Damned Lies & Criminal Sentencing Using Evidence-Based Tools

By: John Lightbourne

The boom of big data and predictive analytics has revolutionized business. eHarmony matches customers based on shared likes and expectations for romance, and Target uses similar methods to strategically push its products on shoppers. Courts and Departments of Corrections have also sought to employ similar tools. However, the use of data analytics in sentencing raises a host of constitutional concerns. In State v. Loomis, the Wisconsin Supreme Court was faced with whether the use of an actuarial risk assessment tool based on a proprietary formula violates a defendant’s right to due process where the defendant could not review how the various inputs were weighed. The opinion attempts to save a constitutionally dubious technique and reads as a warning to lower courts in the proper use of predictive analytics. This article explores certain equal protection and due process arguments implicated by Loomis.
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Cite: 15 Duke L. & Tech. Rev. 327

Authenticity and Admissibility of Social Media Website Printouts

By: Wendy Angus-Anderson

Social media posts and photographs are increasingly denied admission as evidence in criminal trials. Courts often cite issues with authentication when refusing to admit social media evidence. Cases and academic writings separate recent case law into two approaches: The Maryland Approach and the Texas Approach. The first method is often seen as overly skeptical of social media evidence, setting the bar too high for admissibility. The second approach is viewed as more lenient, declaring that any reasonable evidence should be admitted in order for a jury to weigh its sufficiency. This Brief addresses the supposed differences between the two sets of cases and suggests that courts are not actually employing two distinct approaches. The Maryland Approach courts are not holding social media content to a higher standard than the Texas Approach courts, but are merely responding to a lack of evidence connecting the proffered content to the purported author.

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Cite: 14 Duke L. & Tech. Rev. 33