This is from a Harvard University study. Leftists around the nation are working hard to allow criminals back on the streets with little incentive to show up for a trial. This is called the NO CASH BAIL movement. Under this, you get arrested, smile at a judge and an algorithm will decide if you go back to a life of crime or stay in jail. Remember the old adage of computers, “garbage in, garbage out”. Will the system be honestly set or biased in favor of the criminals?
“When predicting flight and danger, many tools use inexact and overly broad definitions of those risks. When predicting violence, no tool available today can adequately distinguish one person’s risk of violence from another. Misleading risk labels hide the uncertainty of these high-stakes predictions and can lead judges to overestimate the risk and prevalence of pretrial violence. To generate predictions, risk assessments rely on deeply flawed data, such as historical records of arrests, charges, convictions, and sentences.”
Once again, the Left is working hard to make more victims. Do you expect anything less?
Technical Flaws of Pretrial Risk Assessments Raise Grave Concerns
Martha Minow, John Bowers, Jonathan Zittrain, Harvard University, 7/17/19
prominent researchers from MIT, Harvard, Princeton, NYU, UC Berkeley and Columbia — including Berkman Klein Directors Martha Minow and Jonathan Zittrain — have signed an open statement of concern regarding the use of actuarial risk assessment as a means of lowering pretrial jail populations.
Read the signed statement (PDF)
Actuarial pretrial risk assessments suffer from serious technical flaws that undermine their accuracy, validity, and effectiveness. They do not accurately measure the risks that judges are required by law to consider. When predicting flight and danger, many tools use inexact and overly broad definitions of those risks. When predicting violence, no tool available today can adequately distinguish one person’s risk of violence from another. Misleading risk labels hide the uncertainty of these high-stakes predictions and can lead judges to overestimate the risk and prevalence of pretrial violence. To generate predictions, risk assessments rely on deeply flawed data, such as historical records of arrests, charges, convictions, and sentences.
This data is neither a reliable nor a neutral measure of underlying criminal activity. Decades of research have shown that, for the same conduct, African-American and Latinx people are more likely to be arrested, prosecuted, convicted and sentenced to harsher punishments than their white counterparts. Risk assessments that incorporate this distorted data will produce distorted results. These problems cannot be resolved with technical fixes. We strongly recommend turning to other reforms.
This statement of concern has been submitted to the following jurisdictions for consideration:
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