275 results for search: Как помогает психоанализ больше в insta---batmanapollo/feed/inter-rater-reliability
USA
Skoll World Forum 2018
New publication in BIOMETRIKA
Celebrating Women in Statistics
In 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.
Data ‘hashing’ improves estimate of the number of victims in databases
But while HRDAG’s estimate relied on the painstaking efforts of human workers to carefully weed out potential duplicate records, hashing with statistical estimation proved to be faster, easier and less expensive. The researchers said hashing also had the important advantage of a sharp confidence interval: The range of error is plus or minus 1,772, or less than 1 percent of the total number of victims.
“The big win from this method is that we can quickly calculate the probable number of unique elements in a dataset with many duplicates,” said Patrick Ball, HRDAG’s director of research. “We can do a lot with this estimate.”
Welcoming Our New Data Scientist
HRDAG and #GivingTuesday 2018
The UDHR Turns 70
HRDAG Report on Disappeared Tamils in Army Custody in Sri Lanka
500 Tamils forcibly disappeared in three days, after surrendering to army in 2009
A new study has estimated that over 500 Tamils were forcibly disappeared in just three days, after surrendering to the Sri Lankan army in May 2009.
The study, carried out by the Human Rights Data Analysis Group and the International Truth and Justice Project, based on compiled lists which identify those who were known to have surrendered, estimated that 503 people had been forcibly disappeared between the 17th– 19th of May 2009.
500 Tamils disappeared in Army custody — New Study
The Sri Lankan army must explain to the families of the disappeared and missing what happened to an estimated 500 Tamils who disappeared in their custody at the war end on/around 18 May 2009, said two international NGOs who have been collating and analysing lists of names.
Sri Lanka has one of the largest numbers in the world of enforced disappearances but these 500 represent the largest number of disappearances all in one place and time in the country. For a detailed account of the process of estimating the 500 please see: “How many people disappeared on 17-19 May 2009 in Sri Lanka?” .
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.
New report published on 500 Tamils missing while in Army custody
The International Truth and Justice Project and HRDAG have published a report on 500 Tamils who disappeared while in Army custody in Sri Lanka in 2009.
The report is titled “How many people disappeared on 17-19 May 2009 in Sri Lanka?” and Patrick Ball, director of research at HRDAG, is the lead author.
Counting the Dead in Sri Lanka
Las cifras de la CVR en el 2019
HRDAG Testimony in Guatemala Retrials
Welcoming Our 2019 Data Science Fellow
The World According to Artificial Intelligence (Part 1)
The World According to Artificial Intelligence: Targeted by Algorithm (Part 1)
The Big Picture: The World According to AI explores how artificial intelligence is being used today, and what it means to those on its receiving end.
Patrick Ball is interviewed: “Machine learning is pretty good at finding elements out of a huge pool of non-elements… But we’ll get a lot of false positives along the way.”
The World According to Artificial Intelligence (Part 2)
The World According to Artificial Intelligence – The Bias in the Machine (Part 2)
Artificial intelligence might be a technological revolution unlike any other, transforming our homes, our work, our lives; but for many – the poor, minority groups, the people deemed to be expendable – their picture remains the same.
Patrick Ball is interviewed: “The question should be, Who bears the cost when a system is wrong?”
