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You shouldn’t believe your eyes: how to identify fake images online

In today’s post-truth society, it’s more important than ever to verify the images you share online.

A photo of Jeremy Corbyn walking through a train carriage of empty seats is many things, but it is not faked. The image, taken from CCTV footage of the 11am train from London to Newcastle on 11 August, hit the headlines last week after Virgin refuted the Labour leader’s claims that he couldn’t find a seat on its service.

Due to the highly-politicised nature of this image (yes, really) many people were quick to question its legitimacy. “It's in the must be true! Cos technology can't enable anyone to airbrush or photo shop things like seat tickets yet,” wrote a commenter on the New Statesman’s own Facebook page, with another noting that Virgin took two weeks to release the images.

It is true that in today’s post-truth society we should question photographs that we see online, particularly those that arguably have an agenda. Many people find it easy to Photoshop an image, but you don’t have to create a fake image to be complicit in the damage they cause. After Hurricane Sandy in 2012, researchers found that 86 per cent of tweets spreading fake images were retweets, not original tweets. Before you share an image online, it is important to analyse its legitimacy. Great. But how?

“Let me emphasise that there is no single test that will tell you everything you’d want to know about the provenance of an image,” says Kevin Connor, the ex-vice president of product management at Adobe and founder of Fourandsix Technologies, a company dedicated to analysing the authenticity of digital images.

“Instead, you really need to play detective, searching for a variety of clues that can provide you with an indication of where an image came from and what has happened to it. One of the first and most useful things you can do is to perform a reverse image search, using a service like Google Images or TinEye. You may want to use both, because they sometimes provide different results.

“If you find any matches, look for the earliest appearance. If the earlier version looks different than the version you have, then your version is probably modified. Even if the image doesn't appear modified, you may discover that the image is not what it claims to be. For example, it's not uncommon for an image to appear on social media claiming to be of a crowd in a recent protest, but reverse image searches then reveal that the image was actually taken in a completely different city years earlier.”

The results of a Google reverse image search on the alledged Hurricane Sandy photograph

Connor became interested in analysing the authenticity of images because he spent over 15 years driving the Photoshop product line at Adobe and found that journalists and law enforcement professionals frequently questioned him on how to tell when images were manipulated.

“I didn't have great answers for them,” he says, “but then I became aware of the research of Hany Farid from Dartmouth College. He was the first person to seriously study algorithms for authenticating photographs. When I was leaving Adobe and deciding what to do next, I decided to team up with Hany and see if we could productise his work.”

One of the main products resulting from this collaboration is, a website that allows photographers to certify that their images are original, unmodified files from their camera. This is useful if you want to prove to an online beau that you aren’t catfishing them, or that the trainers you’re selling on eBay are the real deal. Unfortunately, the service is limited.

“For the typical files you find online or in social media, izitru won't be very useful, because these files are generally not the original files captured from the camera,” says Connor. “For example, Facebook and Twitter never serve up the original image file that someone uploads. It always gets re-saved at a smaller size, with most of the metadata stripped out. Izitru is most useful if you know the person who is sharing the photo, and you can ask for the original. They can either upload it to izitru themselves as proof, or they can send it to you so that you can upload it.”

Reverse image and izitru are both accessible and reliable because you don’t need to be an expert to use them. When it comes to image forensics and analysing the make-up of an image, however, Farid warns me: “There is little the average person can do to reliably determine that a photo is fake.”

“If you do know more about image editing software, then you could start looking for clues within the image – traces that the image editing tools leave behind, or mistakes that the editor made,” says Connor. “This is difficult, though, and many people reach inappropriate conclusions.” This was best illustrated during the 2013 World Press Photo of the Year, when Dr Neal Krawetz, a photography forensics expert, argued the winning image was a composite of various photos. Connor, Fadid and Eduard de Kam from the Nederlands Instituut voor Digitale Fotografie were called in to forensically analyse the photo, and verified that it was real.

De Kam says the easiest way to analyse an image is to get your hands on the raw file, something that can often be difficult. “If there is no raw file, the highest resolution is what I have to work with,” he says. “That means slowly moving through the image trying to find errors, a slow and not very certain process.

That’s not something you or I can easily do, and the meme “This looks shopped, I can tell from some of the pixels” mocks those who think they can. There are, however, a variety of services online that claim to be able to automatically detect fake images. Connor warns against many of these.

“In collaboration with Hany while I was still at Adobe we demonstrated a plug-in that would automatically point out regions in an image that might have been cloned, he says. “We chose not to release this, however, because we felt that in novice hands it might lead people to incorrect conclusions. That's because most of these techniques are not 100 per cent conclusive, and you still need to make an educated judgment about the results.

One of the most common ways websites and internet sleuths will claim to delegitimise an image is through error-level analysis (ELA). ELA shows the differing levels of compression throughout an image, in a way that ostensibly highlights where an image has been changed. For example, if I run this still of Harry Potter through, it will rightly highlight the differing compression levels on the image of Danny DeVito I have pasted onto the Dursleys’ heads in their family portrait.

Yet although this seems pretty irrefutable, Connor warns against ELA. “We simply don't place much value in that test because its results are especially inconclusive,” he says. “People like to use it because it's available online for free and it provides visually interesting results, but these results don't have a lot of value.

“Firstly, it just provides you with a pretty picture without giving you much indication of how to interpret it. Yes, you're told to look for areas of the image that look different than the rest, but how is someone supposed to judge what is ‘different’?

