Wikipedia defines “ethos” in part as: the guiding beliefs or ideals that characterize a community, a nation, or an ideology. In this case the community is that one emerging around “Big Data.” The community who is now collecting, mapping, reducing, and querying gigabytes , terabytes, and petabytes of data.
Our community is now breaching the realm of credit card companies (with fraud detection), Wall Street “quants” with their micro trend algorithms, and our friends in the goverment with deep pockets and Big Iron.
With open source software, commodity hardware and a few Ph.D’s we can now unlock the mysteries of huge data sets. We can now go after complex, and extremely compelling problems. And we can begin to understand, predict, and even steer human behavior to an unprecedented degree.
As interesting as the problems we chase, will be the dilemmas that emerge. Three questions and one searing comment remain etched on my mind from the early days of the revolution:
From a Casino: “Can I predict when a gambler is ABOUT to feel unlucky (so the casino could intervene to them in their casino)”
From a military researcher: “How can I increase my “Kills per Million”?
From a consumer food company: “How long can we keep trans fats in food before we risk a class action lawsuit”
and finally, from an energy trader: “We like to create monopolies, then induce volatility!”
The answers to all of the questions would (and in the case of the casino, did) deliver competitive advantage.
The comment from the energy trader preceeded the collapse of an industry and the dissolution of his company.
All of these statements also made my colleagues and me stop to think ,“Yeah, we can do this, but should we”?
Data Ethos exists to examine that spectrum from competitive advantage to bad behavior as the Big Data / Data Science community evolves.
To paraphrase Peter Parker’s (Spiderman) uncle Ben: With Big Data comes Big Responsibility!
Lets go solve cool problems! And, let’s try not the melt the earth into a soupy goo in the process!
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