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000042075 040__ $$aSzGeWIPO$$beng$$erda
000042075 041__ $$aeng
000042075 1001_ $$aSurden, Harry
000042075 24503 $$aMachine Learning and Law
000042075 264_1 $$a[Seattle, Washington] :$$bUniversity of Washington School of Law,$$c2014.
000042075 300__ $$a29 pages
000042075 336__ $$atext$$btxt$$2rdacontent
000042075 337__ $$aunmediated$$bn$$2rdamedia
000042075 338__ $$avolume$$bnc$$2rdacarrier
000042075 520__ $$aThis Article explores the application of machine learning techniques within the practice of law. Broadly speaking “machine learning” refers to computer algorithms that have the ability to “learn” or improve in performance over time on some task. In general, machine learning algorithms are designed to detect patterns in data and then apply these patterns going forward to new data in order to automate particular tasks. Outside of law, machine learning techniques have been successfully applied to automate tasks that were once thought to necessitate human intelligence — for example language translation, fraud-detection, driving automobiles, facial recognition, and data-mining. If performing well, machine learning algorithms can produce automated results that approximate those that would have been made by a similarly situated person.
000042075 525__ $$aPublished in : Washington Law Review, Vol. 89, no. 1, 2014
000042075 650_0 $$aPatents
000042075 650_0 $$aLitigation
000042075 650_0 $$aLitigation cost
000042075 650_0 $$aSoftware patents
000042075 85641 $$uhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=2417415$$yView this resource
000042075 904__ $$aJournal article
000042075 980__ $$aBIB