Legal technologies and innovation are at the forefront of change in the legal profession and of high relevance to law students.
This guide provides useful resources to help you understand and keep up-to-date in areas such as artificial intelligence, robots and the law, legal analytics, blockchain, predictive coding, and more.
Read books, papers and blogs; listen to podcasts and videos; identify relevant legislation and cases; learn more about the types of practical legal applications of technology; and find ideas to help with teaching and learning.
Due to the fast pace of change in this area, visit the guide regularly for updates.
Artificial Intelligence: A discipline concerned with the building of computer programs that perform tasks requiring intelligence when done by humans. However, intelligent tasks for which a decision procedure is known (e.g. inverting matrices) are generally excluded, whereas perceptual tasks that might seem not to involve intelligence (e.g. seeing) are generally included.
Automated Reasoning: The use of computer programs that perform inference processes.
Biometrics: The use of unique physical characteristics (fingerprints, iris pattern etc.) to identify individuals, typically for the purposes of security
Cloud Computing: An approach to computing in which the end user connects to a remote network of computers (the cloud) in order to run programs, store data, etc. This enables users to access large amounts of data storage and computing power from anywhere in the world without having to own and maintain these resources themselves.
Data Mining: The nontrivial explication or extraction of information from data, in which the information is implicit and previously unknown; an example is identification of the pattern of use of a credit card to detect possible fraud.
Machine Learning: A branch of artificial intelligence concerned with the construction of programs that learn from experience. Learning may take many forms, ranging from learning from examples and learning by analogy to autonomous learning of concepts and learning by discovery.
Natural-Language Processing: The area of computer science that develops systems that implement natural-language understanding. It is a sub-discipline of artificial intelligence and of computational linguistics.
Robotics: A discipline overlapping artificial intelligence and mechanical engineering. It is concerned with building robots: programmable devices consisting of mechanical actuators and sensory organs that are linked to a computer.
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