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| Photo: James Vincent |
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| A famous edited image of a missile launch released by the Iranian government in 2008. (This image was not used in the training or testing of Adobe’s research project.) Photo: The Verge |
Experts around the world are getting increasingly worried about new AI tools that make it easier than ever
to edit images and videos — especially with social media’s power to
share shocking content quickly and without fact-checking. Some of those
tools are being developed by Adobe, but the company is also working on an antidote of sorts by researching how machine learning can be used to automatically spot edited pictures.
The company’s latest work, showcased this month at the
CVPR computer vision conference, demonstrates how digital forensics done
by humans can be automated by machines in much less time.
The research paper
does not represent a breakthrough in the field, and it’s not yet
available as a commercial product, but it’s interesting to see Adobe — a
name synonymous with image editing — take an interest in this line of
work.
Speaking to The Verge, a spokesperson for the
company said that this was an “early-stage research project,” but in the
future, the company wants to play a role in “developing technology that
helps monitor and verify authenticity of digital media.” Exactly what
this might mean isn’t clear, since Adobe has never before released
software designed to spot fake images. But, the company points to its
work with law enforcement (using digital forensics to help find missing children, for example) as evidence of its responsible attitude toward its technology.
The new research paper shows how machine learning can be used to
identify three common types of image manipulation: splicing, where two
parts of different images are combined; cloning, where objects within an
image are copy and pasted; and removal, when an object is edited out
altogether.
