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The Data Scientist Helping to Create Ethical Robots
Kristian Lum is focusing on artificial intelligence and the controversial use of predictive policing and sentencing programs.
Whatâs the relationship between statistics and AI and machine learning?
AI seems to be a sort of catchall for predictive modeling and computer modeling. There was this great tweet that said something like, âItâs AI when youâre trying to raise money, ML when youâre trying to hire developers, and statistics when youâre actually doing it.â I thought that was pretty accurate.
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 Orleansâ partnership with Palantir, but he recognized the data-mapping model at the heart of the program. âI think the data theyâre using, there are serious questions about its predictive power. Weâve seen very little about its ability to forecast violent crime,â Isaac said.
Reflections: The G in HRDAG is the Real Fuel
Rise of the racist robots â how AI is learning all our worst impulses
âIf youâre not careful, you risk automating the exact same biases these programs are supposed to eliminate,â 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 âlearningâ from previous crime reports. For Samuel Sinyangwe, a justice activist and policy researcher, this kind of approach is âespecially nefariousâ because police can say: âWeâre not being biased, weâre just doing what the math tells us.â And the public perception might be that the algorithms are impartial.
Mapping Mexicoâs hidden graves
When Patrick Ball was introduced to Iberoâs database, the director of research at the Human Rights Data Analysis Group in San Francisco, California, saw an opportunity to turn the data into a predictive model. Ball, who has used similar models to document human rights violations from Syria to Guatemala, soon invited Data CĂvica, a Mexico Cityâbased nonprofit that creates tools for analyzing data, to join the project.
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.
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.”
Data-driven crime prediction fails to erase human bias
Work by HRDAG researchers Kristian Lum and William Isaac is cited in this article about the Policing Project: “While this bias knows no color or socioeconomic class, Lum and her HRDAG colleague William Isaac demonstrate that it can lead to policing that unfairly targets minorities and those living in poorer neighborhoods.”
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.
Estimating the human toll in Syria
Megan Price (2017). Estimating the human toll in Syria. Nature. 8 February 2017. © 2017 Macmillan Publishers Limited, part of Springer Nature. All rights reserved. Nature Human Behaviour. ISSN 2397-3374.
DATNAV: New Guide to Navigate and Integrate Digital Data in Human Rights Research
DatNav is the result of a collaboration between Amnesty International, Benetech, and The Engine Room, which began in late 2015 culminating in an intense four-day writing sprint facilitated by Chris Michael and Collaborations for Change in May 2016. HRDAG consultant Jule KrĂŒger is a contributor, and HRDAG director of research Patrick Ball is a reviewer.
Predictive policing violates more than it protects
William Isaac and Kristian Lum. Predictive policing violates more than it protects. USA Today. December 2, 2016. © USA Today.
Can âpredictive policingâ prevent crime before it happens?
HRDAG 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.”
Amnesty International Reports Organized Murder Of Detainees In Syrian Prison
Reports of torture and disappearances in Syria are not new. But the Amnesty International report says the magnitude and severity of abuse has “increased drastically” since 2011. Citing the Human Rights Data Analysis Group, the report says “at least 17,723 people were killed in government custody between March 2011 and December 2015, an average of 300 deaths each month.”
Cifra de lĂderes sociales asesinados es mĂĄs alta: Dejusticia
Contrario a lo que se puede pensar, los datos oficiales sobre lĂderes sociales asesinados no necesariamente corresponden a la realidad y podrĂa haber mucha mayor victimizaciĂłn en las regiones golpeadas por este flagelo, segĂșn el mĂĄs reciente informe del Centro de Estudios de Justicia, Derecho y Sociedad (Dejusticia) en colaboraciĂłn con el Human Rights Data Analysis Group.
Counting The Dead: How Statistics Can Find Unreported Killings
Ball analyzed the data reporters had collected from a variety of sources â including on-the-ground interviews, police records, and human rights groups â and used a statistical technique called multiple systems estimation to roughly calculate the number of unreported deaths in three areas of the capital city Manila.
The team discovered that the number of drug-related killings was much higher than police had reported. The journalists, who published their findings last month in The Atlantic, documented 2,320 drug-linked killings over an 18-month period, approximately 1,400 more than the official number. Ballâs statistical analysis, which estimated the number of killings the reporters hadnât heard about, found that close to 3,000 people could have been killed â more than three times the police figure.
Ball said there are both moral and technical reasons for making sure everyone who has been killed in mass violence is counted.
âThe moral reason is because everyone who has been murdered should be remembered,â he said. âA terrible thing happened to them and we have an obligation as a society to justice and to dignity to remember them.â
Lies, Damned Lies, and “Official” Statistics
Megan Price and Maria Gargiulo (2021). Lies, Damned Lies, and “Official” Statistics. Health and Human Rights Journal. 24 June, 2021. © Health and Human Rights Journal.
The True Dangers of AI are Closer Than We Think
William Isaac is quoted.