The US Bureau of Justice collects information on deaths during arrest, and HRDAG determined the efforts were incomplete. The conclusion: Approximately one third of all Americans killed by strangers are killed by police.
Our newest Data Science Fellow, Will Taylor, is currently a doctoral student in political science and public policy at the University of Michigan.
“Led by the nonprofit Human Rights Data Analysis Group (HRDAG), the process began with creating a merged dataset of “fully identified victims” to avoid double counting. Only casualties whose complete details were listed — such as their full name, date of death and the governorate they had been killed in — were included on this initial list, explained Megan Price, executive director at HRDAG. If details were missing, the victim could not be confidently cross-checked across the eight organizations’ lists, and so was excluded. This provided HRDAG and the U.N. with a minimum count of individuals whose deaths were fully documented by at least one of the different organizations. … “
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Q3. What are the steps in an MSE analysis?
Q4. What does data collection look like in the human rights context? What kind of data do you collect?
Q5. [In depth] Do you include unnamed or anonymous victims in the matching process?
Q6. What do you mean by "cleaning" and "canonicalization?"
Q7. [In depth] What are some of the challenges of canonicalization? (more…)
Boston Police deployed SWAT teams disproportionately to Black neighborhoods, sometimes raiding homes with young children. HRDAG extracted data revealing just how disproportionate.
Causal inference methods show that for indigent clients, money bail increases their likelihood of a guilty conviction.
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The institution’s objectives were to learn the truth about what happened during the armed conflict.
HRDAG's advisory board has added three new members.
The datasets contributed by 30+ organizations do a wonderful job of tallying the violence that was observed—but they don’t account for the violence that nobody witnessed or documented.
2021 Rafto Prize Videos
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Trina Reynolds-Tyler's internship at HRDAG helped her use data science to find patterns in state-sanctioned violence.
Tools like Compas allegedly help judges predict future criminal activities and eliminate bias. HRDAG and partners showed how the tools recycle bias.
Identifiers being sequential could make possible estimations of the population of detained children.
We aim to produce code that is clear, replicatable across machines and operating systems, and that leaves an easy-to-follow audit trail.
The primer addresses what pretrial risk assessment is and what the research supports.
“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.
If you’d like to stay informed about HRDAG events, blogposts, and news, connect with us on Twitter, Facebook or through our RSS feed. We also have a LinkedIn page.
You may contact us directly via email at info @ hrdag.org.
A note for persons in search of assistance with specific human rights cases: We are very sorry for your troubles and your suffering; however, HRDAG does not take on casework. If you need help with a human rights case, you might consider requesting it from the International Committee of the Red Cross (www.icrc.org).
Photo: U.S. National Archives
“I was always a math nerd. My mother has a polaroid of me in the fourth grade with my science fair project … . It was the history of mathematics. In college, I was a math major for a year and then switched to statistics.
I always wanted to work in social justice. I was raised by hippies, went to protests when I was young. I always felt I had an obligation to make the world a little bit better.”
IPFS is a peer-to-peer storage network that promotes the resiliency, immutability, and auditability of data. This README explains code written to shepherd the files from janky external USB drives to IPFS.
