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Algorithms 'consistently' more accurate than people in predicting recidivism, study says:
In a study with potentially far-reaching implications for criminal justice in the United States, a team of California researchers has found that algorithms are significantly more accurate than humans in predicting which defendants will later be arrested for a new crime.
[...] "Risk assessment has long been a part of decision-making in the criminal justice system," said Jennifer Skeem, a psychologist who specializes in criminal justice at UC Berkeley. "Although recent debate has raised important questions about algorithm-based tools, our research shows that in contexts resembling real criminal justice settings, risk assessments are often more accurate than human judgment in predicting recidivism. That's consistent with a long line of research comparing humans to statistical tools."
"Validated risk-assessment instruments can help justice professionals make more informed decisions," said Sharad Goel, a computational social scientist at Stanford University. "For example, these tools can help judges identify and potentially release people who pose little risk to public safety. But, like any tools, risk assessment instruments must be coupled with sound policy and human oversight to support fair and effective criminal justice reform."
The paper—"The limits of human predictions of recidivism"—was slated for publication Feb. 14, 2020, in Science Advances. Skeem presented the research on Feb. 13 in a news briefing at the annual meeting of the American Association for the Advancement of Science (AAAS) in Seattle, Wash. Joining her were two co-authors: Ph.D. graduate Jongbin Jung and Ph.D. candidate Zhiyuan "Jerry" Lin, who both studied computational social science at Stanford.
More information:
Z. Lin, et al. The limits of human predictions of recidivism [open], Science Advances (DOI: 10.1126/sciadv.aaz0652)
(Score: 2) by FatPhil on Thursday February 20 2020, @03:04AM (1 child)
> Adopted children who came from two black parents had an average IQ at age 17 of 83.7. Adopted children who came from two white parents had an average IQ at age 17 of 101.5.
Dending what you mean by "came from", one of those sets wasn't even in the study, according to your description of it:
If you meant "genetically from", the there were no adopted "black children" who "came from two white parents";
If you meant "raised by", the there were no adopted "black children" who "came from two black parents".
Clarity is paramount when communication science. You do not display clarity, so you're not communicating science with your above post, one has to even question whether you've understood the science, if you're so unable to communicate it.
Great minds discuss ideas; average minds discuss events; small minds discuss people; the smallest discuss themselves
(Score: 0) by Anonymous Coward on Thursday February 20 2020, @05:26AM
I think it was obvious I meant genetically from. The distinction was not tautological. It was to draw the distinction between those genetically from 2 black parents, or 1 black parent and 1 white parent. The "accidental" control in that study, makes this an even more critical point of distinction.