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Tech Note – using LLMs for structured info extraction

This post introduces the methodology of the Innocence Discovery Lab, a collaboration between IPNO and HRDAG.

Quantifying Injustice

“In 2016, two researchers, the statistician Kristian Lum and the political scientist William Isaac, set out to measure the bias in predictive policing algorithms. They chose as their example a program called PredPol.  … Lum and Isaac faced a conundrum: if official data on crimes is biased, how can you test a crime prediction model? To solve this technique, they turned to a technique used in statistics and machine learning called the synthetic population.”


The John Maddox Prize for Patrick Ball

Congratulations to Patrick on this well deserved award!

Outreach at Toronto TamilFest for Counting the Dead

Michelle spent a weekend in Toronto, Canada, reaching out to the community at TamilFest, where she and a colleague invited people to sit down and talk.

Counting the Dead in Sri Lanka

ITJP and HRDAG are urging groups inside and outside Sri Lanka to share existing casualty lists.

Mexico

HRDAG and our partners Data Cívica and the Iberoamericana University created a machine-learning model to predict which counties (municipios) in Mexico have the highest probability of unreported hidden graves. The predictions help advocates to bring public attention and government resources to search for the disappeared in the places where they are most likely to be found. Context For more than ten years, Mexican authorities have been discovering hidden graves (fosas clandestinas). The casualties are attributed broadly—and sometimes inaccurately—to the country’s “drug war,” but the motivations and perpetrators behind the mass murders ...

Reflections: Minding the Gap

How might we learn what we don’t know? HRDAG associate Christine Grillo hits the wayback machine and recalls her first exposure to People Against Bad Things, ideas about bias and correlation versus causation, and truth.

Our Thoughts on #metoo

Violence against women in all its forms is a human rights violation. Most of our HRDAG colleagues are women, and for us, unfortunately, recent campaigns such as #metoo are unsurprising.

FAT* Conference 2018

Kristian Lum spoke about "Understanding the Context and Consequences of Pre-Trial Detention" at the Conference on Fairness, Accountability, and Transparency (FAT*).

Kristian Lum in Bloomberg

The interview poses questions about Lum's focus on artificial intelligence and its impact on predictive policing and sentencing programs.

Videos

Here is a collection of videos that profile projects or features us at speaking engagements. Please get in touch with us if you have any HRDAG video or photography.

.Rproj Considered Harmful

We aim to produce code that is clear, replicatable across machines and operating systems, and that leaves an easy-to-follow audit trail.

Mortality in the DDS Prisons in Chad, 1985–1988

Patrick Ball (2014). Human Rights Data Analysis Group. August 22, 2014. © 2014 HRDAG. Creative Commons BY-NC-SA.


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.”


Reflections: The People Who Make the Data

HRDAG associate Miguel Cruz has an epiphany. All those data he’s drowning in? Each datapoint is a personal tragedy, a story both dark and urgent, and he’s privileged to have access.

Film: Solving for X

Solving for X documents Patrick's team as they travel to Guatemala, Kosovo, and Liberia, helping human rights supporters apply sophisticated computer analysis to human rights events.

HRDAG Names New Board Member William Isaac

William Isaac joins HRDAG's Advisory Board, bringing expertise in fairness and artificial intelligence.

100 Women in AI Ethics

We live in very challenging times. The pervasiveness of bias in AI algorithms and autonomous “killer” robots looming on the horizon, all necessitate an open discussion and immediate action to address the perils of unchecked AI. The decisions we make today will determine the fate of future generations. Please follow these amazing women and support their work so we can make faster meaningful progress towards a world with safe, beneficial AI that will help and not hurt the future of humanity.

53. Kristian Lum @kldivergence


Rise of the racist robots – how AI is learning all our worst impulses

“If you’re not careful, you risk automating the exact same biases these programs are supposed to eliminate,” says Kristian Lum, the lead statistician at the San Francisco-based, non-profit Human Rights Data Analysis Group (HRDAG). Last year, Lum and a co-author showed that PredPol, a program for police departments that predicts hotspots where future crime might occur, could potentially get stuck in a feedback loop of over-policing majority black and brown neighbourhoods. The program was “learning” from previous crime reports. For Samuel Sinyangwe, a justice activist and policy researcher, this kind of approach is “especially nefarious” because police can say: “We’re not being biased, we’re just doing what the math tells us.” And the public perception might be that the algorithms are impartial.


Existe la posibilidad de que no se estén documentando todos los asesinatos contra líderes sociales

En ocasiones, las discusiones sobre ese fenómeno se centran más sobre cuál es la cifra real, mientras que el diagnóstico es el mismo: en las regiones la violencia no cede y no se avizoran políticas efectivas para ponerle fin. En medio de este complejo panorama, el Centro de Estudios de Derecho, Justicia y Sociedad (Dejusticia) y el Human Rights Data Analysis Group, publicaron este miércoles la investigación Asesinatos de líderes sociales en Colombia en 2016–2017: una estimación del universo.


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.

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