I’m not sure I’ve ever following a story with the combination of awe and trepidation as AI for the past several years. The potential job displacement alone is staggering.
In the past, as a marketing person who trades in creative thinking, I’ve clung to the idea that however far technology might progress, jobs based in aesthetic judgement were in the clear zone for the foreseeable future.
Machine learning has been great on tasks with well-defined goals, like determining which ads in a campaign to give the most impressions to based on audience response. When the decision is highly subjective, though, it’s been a different situation. But that’s a barrier being broken through. Making the question not if creative jobs will be impacted, but how.
The recent AI experiment by Google is an example.
They turned an experimental deep learning system loose on their database of Street View images with the goal of artistic curation.
Per their blog post.
It mimics the workflow of a professional photographer, roaming landscape panoramas from Google Street View and searching for the best composition, then carrying out various postprocessing operations to create an aesthetically pleasing image.
Here are two of hundreds of beautiful images the AI selected, cropped and processed.
They had a team of professional photographers judge the results of the AI along side a range of other non-AI photos, with impressive results.
A threat, a tool, or both?
There should be a lot of ways to use AI for creative development. What I find interesting in the Google example is the training of the AI system. Talk to any AI expert and they’ll emphasize the importance of having good training data. Garbage in, garbage out.
Whatever you put into the system, that becomes the measuring stick. The Google team pulled the training database from several photography communities, using the human-generated rating system to define the aesthetic taste. (If you want the gory details, you can read the full research paper.)
So the tastes of the photographic communities drove the training data which defined the results. But presumably you could use whatever data you want to train the system, and that’s the direction it will go in. Your new creative brief is the training data. Deployed on the full data set, off it goes generating concepts or creatives or whatever. In remarkable volume. And it never complains or causes HR nightmares.
Sounds like a creative director’s dream. Or a chief marketing officer’s.
Using AI to help creatives generate more ideas seems pretty obvious. You start a project with 100s of loosely-relevant-but-possibly-tangentially-interesting ideas already on the board.
And AI may never be more than a powerful tool creatives have at their disposal. But like Photoshop and digital media in general, this is another way technology compresses deadlines and reduces budgets. It also gives agencies and creatives another learning curve to climb. With opportunities and pitfalls parallel to previous waves of technology.
And of course you shouldn’t ignore the possibility of AI becoming more of a threat than a tool.
The name of the Deep Learning system Google used to generate these images? Creatism. It’s stated purpose? Artistic content creation. You can almost hear a deep voice on a sizzle reel enthusing “Creatism, an artistic content creation agency.”