AI, despite its negative reputation, has the potential to bring good into the world. One of its positive applications is helping solve crimes, as demonstrated by a professor who used machine learning to analyze 20 years’ worth of sexual assault reports. Rachel Lovell, a criminologist from Cleveland State University, trained AI to detect bias in the reports and predict which cases would lead to prosecutions. Surprisingly, officers who displayed bias in their writing had a higher success rate in solving cases.
According to Lovell, these officers were able to capture the trauma of rape in their reports, resulting in more detailed documentation. On the other hand, reports that were not successful were shorter and used phrases like “insufficient evidence” or “no further leads,” which suggested a lack of activity from the victims. Lovell created a glossary to guide the wording used in incident reports and believes that AI can help improve conviction rates by generating more effective reports. “A rape report should not be written using the same tone as a report of a stolen bicycle,” she emphasized.
Police departments are already utilizing AI in various ways. For instance, technology showcased at a police conference in Dubai included sentient analysis software for interpreting moods during interrogations and a Segway equipped with a machine gun. However, these technologies have been found to exhibit bias against minorities, exacerbating the overpolicing and underprotection of people of color. Lovell raises concerns about the lack of diversity in STEM jobs, which may result in inherent biases within AI systems. (AI also holds promise for detecting breast cancer).
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