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Hissène Habré, le Pinochet Africain


The Body Counter


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.


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.


Inside a Dictator’s Secret Police


Benetech Statistical Expert Testifies in Guatemala Disappearance Case


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.”


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

kristian lum headshot 2018In 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.


Can ‘predictive policing’ prevent crime before it happens?

100x100-sciencemagHRDAG analyst William Isaac is quoted in this article about so-called crime prediction. “They’re not predicting the future. What they’re actually predicting is where the next recorded police observations are going to occur.”


What HBR Gets Wrong About Algorithms and Bias

“Kristian Lum… organized a workshop together with Elizabeth Bender, a staff attorney for the NY Legal Aid Society and former public defender, and Terrence Wilkerson, an innocent man who had been arrested and could not afford bail. Together, they shared first hand experience about the obstacles and inefficiencies that occur in the legal system, providing valuable context to the debate around COMPAS.”


Megan Price: Life-Long ‘Math Nerd’ Finds Career in Social Justice

“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.”


Improving the estimate of U.S. police killings

Cory Doctorow of Boing Boing writes about HRDAG executive director Patrick Ball and his contribution to Carl Bialik’s article about the recently released Bureau of Justice Statistics report on the number of annual police killings, both reported and unreported, in 538 Politics.


Using statistics to estimate the true scope of the secret killings at the end of the Sri Lankan civil war

In the last three days of the Sri Lankan civil war, as thousands of people surrendered to government authorities, hundreds of people were put on buses driven by Army officers. Many were never seen again.

In a report released today (see here), the International Truth and Justice Project for Sri Lanka and the Human Rights Data Analysis Group showed that over 500 people were disappeared on only three days — 17, 18, and 19 May.


The Atrocity Archives


Analyze This!


Courts and police departments are turning to AI to reduce bias, but some argue it’ll make the problem worse

Kristian Lum: “The historical over-policing of minority communities has led to a disproportionate number of crimes being recorded by the police in those locations. Historical over-policing is then passed through the algorithm to justify the over-policing of those communities.”


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." Huffington Post Politics Matt Easton September 6, 2014 Link to story on HuffPostPol Related blogpost (Updated Casualty Count for Syria) Back to Press Room

How Many People Will Get Covid-19?

HRDAG has authored two articles in Significance that add depth to discussions around infection rates.

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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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