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Excellent NYT interactive - where do you draw the line on how your data is used by social media companies and smart devices?

Nice little interactive piece from the NYTimes - they've charted sets of data from the Bush presidency, can you accurately extend their line charts to show the change over the Obama years?

Interesting discussion of data on vote recounts and using electronic or hand counting methods (in America where they use electronic voting machines quite commonly). These numbers represent three main kinds of disputes, Foley told me. First, candidates (and their lawyers) argue over what ballots should be counted and which should be thrown out as ineligible. Then, they argue over which candidate specific ballots should count for. Finally, they argue over whether all the eligible votes were counted correctly - the actual recount. Humans are much better than machines at making decisions around the first two kinds of ambiguous disputes, Stewart said, but evidence suggests that the computers are better at counting. Michael Byrne, a psychology professor at Rice University who studies human-computer interaction, agreed. "That's kind of what they're for," he said.

This is a really great example of using a visualisation to communicate a quantitative fact check. This claim is a good case for doing a basic plausibility check, and thinking about what numeric information you'd need to know to understand the claim (e.g., how many people are deported now (what's the baseline), and what are the estimates for the maximum number of unauthorized immigrants in the country?).

Most people pass through some type of public space in their daily routine - sidewalks, roads, train stations. Thousands walk through Bryant Park every day. But we generally think that a detailed log of our location, and a list of the people we're with, is private. Facial recognition, applied to the web of cameras that already exists in most cities, is a threat to that privacy. To demonstrate how easy it is to track people without their knowledge, we collected public images of people who worked near Bryant Park (available on their employers' websites, for the most part) and ran one day of footage through Amazon's commercial facial recognition service.

Nearly every ad you see online is tailored just for you. These digital ads are powered by vast, hidden datasets that allow advertisers to make eerily accurate guesses about who you are, where you've been, how you feel and what you might do next. While targeted ads may be familiar by now, how they work - and the power they have - often seems invisible. We decided to lift the veil on this part of the internet economy, so we bought some ad space. We picked 16 categories (like registered Democrats or people trying to lose weight) and targeted ads at people in them. But instead of trying to sell cars or prescription drugs, we used the ads to reveal the invisible information itself.

The reasons for the disparity in pay vary from company to company but the broader source of the gap can be seen in the distribution of high earners by gender. Of all the companies that have reported to date the top pay quartile, the highest paid 25% of employees, is male-dominated. Almost two-thirds of the top quartile is made up of men, while conversely 57% of the lowest-paid employees are women.

Electric vehicles are better for the climate than gas-powered cars, but many Americans are still reluctant to buy them. One reason: The larger upfront cost. New data published Thursday shows that despite the higher sticker price, electric cars may actually save drivers money in the long-run. To reach this conclusion, a team at the Massachusetts Institute of Technology calculated both the carbon dioxide emissions and full lifetime cost - including purchase price, maintenance and fuel - for nearly every new car model on the market. They found electric cars were easily more climate friendly than gas-burning ones. Over a lifetime, they were often cheaper, too.

Welcome! This app will help train you to make more accurate, better-calibrated predictions. For each question, you'll be prompted to say what you think the answer is and how confident you are in that answer. You should try to give the right answer whenever you can, but your main goal is to be accurate about how confident you are in each answer. In other words, your goal is to be "well-calibrated," which means that when you say you're 50% confident, you're right about 50% of the time, and when you say you're 80% confident, you're right about 80% of the time, and so on. Nobody is perfectly calibrated, but some people are much better calibrated than others, and a variety of studies suggest you can improve your calibration with the sort of practice this app provides.

Some fantastic visualisations in this piece from the Guardian, including a scatterplot and some different kinds of histograms! Well worth exploring. "The figures reveal men are paid more than women in 7,795 out of 10,016 companies and public bodies in Britain, based on the median hourly pay. Across the companies and organisations that had filed by 8am on Thursday, eight out of 10 had a gender pay gap. While the figures do not reflect equal pay for equal work, they do raise questions about structural inequalities in the workforce and may hold the answer to closing the gap."