The Value of Subconscious and Conscious Data for Digital Asset Management

I have recently published a new DAM News feature article: Subconscious and Conscious Data: Where AI & Machine Learning Could Create Genuine Value for DAM.  As alluded to in the title, this describes a method for gleaning inferences and predictive behavioural signals using a model that is based on how human beings store information and contextualise it:

By approaching DAM and Machine Learning from a data and metadata perspective (subconscious and conscious data) there is a far more realistic possibility of replicating the human interpretation skills that are essential for generating genuinely useful automated metadata. If it were possible to digitally capture every interaction that an experienced digital asset manager had with a collection of digital assets you have some of the raw data that would provide the potential to reverse engineer their behaviour and reproduce it more faithfully.” [Read More]

As with a number of other articles I have written about Artificial Intelligence and Machine Learning as it relates to DAM, I still contend that both vendors and consultants have no clear strategy for getting useful results from either.  The fundamental underlying reasons are a) they lack any real motivation to do so and b) they apply linear and over-reductive reasoning which limits their ability to understand the nature of the problem properly.

There is a clear opportunity to innovate here (and to obtain a significant competitive advantage as a result).  Based on the evidence of recent years, however, I am pessimistic about whether many (or even any) of the current market participants have the capacity to do anything tangible about it.  With that said, I am certain that an entity (who is probably not currently active in DAM) will have figured this out already and is already working on something like the model I have described.

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