297 results for search: https:/www.hab.cl/buy-aciphex-baikal-pharmacycom-rtlx/feed/rss2/tchad-faqs-fr

Learning a Modular, Auditable and Reproducible Workflow

The modular nature of the workflow and use of Git allowed us to work on different parts of the project from across the country.

Identifiers of Detained Children Have Implications for Data Security and Estimation

Identifiers being sequential could make possible estimations of the population of detained children.

Protecting the Privacy of Whistle-Blowers: The Staten Island Files

HRDAG built a machine-learning tool to strip the raw data of any potentially identifying information such as names and court case numbers. There was no "acceptable error rate."

Can the Armed Conflict Become Part of Colombia’s History?

Paula Amado and María Juliana Durán Fedullo reflect on how the Truth Commission may change Colombia’s history, finally officially acknowledging the 50-year conflict and its casualties, and reckoning with who did what to whom.

How Data Analysis Confirmed the Bias in a Family Screening Tool

In Pittsburgh …

How Predictive Policing Reinforces Bias

Algorithmic tools like PredPol were supposed to reduce bias. But HRDAG has found that racial bias is baked into the data used to train the tools.

How Pretrial Risk Assessment Tools Perpetuate Unfairness

Tools like Compas allegedly help judges predict future criminal activities and eliminate bias. HRDAG and partners showed how the tools recycle bias.

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 Statistics to Assess Lethal Violence in Civil and Inter-State War

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application, Volume 6. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Patrick Ball and Megan Price (2019). Using Statistics to Assess Lethal Violence in Civil and Inter-State War. Annual Review of Statistics and Its Application. 7 March 2019. © 2019 Annual Reviews. All rights reserved. https://doi.org/10.1146/annurev-statistics-030718-105222.

Privacy Policy

Mailing List Subscription We use Mailchimp to help us keep track of community members who want to stay informed about what HRDAG is doing and thinking. If you self-subscribe to our list, we will never share your contact information. We will never subscribe anyone who does not explicitly agree to a subscription.  Over the course of a year, we mail quarterly letters and fundraising letters, as well as one or two updates as events demand. If, during the course of a fundraising campaign, you make a donation, we will do our best to remove you from the remainder of fundraising mailings that year. We may use your contact information to invite you to ...

Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment

Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini (2018). Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment. Criminal Justice and Behavior. November 23, 2018. © 2018 Sage Journals. All rights reserved. https://doi.org/10.1177/0093854818811379

Laurel Eckhouse, Kristian Lum, Cynthia Conti-Cook and Julie Ciccolini (2018). Layers of Bias: A Unified Approach for Understanding Problems With Risk Assessment. Criminal Justice and Behavior. November 23, 2018. © 2018 Sage Journals. All rights reserved. https://doi.org/10.1177/0093854818811379

Low-risk population size estimates in the presence of capture heterogeneity

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065

James Johndrow, Kristian Lum and Daniel Manrique-Vallier (2019). Low-risk population size estimates in the presence of capture heterogeneity. Biometrika, asy065, 22 January 2019. © 2019 Biometrika Trust. https://doi.org/10.1093/biomet/asy065

Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study

Daniel Manrique-Vallier and Patrick Ball (2019). Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study. Research & Politics, 22 March 2019. © Sage Journals. https://doi.org/10.1177/2053168019835628

Daniel Manrique-Vallier and Patrick Ball (2019). Reality and risk: A refutation of S. Rendón’s analysis of the Peruvian Truth and Reconciliation Commission’s conflict mortality study. Research & Politics, 22 March 2019. © Sage Journals. https://doi.org/10.1177/2053168019835628

The impact of overbooking on a pre-trial risk assessment tool

Kristian Lum, Chesa Boudin and Megan Price (2020). The impact of overbooking on a pre-trial risk assessment tool. FAT* '20: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. January 2020. Pages 482–491. https://doi.org/10.1145/3351095.3372846 ©ACM, Inc., 2020.

Kristian Lum, Chesa Boudin and Megan Price (2020). The impact of overbooking on a pre-trial risk assessment tool. FAT* ’20: Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency. January 2020. Pages 482–491. https://doi.org/10.1145/3351095.3372846 ©ACM, Inc., 2020.

Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States

James Johndrow, Patrick Ball, Maria Gargiulo, and Kristian Lum. (2020). Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States. Harvard Data Science Review. 24 November, 2020. © The Authors, 2020, CC BY 4.0. https://doi.org/10.1162/99608f92.7679a1ed

James Johndrow, Patrick Ball, Maria Gargiulo, and Kristian Lum. (2020). Estimating the Number of SARS-CoV-2 Infections and the Impact of Mitigation Policies in the United States. Harvard Data Science Review. 24 November, 2020. © The Authors, 2020, CC BY 4.0. https://doi.org/10.1162/99608f92.7679a1ed

Beautiful game, ugly truth?

Megan Price (2022). Beautiful game, ugly truth? Significance, 19: 18-21. December 2022. © The Royal Statistical Society. https://doi.org/10.1111/1740-9713.01702

Megan Price (2022). Beautiful game, ugly truth? Significance, 19: 18-21. December 2022. © The Royal Statistical Society. https://doi.org/10.1111/1740-9713.01702

Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions

Daniel Manrique-Vallier, Patrick Ball, Mauricio Sadinle. (2022). Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions. In: Carriquiry, A.L., Tanur, J.M., Eddy, W.F. (eds) Statistics in the Public Interest. Springer Series in the Data Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-75460-0_2

Manrique-Vallier, D., Ball, P., Sadinle, M. (2022). Capture-Recapture for Casualty Estimation and Beyond: Recent Advances and Research Directions. In: Carriquiry, A.L., Tanur, J.M., Eddy, W.F. (eds) Statistics in the Public Interest. Springer Series in the Data Sciences. Springer, Cham. https://doi.org/10.1007/978-3-030-75460-0_2

verdata: An R package for analyzing data from the Truth Commission in Colombia

Maria Gargiulo, María Julia Durán, Paula Andrea Amado, and Patrick Ball (2024). verdata: An R package for analyzing data from the Truth Commission in Colombia. The Journal of Open Source Software. 6 January, 2024. 9(93), 5844, https://doi.org/10.21105/joss.05844. Creative Commons Attribution 4.0 International License.

Maria Gargiulo, María Julia Durán, Paula Andrea Amado, and Patrick Ball (2024). verdata: An R package for analyzing data from the Truth Commission in Colombia. The Journal of Open Source Software. 6 January, 2024. 9(93), 5844, https://doi.org/10.21105/joss.05844. Creative Commons Attribution 4.0 International License.

How public involvement can improve the science of AI

Proceedings of the National Academy of Sciences of the United States of America

As AI systems from decision-making algorithms to generative AI are deployed more widely, computer scientists and social scientists alike are being called on to provide trustworthy quantitative evaluations of AI safety and reliability. These calls have included demands from affected parties to be given a seat at the table of AI evaluation. What, if anything, can public involvement add to the science of AI? In this perspective, we summarize the sociotechnical challenge of evaluating AI systems, which often adapt to multiple layers of social context that shape their outcomes. We then offer guidance for improving the science of AI by engaging lived-experience experts in the design, data collection, and interpretation of scientific evaluations.

© 2025 National Academy of Sciences. All rights reserved.

Nathan Matias and Megan Price (2025). How public involvement can improve the science of AI. Proceedings of the National Academy of Sciences of the United States of America, Vol. 122, No. 48. 14 November, 2025. © 2025 National Academy of Sciences. https://doi.org/10.1073/pnas.2421111122

Rionegro

Text in English El uso de información de cementerios en la búsqueda de los desaparecidos: lecciones de un estudio piloto en Rionegro, Antioquia, Colombia Entre mayo y julio de 2009, investigadores del Grupo de Análisis de Datos de Derechos Humanos de Benetech (HRDAG por su sigla en inglés), condujeron un estudio piloto que examinó los patrones de la información sobre los cadáveres sin identificar en el cementerio de Rionegro, un municipio en el departamento de Antioquia, Colombia. El estudio se realizó en apoyo a los actuales esfuerzos de la organización socia de HRDAG, EQUITAS (Equipo Colombiano Interdisciplinario de Trabajo Forense y ...

Our work has been used by truth commissions, international criminal tribunals, and non-governmental human rights organizations. We have worked with partners on projects on five continents.

Donate

HRDAG

Selected projects

Stay informed about our work

©2025 Human Rights Data Analysis Group. Some rights reserved.
HRDAG is a non-profit project of Community Partners®, tax ID 95-4302067
Privacy Policy