Big Data Teaches Us We Are Big Paranoid
November 18, 2016
I love election years! Actually, that is sarcasm. Election years bring out the worst in Americans. The media runs rampant with predictions that each nominee is the equivalent of the anti-Christ and will “doom America,” “ruin the nation,” or “destroy humanity.” The sane voter knows that whoever the next president is will probably not destroy the nation or everyday life…much. Fear, hysteria, and paranoia sells more than puff pieces and big data supports that theory. Popular news site Newsweek shares that, “Our Trust In Big Data Shows We Don’t Trust Ourselves.”
The article starts with a new acronym: DATA. It is not that new, but Newsweek takes a new spin on it. D means dimensions or different datasets, the ability to combine multiple data streams for new insights. A is for automatic, which is self-explanatory. T stands for time and how data is processed in real time. The second A is for artificial intelligence that discovers all the patterns in the data.
Artificial intelligence is where the problems start to emerge. Big data algorithms can be unintentionally programmed with bias. In order to interpret data, artificial intelligence must learn from prior datasets. These older datasets can show human bias, such as racism, sexism, and socioeconomic prejudices.
Our machines are not as objectives as we believe:
But our readiness to hand over difficult choices to machines tells us more about how we see ourselves.
Instead of seeing a job applicant as a person facing their own choices, capable of overcoming their disadvantages, they become a data point in a mathematical model. Instead of seeing an employer as a person of judgment, bringing wisdom and experience to hard decisions, they become a vector for unconscious bias and inconsistent behavior. Why do we trust the machines, biased and unaccountable as they are? Because we no longer trust ourselves.”
Newsweek really knows how to be dramatic. We no longer trust ourselves? No, we trust ourselves more than ever, because we rely on machines to make our simple decisions so we can concentrate on more important topics. However, what we deem important is biased. Taking the Newsweek example, what a job applicant considers an important submission, a HR representative will see as the 500th submission that week. Big data should provide us with better, more diverse perspectives.
Whitney Grace, November 18, 2016
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
Geofeedias Political Action
August 20, 2015
The presidential election is a little over a year away and potential presidential candidates are starting on their campaign trails. The Republican and Democratic parties are heating up with the GOP debates and voters are engaging with the candidates and each other via social media. The information posted on social media is a gold mine for the political candidates to learn about the voters’ opinions and track their approval rating. While Twitter and Facebook data is easy to come by with Google Analytics and other software, visual mapping of the social media data is a little hard to find.
To demonstrate its product capabilities, Geofeedia took social media Instagram, fed it into its data platform, and shared the visual results in the blog post, “Instagram Map: Republican Presidential Debate.” Geofeedia noted that while business mogul Donald Trump did not fare well during the debate nor is he in the news, he is dominating the social media feeds:
“Of all social content coming out of the Quicken Loans Center, 93% of posts were positive in sentiment. The top keywords were GOP, debate, and first, which was to be expected. Although there was no decided winner, Donald Trump scored the most headlines for a few of his memorable comments. He was, however, the winner of the social sphere. His name was mentioned in social content more than any other candidate.”
One amazing thing is that social media allows political candidates to gauge the voters’ attitudes in real time! They can alter their answers to debate questions instantaneous to sway approval in their favor. Another interesting thing Geofeedia’s visual data models showed is a heat map where the most social media activity took place, which happened to be centered in the major US metropolises. The 2016 election might be the one that harnesses social media to help elect the next president. Also Geofeedia also has excellent visual mapping tools.
Whitney Grace, August 20, 2015
Sponsored by ArnoldIT.com, publisher of the CyberOSINT monograph
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