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An algorithm is not just a computer thing. "It's a set of rules to be followed in calculations or other problem-solving operations," the dictionary says. In other words, it's like logic.
But some lawyers and judges get all wound up in the cross-over from human logic to computer algorithms. Some say you can't you win an argument with just an algorithm.
The debate came up in State v. Loomis, when the Wisconsin Supreme Court upheld the use of an algorithm to weigh predictive risk at sentencing because the defendant could have challenged the accuracy of data fed into the algorithm. But in an article for The Colorado Technology Law Journal, Anne L. Washington questioned the court's reasoning. She said the judges "ignored the computational procedures that processed the data within the algorithm."
"How algorithms calculate data is equally as important as the quality of the data calculated," she said. "The arguments in Loomis revealed a need for new forms of reasoning to justify the logic of evidence-based tools."
Washington, an assistant professor of data policy at New York University, says "data science reasoning" could provide ways to dispute predictive algorithms. She says scholars have overlooked how to frame courtroom debates about them.
It's about knowing how the technology works, she suggests. Or in sanitation workers' parlance -- garbage in, garbage out.
In Loomis, the bigger issue was due process. Defense attorneys argued that algorithmic sentencing violated the offender's due process rights because they could not verify the risk prediction. The court recognized the challenge, but said legal process must adapt to technology. Some concerns, the judges said, may be alleviated in the future.
"Different and better tools may be developed.," they said. "As data changes, our use of evidence-based tools will have to change as well."
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