ENTRIES TAGGED "Facebook"
Response to NSA data mining and the troubling lack of technical details, Facebook's Open Compute data center, and local police are growing their own DNA databases.
It’s a question of power, not privacy — and what is the NSA really doing?In the wake of the leaked NSA data-collection programs, the Pew Research Center conducted a national survey to measure American’s response. The survey found that 56% of respondents think NSA’s telephone record tracking program is an acceptable method to investigate terrorism, and 62% said the government’s investigations into possible terrorist threats are more important than personal privacy.
Rebecca J. Rosen at The Atlantic took a look at legal scholar Daniel J. Solove’s argument that we should care about the government’s collection of our data, but not for the reasons one might think — the collection itself, he argues, isn’t as troubling as the fact that they’re holding the data in perpetuity and that we don’t have access to it. Rosen quotes Solove:
“The NSA program involves a massive database of information that individuals cannot access. … This kind of information processing, which forbids people’s knowledge or involvement, resembles in some ways a kind of due process problem. It is a structural problem involving the way people are treated by government institutions. Moreover, it creates a power imbalance between individuals and the government. … This issue is not about whether the information gathered is something people want to hide, but rather about the power and the structure of government.”
Obstacles for big data, big data intelligence, and a privacy plugin puts Google and Facebook settings in the spotlight.
Here are a few stories from the data space that caught my attention this week.
Big obstacles for big data
For the latest issue of Foreign Policy, Uri Friedman put together a summarized history of big data to show “[h]ow we arrived at a term to describe the potential and peril of today’s data deluge.” A couple months ago, MIT’s Alex “Sandy” Pentland took a look at some of that big data potential for Harvard Business Review; this week, he looked at some of the perilous aspects. Pentland writes that to be realistic about big data, it’s important to look not only at its promise, but also its obstacles. He identifies the problem of finding meaningful correlations as one of big data’s biggest obstacles:
“When your volume of data is massive, virtually any problem you tackle will generate a wealth of ‘statistically significant’ answers. Correlations abound with Big Data, but inevitably most of these are not useful connections. For instance, your Big Data set may tell you that on Mondays, people who drive to work rather than take public transportation are more likely to get the flu. Sounds interesting, and traditional research methods show that it’s factually true. Jackpot!
“But why is it true? Is it causal? Is it just an accident? You don’t know. This means, strangely, that the scientific method as we normally use it no longer works, because there are so many possible relationships to consider that many are bound to be ‘statistically significant’. As a consequence, the standard laboratory-based question-and-answering process — the method that we have used to build systems for centuries — begins to fall apart.”
Pentland says that big data is going to push us out of our comfort zone, requiring us to conduct experiments in the real world — outside our familiar laboratories — and change the way we test the causality of connections. He also addresses issues of understanding those correlations enough to put them to use, knowing who owns the data and learning to forge new types of collaborations to use it, and how putting individuals in charge of their own data helps address big data privacy concerns. This piece, together with Pentland’s earlier big data potential post, are this week’s recommended reads.
How Facebook stacks up against other tech IPOs.
This week's visualization comes from The New York Times and compares the last 30 years of tech IPOs (hint: watch for the big blue dot).
Pete Warden walks through the steps behind his latest Facebook visualization.
Creating a visualization requires more than just data and imagery. Pete Warden outlines the process and actions that drove his new Facebook visualization project.
Facebook says we're closer than we thought, Gnip targets finance, and eBay grabs Hunch.
Facebook research questions the "six degrees of separation" rule, Gnip gets into the real-time financial data business, and eBay looks to put Hunch's recommendation engine to use.
Facebook surfaces past status updates, particles defy physics, and data goes Hollywood in "Moneyball."
This week's data news includes news on Facebook's Timeline, observations of neutrinos moving faster than the speed of light, and Hollywood's take on data analysis.