I write and speak quite often about photographs as evidence. This is perhaps partly because I take a lot of pictures and use their EXIF data (Exchangeable Image File Format – a specific type of extended metadata) to find and categorise them. It is partly because pictures are inherently more interesting than Word files or spreadsheets, so that their hidden data makes for better stories. It is partly, perhaps mainly, because very many people take a lot of photographs every day, unconsciously pinning their devices (and therefore generally themselves) to identifiable places.
They also pin themselves to other people, that is, can inadvertently show that two or more people were in the same place at the same time if the EXIF data from two cameras are matched thanks to pictures taken at the time. The individuals don’t need pictures of each other if they both took pictures of the same view at the same moment, and an investigator who has both pictures, and perhaps the devices which were used to take them, might get a starting-point in showing a conspiracy or some kind of joint endeavour.
Nuix is good at extracting evidence from pictures, whether through EXIF data or from the content. Two recent articles by Paul Slater, Global Head of Investigation Solutions at Nuix, explore this subject in some detail. The first is called Images Are Everywhere: Nuix Investigation Workflows. It covers the ubiquity of photographs and the use of software like Nuix to cut down the task of investigators confronted by very large volumes, for example, by finding “known” pictures (not necessarily exact duplicates) which have been seen already.
The second of Paul Slater’s posts is called Rock, Paper, Scissors, Knife, Gun, Elephant gives examples of EXIF data, including the camera on which pictures were taken and the GPS location at the time of any picture. It also mentions enhancements such as skin tone identification and facial recognition.
From the basic data one can deduce more – a camera phone’s attribution to a suspect (e.g. by selfies) or or the suspect’s association with things or places, perhaps by grouping several apparently discrete items on a map.
At the end of the second article, Paul Slater addresses a point which is worth making – the fact that you can find a lot of stuff on a phone camera does not mean that you must go through it all. Analytics (plus the same common sense and proportionality which you would apply to any other source of evidence) helps keep the focus on the things likely to matter. The main use of software like the tools which Paul Slater describes is, as he puts it, “to help quickly filter down what might seem like an insurmountable volume of material and bubble to the surface the potentially relevant items to review first”.
It is also worth remembering that photographs may be a source of useful information even if you lack the metadata / EXIF data. I wrote about this in 2018 in an article called From Prague to Piccadilly Circus: drawing conclusions about a photograph without the help of metadata.
You might also use commonly available tools like reverse image finders. I have just taken from Twitter a picture of a well-known legal tweeter and run it through two reverse image finders. The first returned simply “elder”, which was less than useful. The second, however, produced a number of pictures of people including two of the right person. The contents of someone’s picture collection can allow cross-referencing beyond the devices in your hands.
For that to be useful, two elements are required. One is that you have only a small pool of pictures, where a typical device may have thousands (and you may have hundreds of devices, not much time and limited resources). The other is that you know your starting point – in my example, I had a known person and sought other pictures of that person. In many investigations, your starting-point is thousands of unnamed entities to match against thousands of others, where the point is not necessary to match A to B but to see if there are any matches at all between any person, place or thing which may give a clue. For that you need the kind of tools which Paul Slater covers in his articles.