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Some great quotes in this piece! The language of politics warps our democracy again and again, as in this tax calculation. The media must unpack statistics Last week, the Institute for Fiscal Studies and the Health Foundation published a report on funding for health and social care. One figure from the report was repeated across the headlines. For the NHS to stay afloat, it would require "£2,000 in tax from every household". Shocking stuff!If you're sitting at a bar with a group of friends and Bill Gates walks in, the average wealth of everyone in the room makes you all millionaires. But if you try to buy the most expensive bottle of champagne in the place, your debit card will still be declined. The issue to be addressed, and one to which there is no fully correct answer, is how we can put numbers into a context that enables people to make informed choices. Big numbers are hard to conceptualise - most of us have no intuitive understanding of what £56bn even looks like.

Data analysis is playing an increasing role in the U.S. electoral system, raising an important question as the Trump administration prepares to oversee the 2020 Census: What if the data aren't reliable?

We learned this week that the Trump campaign may have tried to dissuade millions of Black voters from voting in 2016 through highly targeted online ads. The investigation, by Channel 4, highlighted a still little-understood online advertising technique, microtargeting. This targets ads at people based on the huge amount of data available about them online. Experts say Big Tech needs to be much more transparent about how microtargeting works, to avoid overblown claims but also counter a potential threat to democracy.

hen the AP United States history students at Aragon High School in San Mateo California, scanned the professionally designed pages of www.minimumwage.com, most concluded that it was a solid, unbiased source of facts and analysis. They noted the menu of research reports, graphics and videos, and the "About" page describing the site as a project of a "nonprofit research organization" called the Employment Policies Institute. But then their teacher, Will Colglazier, demonstrated how a couple more exploratory clicks-critically, beyond the site itself-revealed that the Employment Policies Institute is considered by the Center for Media and Democracy to be a front group created by lobbyists for the restaurant and hotel industries. "I have some bright students, and a lot of them felt chagrined that they weren't able to deduce this," said Colglazier, who videotaped the episode last January. "They got duped."

Great article discussing experts, their role in democracy, and some of the problems facing expertise. "Part of the problem is that some people think they're experts when in fact they're not. We've all been trapped at a party where one of the least informed people in the room holds court, confidently lecturing the other guests with a cascade of banalities and misinformation. This sort of experience isn't just in your imagination. It's real, and it's called "the Dunning-Kruger effect," after the research psychologists David Dunning and Justin Kruger. The essence of the effect is that the less skilled or competent you are, the more confident you are that you're actually very good at what you do. The psychologists' central finding: "Not only do [such people] reach erroneous conclusions and make unfortunate choices, but their incompetence robs them of the ability to realize it." We are moving toward a Google-fueled, Wikipedia-based collapse of any division between professionals and laypeople."

The Supreme Court does not compute. Or at least some of its members would rather not. The justices, the most powerful jurists in the land, seem to have a reluctance - even an allergy - to taking math and statistics seriously. For decades, the court has struggled with quantitative evidence of all kinds in a wide variety of cases. Sometimes justices ignore this evidence. Sometimes they misinterpret it. And sometimes they cast it aside in order to hold on to more traditional legal arguments. (And, yes, sometimes they also listen to the numbers.) Yet the world itself is becoming more computationally driven, and some of those computations will need to be adjudicated before long. Some major artificial intelligence case will likely come across the court's desk in the next decade, for example. By voicing an unwillingness to engage with data-driven empiricism, justices - and thus the court - are at risk of making decisions without fully grappling with the evidence. This problem was on full display earlier this month, when the Supreme Court heard arguments in Gill v. Whitford, a case that will determine the future of partisan gerrymandering - and the contours of American democracy along with it. As my colleague Galen Druke has reported, the case hinges on math: Is there a way to measure a map's partisan bias and to create a standard for when a gerrymandered map infringes on voters' rights?