. In particular, this article will argue that with the advent of forms of hype (sometimes referred to as the hype cycle) in relation to big data and …


Outcome Prediction In The Practice Of Law, Mark K. Osbeck, Michael Gilliland Jul 2018

Outcome Prediction In The Practice Of Law, Mark K. Osbeck, Michael Gilliland

Articles

Business forecasters typically use time-series models to predict future demands, the forecasts informing management decision making and guiding organizational planning. But this type of forecasting is merely a subset of the broader field of predictive analytics, models used by data scientists in all manner of applications, including credit approvals, fraud detection, product-purchase and music-listening recommendations, and even the real-time decisions made by self-driving vehicles. The practice of law requires decisions that must be based on predictions of future legal outcomes, and data scientists are now developing forecasting methods to support the process. In this article, Mark Osbeck and Mike Gilliland …


Ethics Of Using Artificial Intelligence To Augment Drafting Legal Documents, David Hricik Jan 2018

Ethics Of Using Artificial Intelligence To Augment Drafting Legal Documents, David Hricik

Articles

Skynet is not and may never be self-aware, but machines are al-ready doing legal research, drafting legal documents, negotiating disputes such as traffic tickets and divorce schedules, and even drafting patent applications. Machines learn from us, and each other, to augment the ability of lawyers to represent clients—and even to replace lawyers completely. While it also threatens lawyers’ jobs, the exponential increase in the capacity of machines to transmit, store, and process data presents the opportunity for lawyers to use these services to provide better, cheaper, or faster legal representation to clients. By way of familiar example, instead of determining …