“I am just a copy of a copy of a copy, Everything I say has come before…”
Nine Inch Nails – Copy of A (2013)
It started as a random shower thought that quickly made itself home in my brain and would not let go. As I stood there, letting the water cascade over me, I couldn’t help but wonder: what happens when we rely on AI models exclusively to mass-produce our content? Are we heading into an era of generic, dumb content?
Before we get all philosophical, let’s do a quick intro: AI, or Artificial Intelligence, is when computers can do tasks that usually need human intelligence, such as understanding language, recognizing images, or making decisions.
As more and more people adopt AI, more and more are using it to generate content; let’s call them outputs. And as these AI-generated outputs are released into the wild, these models are increasingly being trained on data that other AI models have created.
So, are we on the verge of drowning in a sea of AI-generated sameness? The answer is yes, but no.
Let’s discuss why…
Oh Hi, AI! -The Rise of Dumb, Non-differentiated, Content
One way AI is created is through training models on large amounts of data. Essentially, they are fed examples of what they should do and then use that data to predict new situations. Think of the spam filter on your email. First, the model trains on a dataset of emails labeled “spam” or “not spam.” Then, when a new email comes in, it applies what it learned to predict whether the new email is spam.
Let’s apply this approach to content and throw mass adoption into the mix; billions worldwide create AI content that feeds from these previous outputs. This ultimately results in a lack of diversity, leading to generic creations.
As an example. let’s imagine a machine learning model trained to develop short horror stories sourcing from Reddit’s r/nosleep/, to publish them on the same subreddit through a bot and farm karma points. As this model is only trained on data generated by a source that increasingly consists of outputs created by other AI models, the stories it produces will likely be highly similar to one another and lack originality. Some might not even make that much sense anymore.
And as it turns out, AI-generated outputs are already leaving their footprint on a wide range of creative industries, such as:
- Photography
- Fine arts
- Literature
- Music
- Film
- Advertising
Now picture a world in which sad songs just don’t hit the same way, portraits have no emotional depth, and films lack that X factor that allows us to connect and identify with the story on a level we can’t explain (yes, even superhero movies).
That seems like a pretty shit world to live in. The good news is that it doesn’t have to be that way.
Collaboration, Not a Replacement: AI as a Creative Tool
In the same way that when left alone, AI will ultimately create dumb content, its outputs can also enhance and augment human creativity. It can help to develop new ideas, find new ways of doing things, and make the creative process more efficient.
For example, I was born in Argentina, and my native language is Rioplatense Spanish. While I feel pretty comfortable writing in English, my grammar can give away I am not a native speaker. To mitigate this and focus on what I want to write, I have incorporated Grammarly in my workflow, a tool that employs AI to check for grammar, punctuation, and spelling errors in text.
Through time, it has not only been helpful to write but also taught me how to do it better. But just like me, Grammarly doesn’t get it right 100% of the time, and that’s when my experience, the conversations I have had with native speakers from different backgrounds, the books I’ve read, and films I’ve watched come into play to help me detect those mistakes and fix them. To choose to go with my ideas versus a suggestion from the app.
And just like this example, there are several ways in which AI can be a valuable tool to boost creativity that exists in all of us:
- New ideas: For example, a fashion brand could use AI to analyze data on fashion trends and predict possible trends. A designer curates the information and adds a twist to it.
- 24/7 on-call editor: As we previously covered, AI can help creatives fix their writing or artwork mistakes.
- Research: AI can help research and gather information. Think of a tool that can scan tons of data and pull out important information for a project.
- Project management: Creatives want to create rather than spend time in front of a spreadsheet. Why wouldn’t we use a tool that can automatically organize tasks and deadlines?
- Promoting your work: Tools like CoSchedule Headline Analyzer to optimize your blog headlines can figure out the best way to share a project online and get eyeballs on it.
- New tools: AI-powered software like Adobe Sensei and OpenAI’s GPT-3 can be used to design and develop innovative tools for artists and writers to enhance their creative work.
- Asset management: It can assist in organizing, archiving, and preserving digital media such as photos and videos, which can be a tedious task for many of us.
AI vs. Human: How To Coexist?
Not going to lie; I can offer all these examples and get all cheery about us humans adding value, but AI will continue getting better at copying us, and yes, some clients will go for the lowest possible cost and outsource the whole thing to some platform named Sprongle.
That’s ok; let them go. Those who prioritize cost over quality have always existed, and you should run away from them faster than you can say “payment in exposure.”
But just like the Beatles did before, employing groundbreaking studio tricks to record Revolver and Sgt. Pepper, we now get the opportunity to be part of the early stages of AI-mass adoption as a means to an end, not the end itself, to enrich our creativity.
We get to figure out how we want to use it.
So, rather than fearing the robot overlords taking over, let’s use our energy to work out how to tame this creature to our advantage and leverage it to push our creative boundaries beyond what we thought was achievable.
I, for one, feel pretty f’in excited.
