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000042028 040__ $$aSzGeWIPO$$beng$$erda
000042028 041__ $$aeng
000042028 1001_ $$aWachter, Sandra
000042028 1001_ $$aMittelstadt, Brent
000042028 24503 $$aA Right to Reasonable Inferences :$$bRe-Thinking Data Protection Law in the Age of Big Data and AI
000042028 264_1 $$a[New York City, New York] :$$bColumbia Business Law Review,$$c2018.
000042028 300__ $$a130 pages
000042028 336__ $$atext$$btxt$$2rdacontent
000042028 337__ $$aunmediated$$bn$$2rdamedia
000042028 338__ $$avolume$$bnc$$2rdacarrier
000042028 520__ $$aThis Article argues that a new data protection right, the ‘right to reasonable inferences’, is needed to help close the accountability gap currently posed by ‘high risk inferences’ , meaning inferences drawn from Big Data analytics that damage privacy or reputation, or have low verifiability in the sense of being predictive or opinion-based while being used in important decisions. This right would require ex-ante justification to be given by the data controller to establish whether an inference is reasonable. This disclosure would address (1) why certain data form a normatively acceptable basis from which to draw inferences; (2) why these inferences are relevant and normatively acceptable for the chosen processing purpose or type of automated decision; and (3) whether the data and methods used to draw the inferences are accurate and statistically reliable. The ex-ante justification is bolstered by an additional ex-post mechanism enabling unreasonable inferences to be challenged.
000042028 525__ $$aPublished in : Columbia Business Law Review, 2019(2)
000042028 650_0 $$aArtificial Intelligence
000042028 650_0 $$aAutomated Decision-Making
000042028 650_0 $$aBig Data
000042028 650_0 $$aCopyright
000042028 650_0 $$aData Protection
000042028 650_0 $$aData Analytics
000042028 85641 $$uhttps://papers.ssrn.com/sol3/papers.cfm?abstract_id=3248829$$yView this resource
000042028 904__ $$aJournal article
000042028 980__ $$aBIB