701 results for search: %EB%A7%88%EC%BC%80%ED%8C%85%EC%A0%84%EB%AC%B8%E2%99%82%ED%85%94%EA%B7%B8adgogo%E2%99%82%EB%8B%A8%EA%B5%AC%EB%8F%99%ED%98%B8%EC%8A%A4%ED%8A%B8%EB%B0%94%E3%83%AD%EB%A7%88%EC%BC%80%ED%8C%85%E2%94%9E%EC%A0%84%EB%AC%B8%18%EB%8B%A8%EA%B5%AC%EB%8F%99%E5%B0%A3%ED%98%B8%EC%8A%A4%ED%8A%B8%EB%B0%94%E5%B0%A3interjectional/feed/rss2/chad-photo-essay
Reflections: Growing and Learning in Guatemala
Welcoming Our 2019 Human Rights Intern
Reflections: HRDAG Was Born in Washington
A Model to Estimate SARS-CoV-2-Positive Americans
Reflections: A Meaningful Partnership between HRDAG and Benetech
Nonprofits Are Taking a Wide-Eyed Look at What Data Could Do
Stay informed about our work
Big data may be reinforcing racial bias in the criminal justice system
Laurel Eckhouse (2017). Big data may be reinforcing racial bias in the criminal justice system. Washington Post. 10 February 2017. © 2017 Washington Post.
Benetech’s Human Rights Data Analysis Group Publishes 2010 Analysis of Human Rights Violations in Five Countries,
Analysis of Uncovered Government Data from Guatemala and Chad Clarifies History and Supports Criminal Prosecutions
By Ann Harrison
The past year of research by the Benetech Human Rights Data Analysis Group (HRDAG) has supported criminal prosecutions and uncovered the truth about political violence in Guatemala, Iran, Colombia, Chad and Liberia. On today’s celebration of the 62nd anniversary of the Universal Declaration of Human Rights, HRDAG invites the international community to engage scientifically defensible methodologies that illuminate all human rights violations – including those that cannot be directly observed. 2011 will mark the 20th year that HRDAG researchers have analyzed the patterns and magnitude of human rights violations in political conflicts to determine how many of the killed and disappeared have never been accounted for – and who is most responsible.
State Violence in Guatemala, 1960-1996: A Quantitative Reflection
Patrick Ball, Paul Kobrak, Herbert F. Spirer. State Violence in Guatemala, 1960-1996: A Quantitative Reflection. © 1999 American Association for the Advancement of Science. [pdf – english] [pdf – español]
In Syria, Uncovering the Truth Behind a Number
Huffington Post Politics writer Matt Easton interviews Patrick Ball, executive director of HRDAG, about the latest enumeration of killings in Syria. As selection bias is increasing, it becomes harder to see it: we have the “appearance of perfect knowledge, when in fact the shape of that knowledge has not changed that much,” says Patrick. “Technology is not a substitute for science.”
Data Mining for Good: CJA Drink + Think
Working Where Statistics and Human Rights Meet
Robin Mejia and Megan Price (2018). Working Where Statistics and Human Rights Meet. Chance (special issue). February 2018. © 2018 CHANCE.
The Statistics of Genocide
Patrick Ball and Megan Price (2018). The Statistics of Genocide. Chance (special issue). February 2018. © 2018 CHANCE.
Selection Bias and the Statistical Patterns of Mortality in Conflict.
Megan Price and Patrick Ball. 2015. Statistical Journal of the IAOS 31: 263–272. doi: 10.3233/SJI-150899. © IOS Press and the authors. All rights reserved. Creative Commons BY-NC-SA.
Talks
Haiti
Palantir Has Secretly Been Using New Orleans to Test Its Predictive Policing Technology
One of the researchers, a Michigan State PhD candidate named William Isaac, had not previously heard of New Orleans’ partnership with Palantir, but he recognized the data-mapping model at the heart of the program. “I think the data they’re using, there are serious questions about its predictive power. We’ve seen very little about its ability to forecast violent crime,” Isaac said.
Celebrating Women in Statistics
In her work on statistical issues in criminal justice, Lum has studied uses of predictive policing—machine learning models to predict who will commit future crime or where it will occur. In her work, she has demonstrated that if the training data encodes historical patterns of racially disparate enforcement, predictions from software trained with this data will reinforce and—in some cases—amplify this bias. She also currently works on statistical issues related to criminal “risk assessment” models used to inform judicial decision-making. As part of this thread, she has developed statistical methods for removing sensitive information from training data, guaranteeing “fair” predictions with respect to sensitive variables such as race and gender. Lum is active in the fairness, accountability, and transparency (FAT) community and serves on the steering committee of FAT, a conference that brings together researchers and practitioners interested in fairness, accountability, and transparency in socio-technical systems.
Criminality registration and measurement
Patrick Ball and Michael Reed Hurtado. 2016. El registro y la medición de la criminalidad. El problema de los datos faltantes y el uso de la ciencia para producir estimaciones en relación con el homicidio en Colombia, demostrado a partir de un ejemplo: el departamento de Antioquia (2003-2011). Revista Criminalidad, 58 (1): 9-23. Criminality registration and measurement. The problem of missing data, and the use of science to produce estimations relating to homicide in Colombia, as demonstrated with an example from one of its administrative and political divisions: the Department of Antioquia (2003-2011).