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Citizen-generated data is especially important for women's rights issues. In many countries the lack of women in positions of institutional power, combined with slow, bureaucratic systems and a lack of prioritisation of women's rights issues means data isn't gathered on relevant topics, let alone appropriately responded to by the state. Even when data is gathered by institutions, societal pressures may mean it remains inadequate. In the case of gender-based violence, for instance, women often suffer in silence, worrying nobody will believe them or that they will be blamed. Providing a way for women to contribute data anonymously or, if they so choose, with their own details, can be key to documenting violence and understanding the scale of a problem, and thus deciding upon appropriate responses.

If you were surprised by the result of the Brexit vote in the UK or by the Trump victory in the US, you might live in an echo chamber - a self-reinforcing world of people who share the same opinions as you. Echo chambers are a problem, and not just because it means some people make incorrect predictions about political events. They threaten our democratic conversation, splitting up the common ground of assumption and fact that is needed for diverse people to talk to each other. A few tools are mentioned in the post that help you see "the other side" of a story - you might like to play with them, e.g. http://politecho.org "is a browser extension that shows the political biases of your friends and Facebook newsfeed"

EVERYONE HAS A THEORY about who's to blame for the housing shortage that's driving up prices and chasing Bay Area families out of the region. A new poll offers surprising insights into where most of us point the finger: not at the government officials who control what homes are built where, but at the tech companies that have flooded this region with jobs and the real estate developers trying to maximize profits.

Interesting discussion of a contentious issue (although a little light on evidence!!) Tallinn, known for its digital government and successful tech startups, is often referred to as Europe's innovation capital. Now celebrating five years of free public transport for all citizens, the government is planning to make Estonia the first free public transport nation. Allan Alaküla, Head of Tallinn European Union Office, shares some valuable insights for other cities.

When creating a machine-learning algorithm, designers have to make many choices: what data to train it on, what specific questions to ask, how to use predictions that the algorithm produces. These choices leave room for discrimination, particularly against people who have been discriminated against in the past. For example, training an algorithm to select potential medical students on a data set that reflects longtime biases against women and people of color may make these groups less likely to be admitted. In computing, the phrase "garbage in, garbage out" describes how poor-quality input leads to poor-quality output. In this case we might say, "White male doctors in, white male doctors out."

Mashable's series Algorithms explores the mysterious lines of code that increasingly control our lives - and our futures. The world in 2020 has been given plenty of reasons to be wary of algorithms. Depending on the result of the U.S. presidential election, it may give us one more. Either way, it's high time we questioned the impact of these high-tech data-driven calculations, which increasingly determine who or what we see (and what we don't) online. The impact of algorithms is starting to scale up to a dizzying degree, and literally billions of people are feeling the ripple effects. This is the year the Social Credit System, an ominous Black Mirror-like "behavior score" run by the Chinese government, is set to officially launch. It may not be quite as bad as you've heard, but it will boost or tighten financial credit and other incentives for the entire population. There's another billion unexamined, unimpeachable algorithms hanging over a billion human lives.

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.

Some advice on evaluating claims made on data Bergstrom believes that calling bullshit on data, big or otherwise, doesn't require a statistics degree-only common sense and a few habits of mind. "You don't have to understand all the gears inside a black box in order to evaluate what you're being told," he said. For those who were unable to enroll in INFO 198/BIOL 106B this spring, here is some of his and West's advice: