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The specter of the impact of artificial intelligence [AI] on law and legal education casts a long and uncertain shadow. Its mix of enthusiasm and trepidation can arise from a thin idea of what the label refers to. Four components differentiate AI from even high-end automation: Big data and predictive analytics, deep learning software, cloud computing, and natural language process. From the perspective of the person on the street though, is captured as “the art of creating machines that perform functions that require intelligence when performed by people,” centering on the ability to make independent choices. While that gloss may fail as a technical specification, it appears to capture the ordinary meaning, and will suffice for the purposes of this chapter, with only one additional clarification.

In the following discussion we focus on what exists today, narrow (or weak) AI. Narrow AI refers to algorithms that are application-specific, as compared to the generalized AI that mimics the human ability to learn and perform on any topic. Generalized (or strong) AI does not currently exist, and some experts are skeptical that it ever will. If society decides that even this limited version of AI is undesirable, all things considered, then that determination should preclude any need to separately evaluate the general variety. For the time being, therefore, we are justified in considering only the narrow version.

By that definition, we are already immersed in an AI-rich environment. The appeal is obvious. A dispassionate computer algorithm returns lower error rates when compared to humans, in part because it reasons from data without being swayed by emotions or preferred outcomes. A common example of everyday AI application occurs whenever Amazon shoppers find book recommendations based on the user’s past views and purchases. This ability to find hidden patterns received a powerful demonstration when Target identified a young customer whose shopping habits signaled a pregnancy that was unknown to the parents who complained when the store started sending baby-related coupons. AI helps spam filters learn to exclude emails of a certain kind and not just those that contain certain words. Our phones work to understand our individual dialects. With the development of self-driving cars, intelligent refrigerators, and medical diagnostics, it will be a rare individual who can claim that they have insulated themselves from this new world of nonhuman thinking and learning. Such a ubiquitous impact cannot help but reach into the practice of law.

Publication Date

2020

Book Title

Law Librarianship in the Age of AI

Book Author/Editor

Ellyssa Kroski

Publisher

ALA Editions

ISBN

978-0838946275

Disciplines

Digital Communications and Networking | Law Librarianship

Benefits, drawbacks, and risks of AI

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