Video review: EyeEm magazine

by Steve Watson in January 2017

I try to keep these video reviews under two and a half minutes, and when they run longer it’s a sure sign that I’m struggling to put my finger on something. That’s what happened with EyeEm magazine this week – a heavily conceptual title that seeks to prove amongst other things that an algorithm can recognise beauty.

As you’ll see from the video below, I’m not sure they quite managed to do that. But I’m also aware of my own very human bias, and a well-placed Baudelaire quote reminds us that a little over 100 years ago, photography itself was seen as an imposition on the arts that should be defended against:

“If photography is allowed to supplement art in some of its functions, it will soon have supplanted or corrupted it altogether… its true duty is to be the servant of the sciences and arts – but the very humble servant, like printing or shorthand, which have neither created nor supplemented literature.”

The editors at EyeEm are aware of the feathers they will ruffle in making a magazine like this, but that doesn’t hold them back from declaring that a second renaissance is here, “From the brushes and chisels of the old world to the AI and machine learning of the next frontier…”

But in this magazine the technological disruption is not focused on creation; the cameras we use to take pictures on our phones today are clearly very different to the machines Baudelaire would have recognised, but their structure is essentially the same in that they use lenses to focus light on a given point.

It seems to me that the massive disruption coming from technology in this case is in curation; now that almost everybody is armed with a camera all day every day, giving us the power to capture and share images, we need machines to intervene and make sense of it all. EyeEm are setting themselves a hard target in their mission to create a machine that can recognise beauty, but maybe that’s really just there to pique the interest of casual observers like me. Because there’s no arguing that what they have created is a machine that’s able to automatically recognise and sort images, in doing so creating associations that would not otherwise have existed.

Take a look at the video below to see the results for yourself…

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