Opinion

What AI can teach us about our attitudes towards creativity

Mintel's Elysha Young considers what our disbelief in AI's creative side has to say about our own misguided belief in the innate power of the human brain.

At this point I think everyone has wondered whether their job could be done by a computer.

Is my contribution something that only I could do, or merely a series of processes and actions which could be automated and performed by a robot to the same (or better) result?

The idea has loomed over us since artificial intelligence first entered the public imagination over 60 years ago. 

In advertising, we’ve already seen a shift in the way media is bought and sold – algorithms are the basis of all programmatically traded media, allowing for constant optimisation.

Not too long ago, we would have to watch for the ratings each day, analyse the target audience and figure out what they’re doing. These days we just plug in the budget and let the system do the rest.

Automation has turned the human element of trading media into little more than bookkeeping, making sure budgets and CPMs are on point and letting the computer do the fun stuff.

That’s all well and good in trading – it was always a game of efficiency, and computers are faster with numbers than we are. But what happens when AI technology becomes so advanced that it becomes better at the aspects of advertising we’ve always considered closer to art than science: the human part, the insight, the hook that makes an idea great?

Could AI become better at creativity, at coming up with that big idea, than human creatives?

It’s been said that there can’t come a point where AI can create an idea from nothing. This implies that human creativity is also born from nothing, that ideas are created in a vacuum or strike like lightening from the heavens.

But human beings are not blank slates. We contain a range of different experiences, biases, and knowledge and ideas about all sorts of different things, all of which inform the way in which we think.

It also discounts one of the most important elements in the creative process – research. Without an intimate knowledge of your product and your audience, and a broader understanding of the world in which you want to create, coming up with something that brings brand and consumer together in a meaningful way is practically impossible.

What some in creative fields call “looking for inspiration” is literally just the process of gathering knowledge, learning every single thing you can about whatever it is you’re trying to sell and how it fits in.  

The other thing this assumes is that ideas are completely distinct and independent of each other, and that the best idea is a brand new idea that no one has ever thought of before.

This is both a lot of pressure to put on a creative, and ultimately untrue of most successful new product or campaign launches.

First published in 1965, James Webb Young’s A Technique for Producing Ideas describes creativity as a five step process in which the “production of ideas is just as definite as the production of Fords; that the production of ideas, too, runs on an assembly line.”

He notes the Italian philosopher Pareto’s assertion that there is no such thing as a new idea, just new combinations of old elements. Nothing in the world is completely brand new, but our perceptions, perspectives, and the connections we draw between elements can be.

Young’s Five Step Technique

  1. Gathering the raw materials – research everything there is to know, specifically about your product and consumers, and broadly about pop culture and events
  2. Thinking – make connections and exhaust every possibility
  3. Relax – drop the project entirely. Ride a bike, watch a movie, don’t think about it.
  4. Aha moment! – an idea will come when you least expect it (probably in the middle of the night)
  5. Evaluate – fine tune, rework, make your idea fit the brief, get feedback.

By following Young’s ideation process, we can see which elements of creativity can be sped up, made more efficient, or replaced outright, by AI.

It’s also clear which parts can only (at least for now) be done by humans with those particular skills. The key benefit of AI is that it can almost instantaneously process information and map connections between different elements.

With creative solutions being consistently touted as ‘data-led’ by marketers and advertisers, having an intelligent analytics tool that can deep-dive into consumer data for hidden insights enables creatives to actually deliver on that promise – to truly lead the creative with whatever is unearthed in the enormous datasets we’re collecting.

An AI tool which facilitates the research and thinking phases of the process by providing both quantity and quality of relevant research, and highlighting the ways different elements do or don’t relate to each other, would obviously save creatives a lot of time.

What it can’t do, however, is reason. It can’t evaluate ideas, or intuit potential consumer responses, or capture the ‘feel’ of something.

Imagine, for example, that last year’s notoriously bad Pepsi ad was made by AI. All the elements were on point – a trendy cultural figure (Kendall Jenner), hot button current event (protests) and a pastiche of cool young people doing generic cool things, all makes sense on paper. What AI can’t compute, as yet, is the sensitivity of what it’s saying, or even whether putting it all together makes sense. 

It’s still up to the creative to do the legwork of ingesting all the information provided, mulling it over, coming up with as many big ideas as possible, and then, most importantly, evaluating those ideas for appropriateness, relevancy, and of course that extra special something which makes a good idea great.

We need to stop thinking of AI as the hot new intern eyeing off our job. By utilising AI as a co-creativity partner, rather than fearing it as a competitor, the potential is there for creatives to do some incredibly insightful and innovative work within an ever-changing media landscape.

Elysha Young is account manager – ANZ at Mintel.

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