In the common law of torts, res ipsa loquitur (Latin for “the thing speaks for itself”) is a doctrine that infers negligence from the very nature of an accident or injury in the absence of direct evidence on how any defendant behaved. Although modern formulations differ by jurisdiction, common law originally stated that the accident must satisfy the necessary elements of negligence: duty, breach of duty, causation, and injury. In res ipsa loquitur, the elements of duty of care, breach, and causation are inferred from an injury that does not ordinarily occur without negligence.
Res ipsa loquitur is often confused with prima facie (“at first sight”), the common law doctrine that a party must show some minimum amount of evidence before a trial is worthwhile.
What on earth does this have to do with Forensic Content Analysis? In so many cases, attorneys argue and judges agree that a video / image is what it is – that it speaks for itself – that an analyst is not needed to explain crucial elements of the evidence item – that the content does not need to be analyzed.
Take this image:
The upper section is a depiction of the Chuvash State Opera and Ballet Theater in Cheboksary, Russia. This icon of Brutalist architecture is one of the great examples of Brutalism in Russia, and a must see for tourists.
The lower section layers in (adds, or Photoshops) elements from Star Wars.
Under res ipsa loquitur – the lower section speaking for itself – it could be argued that Imperial troops have occupied central Russia. This is, of course a ridiculous idea. Here, we’re using absurdity to illustrate the absurd.
In terms of modern multimedia evidence – can the file indeed speak for itself? Is the object of interest an artifact of compression, a result of noise, or an element of the scene? How would you know? You would engage an analyst.
Any case involving Forensic Content Analysis must necessarily start with a “ground truth assessment;” what are the elements of the area of interest. A macro block analysis may be performed on a video file. Is the area of interest populated by lossless encoded data, copied data, predicted data, or error? How would you know? You would know by using validated tools and your trained mind / eyes.
In Authentication cases, this is no different. Fakes are getting sophisticated and easier to perform. Analysts need valid tools, training, and education. This is why the training / educational sessions that we offer move beyond simple button pushing into a deeper understanding of the underlying technology as well as how forgeries are created in the first place. Because “false positives” and “false negatives” can be frequent in authentication tools that are built around data sets, one must know how to interpret results as well as how to successfully validate them across a wider variety of methods that do not only involve the software being used. This is why statistics goes hand in hand with the domains of analysis.
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