Computational Tagging

In my SXSW panel this year, Ramesh Jain and Anna Dickson and I delved into the implications of Artificial Intelligence (AI) becoming a commodity, which will be a commonplace reality by the end of 2017.  We looked at several classes of services and considered what they were good for.

I’ve been spending a lot of time on the subject over the last few months writing The DAM Book 3. Clearly AI will be important in collection management and the deployment of images for various types of communication.

But I  hate using the term AI to describe the array of services that help you make sense of your photos. There’s actually a bunch of useful stuff that is not technically AI. Adding date or GPS info is definitely not AI. And linking to other data (like a wikipedia page) is not really AI. ( It’s actually just linking). Machine Learning and programmatic tagging comes in a lot of forms – some is really basic, and some is complex.

The term Computational Imaging was pretty obscure when the last version of The Dam Book was published, but it’s become a very common term. I think this is a useful concept to extend to the whole AI/Machine Learning/Data Scraping/Programmatic Tagging stack.

In The DAM Book 3, I’m using the term Computational Tagging to refer to all the computer-based tagging methods that involve some level of automation. This runs from the tags made by the computer in my camera to the sophisticated AI environments of the future. At the moment, it’s not widely-used term (Google shows 138 instances on the web), but I think it’s the best general description for the automatic and computer-assisted tagging that are becoming an essential part of working with images.

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