dunnettreader + big_data   4

What a fossil revolution reveals about the history of ‘big data’ – David Sepkoski | Aeon Ideas
A stenopterygius fossil. Photo courtesy Wikipedia In 1981, when I was nine years old, my father took me to see Raiders of the Lost Ark . Although I had to…
big_data  paleobiology  archaeology  geology  from instapaper
march 2018 by dunnettreader
Noah Smith - Economics Has a Math Problem - Bloomberg View - September 2015
A lot of people complain about the math in economics. Economists tend to quietly dismiss such complaints as the sour-grapes protests of literary types who lack…
Instapaper  economic_theory  economic_models  mathematization  statistics  big_data  machine_learning  from instapaper
september 2015 by dunnettreader
Danielle Keats Citron and Frank A. Pasquale - "The Scored Society: Due Process for Automated Predictions" | 89 Washington Law Review 1 (2014)
Both at University of Maryland Francis King Carey School of Law -- Keywords - Big Data, predictions, artificial intelligence -- Big Data is increasingly mined to rank and rate individuals. Predictive algorithms assess whether we are good credit risks, desirable employees, reliable tenants, valuable customers—or deadbeats, shirkers, menaces, and “wastes of time.” Crucial opportunities are on the line, including the ability to obtain loans, work, housing, and insurance. Though automated scoring is pervasive and consequential, it is also opaque and lacking oversight. In one area where regulation does prevail—credit—the law focuses on credit history, not the derivation of scores from data. Procedural regularity is essential for those stigmatized by “artificially intelligent” scoring systems. The American due process tradition should inform basic safeguards. Regulators should be able to test scoring systems to ensure their fairness and accuracy. Individuals should be granted meaningful opportunities to challenge adverse decisions based on scores miscategorizing them. Without such protections in place, systems could launder biased and arbitrary data into powerfully stigmatizing scores. -- downloaded pdf to Note
article  legal_theory  US_constitution  civil_liberties  due_process  big_data  financial_innovation  privacy  reputation  inequality  financial_regulation  algorithms  downloaded  EF-add 
july 2014 by dunnettreader

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