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Weapons of Math Destruction
Weapons of Math Destruction: invisible, ubiquitous algorithms are ruining millions of lives. Excerpt:
As Patrick once explained to me, you can train an algorithm to predict someone’s height from their weight, but if your whole training set comes from a grade three class, and anyone who’s self-conscious about their weight is allowed to skip the exercise, your model will predict that most people are about four feet tall. The problem isn’t the algorithm, it’s the training data and the lack of correction when the model produces erroneous conclusions.
Using statistics to estimate the true scope of the secret killings at the end of the Sri Lankan civil war
In the last three days of the Sri Lankan civil war, as thousands of people surrendered to government authorities, hundreds of people were put on buses driven by Army officers. Many were never seen again.
In a report released today (see here), the International Truth and Justice Project for Sri Lanka and the Human Rights Data Analysis Group showed that over 500 people were disappeared on only three days — 17, 18, and 19 May.
Improving the estimate of U.S. police killings
Cory Doctorow of Boing Boing writes about HRDAG executive director Patrick Ball and his contribution to Carl Bialik’s article about the recently released Bureau of Justice Statistics report on the number of annual police killings, both reported and unreported, in 538 Politics.
Data Mining for Good: Thoreau Center Lunch + Learn
Core Concepts
Uncovering Police Violence in Chicago: A collaboration between HRDAG and Invisible Institute
Pulling the Plug: Network Disruptions and Violence in the Syrian Conflict
Trove to IPFS
Using Data and Statistics to Bring Down Dictators
In this story, Guerrini discusses the impact of HRDAG’s work in Guatemala, especially the trials of General José Efraín Ríos Montt and Colonel Héctor Bol de la Cruz, as well as work in El Salvador, Syria, Kosovo, and Timor-Leste. Multiple systems estimation and the perils of using raw data to draw conclusions are also addressed.
Megan Price and Patrick Ball are quoted, especially in regard to how to use raw data.
“From our perspective,” Price says, “the solution to that is both to stay very close to the data, to be very conservative in your interpretation of it and to be very clear about where the data came from, how it was collected, what its limitations might be, and to a certain extent to be skeptical about it, to ask yourself questions like, ‘What is missing from this data?’ and ‘How might that missing information change these conclusions that I’m trying to draw?’”
Videos
The World According to Artificial Intelligence (Part 1)
The World According to Artificial Intelligence: Targeted by Algorithm (Part 1)
The Big Picture: The World According to AI explores how artificial intelligence is being used today, and what it means to those on its receiving end.
Patrick Ball is interviewed: “Machine learning is pretty good at finding elements out of a huge pool of non-elements… But we’ll get a lot of false positives along the way.”
Humanitarian Statistics
In late 2006, a statistical study of deaths that occurred after the invasion of Iraq ignited a storm of controversy. This Lancet study estimated that more than 650,000 additional Iraqis died during the invasion than would have at pre-invasion death rates, a vastly higher estimate than any previous. But in January, a World Health Organization study placed the number at about 150,000.