Posts Under: Big Data

AI Spotlight: Solving Anne Frank’s Betrayal with Artificial Intelligence

One of the biggest cold cases of the 21st Century is the case of who betrayed Anne Frank and her family to the Nazis during World War II.  Anne Frank’s family and another family famously hid in a secret annex for two years before they were given away by an unknown person to the Gestapo.  The Nazis found them and they were sent to concentration camps.  Anne died in the Bergen-Belsen concentration camp and famously wrote a diary documenting her experience hiding from the Nazis.  Her father Otto was the lone survivor of the group of eight hiders.  Otto was able to piece together much of what happened and had Anne’s diary published.  Yet, the Frank family, and many other families who suffered in the holocaust, thought they would never know who betrayed them.  Artificial Intelligence (AI) may be a tool that can help solve this mystery. This case, along with a few others, is strange for a number of reasons.  First, the Nazis were known f ...

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Big Data: A Twenty-First Century Arms Race Report Launch

The Atlantic Council and Thomson Reuters released a timely report on “Big Data: A Twenty-First Century Arms Race” on June 27, 2017, at a well-attended event at the Atlantic Council’s Washington, D.C. headquarters.  Policymakers all over the world should be aware of the powerful tools at their disposal such as World-Check to address political and economic threats.  This is something of a theme for SIIA.  Recently, for example, we wrote about how artificial intelligence (AI) can help in the anti-money laundering (AML) fight.   We have also written about how FICO’s AML tool works.  The Atlantic Council report contains many realistic policy recommendations, which policymakers from different regulatory “silos” should review.  This is another theme for SIIA.  Regulators and policymakers should engage in regular dialogue with each other.  For example, financial supervisors and privacy regulators should talk to ea ...

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SIIA Releases Brief on Algorithmic Fairness

Recent technological developments have led to the rise of “big data” analytics which include machine learning and artificial intelligence.  These new technologies will without question provide ample opportunity for growth for consumers, businesses, and the global economy as a whole.  As this technological evolution continues to take place, it does not come without some risk.   Over the last few years, algorithmic fairness, has become an issue of serious debate.  Most recently, Cathy O’Neil released a book titled, “Weapons of Math Destruction,” and Frank Pasquale published “The Black Box Society,” in which they look at issues of discrimination and the role that algorithms play in exacerbating discrimination.  SIIA responded to these works in a blog by saying that tech leaders must quickly act to ensure algorithmic fairness. To go even further, on Friday, November 04, 2016, SIIA released an issue brief on the topic ...

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How Hanley Wood Learned to Stop Worrying and Love the Ad Sales Data Bomb

It's what Prescott Shibles warned us about last year at the 2015 Connectiv Executive Summit when he said, "Targeting data will soon be worth more than advertising inventory." But for Hanley Wood, accepting and adapting to this change in buyer behavior became an opportunity to reverse engineer the formula to provide unique data points to advertisers, charge a premium for it and even boost performance on its own properties. 

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SIIA to NTIA: Maintain Current Frameworks for Regulating the IoT

Today, SIIA submitted comments responding to the National Telecommunications and Information Administration’s (NTIA) request for comments concerning the benefits, challenges, and potential roles of government in fostering the Internet of Things (IoT).  

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SSD Webcast | Data Transformation, Processing and Analytics

Data Transformation, Processing & Analytics

The Right Tools for the Right Job

Big data is transforming how companies manage, operate, analyze, and innovate.  With growing movements in every department toward more data-driven decision making, organizations often ask: how do I think about my Big Data project? What is the framework? Where is Big Data providing value to my organization today? And where should it drive value in 2016?

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Re-Thinking Privacy in the Connected World

Late last week, SIIA hosted a lunch event “Re-Thinking Privacy in the Connected World” that focused on reevaluating popular understandings of the privacy cost/benefit analysis of data-driven innovation and the Internet of Things (IoT). So often discussion of these technologies and analytic methods demonize data collection as a risk to personal privacy and security. But our speakers gave us a more balanced understanding of the complex relationship between technology, data and privacy.  They underscored that while there may be fundamental right to privacy, privacy is not monolithic, but based on a diverse and evolving set of expectations.  And they rebutted the notions that enhancing privacy can be accomplished merely by limiting data collection, or that more data equals less privacy, which calls for more regulation. more

Data Analytics Improves Decisionmaking

A recent article in the New York Times raises the question: do algorithms discriminate?  The question is legitimate, but the emphasis is wrong.  Instead of thinking of data analytics as a problem, we need to welcome the new opportunities for improved decisionmaking that they enable.  And we need to cooperate to identify and address any disparate impacts data-driven decisionmaking might have.

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