“Additionally, because the technique is testing for something that's only tangentially related to image editing, it's prone to producing unacceptable levels of both false positives and false negatives. In other words, it's not very difficult to find edited images that don't product suspicious results in ELA, and it's also not too difficult to find unedited images that do produce suspicious results.

“At best, ELA might be useful for directing your attention to certain areas of the image that may deserve future scrutiny, but you shouldn't make any final conclusions based on ELA alone.”

When it comes to analysing an image then, it might be best to use the cheapest and most user-friendly computer at your disposal: your brain.

“It is harder to fake an image then to write total nonsense,” says de Kam. “So we should always keep thinking whatever we see, whatever we read, how much sense does this make?”

Many fake images that spread online aren’t fake in the sense that they’ve been manipulated, but fake in that the stories attributed to them are false. The first step, therefore, is to apply critical thinking. Are there any other images that can corroborate the one you’re looking at? For example, by finding other images from the day Hillary Clinton was photographed next to a woman wearing an "I'm with stupid" t-shirt, we can easily see the image was faked. 

Another important question to ask is whether the source reliable, and what agenda they might have. Once you've exhausted your brain, there are a multitude of low-tech services that can help you find answers, such as and Twitter accounts like @HoaxOfFame or @PicPedant, which are dedicated to uncovering fake images and stories.

Being sceptical and asking questions are therefore most people’s best options. The Defense Advanced Research Projects Agency (DARPA) has recently begun a large research effort into image forensics, and, with Hany Farid working on the team, might develop a way to automatically detect image manipulation.

“For now, though,” says Connor, “it's still some tricky detective work.” 

Amelia Tait is a technology and digital culture writer at the New Statesman.

Getty/Glu Games/New Statesman
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The second coming of Gordon Ramsay

A star is reborn. 

It would be a lie to say that Gordon Ramsay ever disappeared. The celebrity chef made his television debut in 1997 and went on to star in shows in 1998, 2001, 2004, 2005, 2006, 2007, 2009, 2010, 2011, 2012, 2013, 2014, 2015, 2016, and 2017. There hasn’t been a lull in Ramsay’s career, which has arguably gone from strength to strength. In 2000, he was cooking for Vladimir Putin and Tony Blair – in 2008, he ate the raw heart of a dead puffin.

Left: Gordon Ramsay shaking hands with Vladimir Putin. Right: Gordon Ramsay hugging a puffin (different from the one he ate).

Yet we are, undeniably, in the middle of a Ramsay renaissance. How? How could a man that conquered the last twenty years of cookery-based television have an upsurge in popularity? There are only so many television channels – so many amateur donkey chefs. Wrong. The internet has enabled a Ramsay resurgence, the second act of a play overflowing with blood, sweat, and French onion soup.


We all, of course, know about Gordon’s Twitter account. Although started in 2010, the social media profile hit the headlines in February this year when Ramsay began rating food cooked by the world’s amateur-amateur chefs. But other elements of Ramsay’s internet celebrity are more miraculous and mysterious.

His official YouTube channel uploads, on average, three videos a week. Decades old clips from Kitchen Nightmares accumulate over three million views in as many days. A 15,000 follower-strong Facebook fan page for the show – which premiered in 2007 and ended in 2014 – was set up on 19 June 2017.

Wow, wow, wow, wow. Wow.       

A Google Trends graph showing an April 2017 surge in Ramsay's popularity, after a decline in 2014.                                      

What makes a meme dank? Academics don’t know. What is apparent is that a meme parodying Gordon Ramsay’s fury over missing lamb sauce (first aired on Hell’s Kitchen in 2006) had a dramatic upsurge in popularity in December 2016. This is far from Gordon’s only meme. Image macros featuring the star are captioned with fictitious tirades from the chef, for example: “This fish is so raw… it’s still trying to find Nemo”. A parody clip from The Late Late Show with James Cordon in which Ramsay calls a woman an “idiot sandwich” has been watched nearly five million times on YouTube.

And it is on YouTube where Ramsay memes most thrive. The commenters happily parrot the chef’s most memable moments, from “IT’S RAW” to the more forlorn “fuck me” after the news something is frozen. “HELLO MY NAME IS NINOOOOO!” is an astonishingly popular comment, copied from a clip in which a Kitchen Nightmares participant mocks his brother. If you have not seen it – you should.

But what does all this mean for Ramsay’s career? His YouTube channel and Facebook page are clearly meticulously managed by his team – who respond to popular memes by clipping and cutting new videos of classic Ramsay shows. Although this undoubtedly earns a fortune in ad revenue, Ramsay’s brand has capitalised on his internet fame in more concrete ways. The chef recently voiced Gordon Ramsay Dash, a mobile game by Glu Games Inc in which you can cook with the star and he will berate or praise you for your efforts. Ten bars of gold – which are required to get upgrades and advance in the game – cost 99p.

Can other celebrity chefs learn from Ramsay? A generation will never forgive that twisted, golden piece of meat, Jamie Oliver, for robbing them of their lunch time Turkey Twizzlers. But beyond this, the internet’s love is impossible to game. Any celebrity who tried to generate an online following similar to Ramsay’s would instantly fail. Ramsay’s second coming is so prolific and powerful because it is completely organic. In many ways, the chef is not resposible for it. 

In truth, the Ramsay renaissance only worked because it was - though the chef himself would not want to admit it - completely raw.

Amelia Tait is a technology and digital culture writer at the New Statesman.