Can you believe what you’re seeing? Personal identification of suspects is a major crime fighting tool. Scientists will soon be able to identify your hair color from your DNA, so all criminals will have to immediately use hair dye or wear a wig.
In PhysOrg.com, Katharine Gammon quotes forensic expert Manfred Kayser as saying, "Tools that allow us to know what an unknown person looks like can be incredibly useful." You can teach your computer to do lots of things, but can you train it to do CSI-type forensics? On 6 May 2004, a Portland, Oregon lawyer named Brandon Mayfield was arrested for his alleged involvement in the terrorist bombings of four commuter trains in Madrid. The sole evidence against him was a partial fingerprint found on a plastic bag. The FBI did CSI on the case: Their Integrated Automated Fingerprint Identification System had identified Mayfield as a possible match, and three FBI fingerprint experts as well as an outside expert confirmed the identification. Spanish authorities, however, strenuously argued that the fingerprint belonged not to Mayfield but to an Algerian with a criminal record, Spanish residency, and known terrorist links.
They were right. The US government eventually agreed to pay Mayfield $2 million for the mistake and issued a formal apology. This is only one of countless examples of forensic analysis gone wrong. And yet, such traditional forms of forensic evidence can be very helpful, provided they are examined objectively and that the uncertainty of the results can be measured and properly explained. This is where computers have a role to play. The relatively new field of computational forensics has sprung up to address this. It’s not yet mainstream, but then, we all remember from the O.J. Simpson trial, how DNA data was discounted as evidence at first. Eventually the courts may allow computational forensics to be applied in actual criminal trials as well.
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