705 results for search: %ED%99%8D%EB%B3%B4%EC%A0%84%EB%AC%B8%E3%85%BF%ED%85%94%EB%A0%88adgogo%E3%85%BF%EA%B0%81%EC%82%B0%EA%B1%B4%EC%A0%84%EB%A7%88%EC%82%AC%EC%A7%80%E3%81%BF%ED%99%8D%EB%B3%B4%E2%94%BA%EC%A0%84%EB%AC%B8%E2%82%AA%EA%B0%81%EC%82%B0%E4%9D%90%EA%B1%B4%EC%A0%84%EB%A7%88%EC%82%AC%EC%A7%80%E7%AE%A0nonbeing/feed/rss2/privacy
New Estimate Of Killings By Police Is Way Higher — And Still Too Low
Carl Bialik of 538 Politics interviews HRDAG executive director Patrick Ball in an article about the recently released Bureau of Justice Statistics report about the number of annual police killings, both reported and unreported. As Bialik writes, this is a math puzzle with real consequences.
What happens when you look at crime by the numbers
Kristian Lum’s work on the HRDAG Policing Project is referred to here: “In fact, Lum argues, it’s not clear how well this model worked at depicting the situation in Oakland. Those data on drug crimes were biased, she now reports. The problem was not deliberate, she says. Rather, data collectors just missed some criminals and crime sites. So data on them never made it into her model.”
Amnesty report damns Syrian government on prison abuse
An excerpt: The “It breaks the human” report released by the human rights group Amnesty International highlights new statistics from the Human Rights Data Analysis Group, or HRDAG, an organization that uses scientific approaches to analyze human rights violations.
A better statistical estimation of known Syrian war victims
Researchers from Rice University and Duke University are using the tools of statistics and data science in collaboration with Human Rights Data Analysis Group (HRDAG) to accurately and efficiently estimate the number of identified victims killed in the Syrian civil war.
…
Using records from four databases of people killed in the Syrian war, Chen, Duke statistician and machine learning expert Rebecca Steorts and Rice computer scientist Anshumali Shrivastava estimated there were 191,874 unique individuals documented from March 2011 to April 2014. That’s very close to the estimate of 191,369 compiled in 2014 by HRDAG, a nonprofit that helps build scientifically defensible, evidence-based arguments of human rights violations.
Trump’s “extreme-vetting” software will discriminate against immigrants “Under a veneer of objectivity,” say experts
Kristian Lum, lead statistician at the Human Rights Data Analysis Group (and letter signatory), fears that “in order to flag even a small proportion of future terrorists, this tool will likely flag a huge number of people who would never go on to be terrorists,” and that “these ‘false positives’ will be real people who would never have gone on to commit criminal acts but will suffer the consequences of being flagged just the same.”
Calculations for the Greater Good
As executive director of the Human Rights Data Analysis Group, Megan Price uses statistics to shine the light on human rights abuses.
Crean sistema para predecir fosas clandestinas en México
Por ello, Human Rights Data Analysis Group (HRDAG), el Programa de Derechos Humanos de la Universidad Iberoamericana (UIA) y Data Cívica, realizan un análisis estadístico construido a partir de una variable en la que se identifican fosas clandestinas a partir de búsquedas automatizadas en medios locales y nacionales, y usando datos geográficos y sociodemográficos.
Sobre fosas clandestinas, tenemos más información que el gobierno: Ibero
El modelo “puede distinguir entre los municipios en que vamos a encontrar fosas clandestinas, y en los que es improbable que vayamos a encontrar estas fosas”, explicó Patrick Ball, estadístico estadounidense que colabora con el Programa de Derechos Humanos de la Universidad Iberoamericana de la Ciudad de México.
Fosas clandestinas en México manifiestan existencia de crímenes de lesa humanidad
Patrick Ball, estadístico norteamericano, colabora con el Programa de Derechos Humanos de la Universidad Iberoamericana en una investigación sobre fosas clandestinas.
The ghost in the machine
“Every kind of classification system – human or machine – has several kinds of errors it might make,” [Patrick Ball] says. “To frame that in a machine learning context, what kind of error do we want the machine to make?” HRDAG’s work on predictive policing shows that “predictive policing” finds patterns in police records, not patterns in occurrence of crime.
Cifra de líderes sociales asesinados es más alta: Dejusticia
Contrario a lo que se puede pensar, los datos oficiales sobre líderes sociales asesinados no necesariamente corresponden a la realidad y podría haber mucha mayor victimización en las regiones golpeadas por este flagelo, según el más reciente informe del Centro de Estudios de Justicia, Derecho y Sociedad (Dejusticia) en colaboración con el Human Rights Data Analysis Group.
Using Data to Reveal Human Rights Abuses
Profile touching on HRDAG’s work on the trial and conviction of Hissène Habré, its US Policing Project, data integrity, data archaeology and more.
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.
5 Questions for Kristian Lum
Kristian Lum discusses the challenges of getting accurate data from conflict zones, as well as her concerns about predictive policing if law enforcement gets it wrong.
Hunting for Mexico’s mass graves with machine learning
“The model uses obvious predictor variables, Ball says, such as whether or not a drug lab has been busted in that county, or if the county borders the United States, or the ocean, but also includes less-obvious predictor variables such as the percentage of the county that is mountainous, the presence of highways, and the academic results of primary and secondary school students in the county.”
Documenting Syrian Deaths with Data Science
Coverage of Megan Price at the Women in Data Science Conference held at Stanford University. “Price discussed her organization’s behind-the-scenes work to collect and analyze data on the ground for human rights advocacy organizations. HRDAG partners with a wide variety of human rights organizations, including local grassroots non-governmental groups and—most notably—multiple branches of the United Nations.”