AI is a game-changer for marketers. In terms of competitive advantage, productivity, efficiency, customer experience, and so much more. It is here, it’s happening, and the opportunity is massive. But in the words of Spiderman’s Uncle: “With great power comes great responsibility.”

As an industry, we are standing at a pivotal moment in marketing, where we must choose between simply using AI or using it responsibly and inclusively. The choice we make will shape our whole industry moving forward. So we can move fast and break things, an approach that has sometimes served us well. Or we can lay down our ethics and responsibilities and do what we can to avoid replicating and amplifying the stereotypes and other inclusion challenges that we’ve all worked hard to overcome.

AI poses certain obvious risks for brands, such as losing distinctiveness in a sea of AI sameness. As well as the weight of potential misinformation, the skills gap and impact on jobs and careers. Then there are the less obvious challenges, like losing cultural nuance, which is particularly important for delivering more inclusive marketing. We can’t afford to leave the human behind in this process; doing so would ignore our capacity for empathy and cultural understanding.

The really big challenge that we need to talk about though is bias.

As human beings, our brains are programmed to be biased. There’s about 188 different cognitive biases that help us to process, categorise, remember and act on the vast amount of information that our brains receive. However, these biases can also lead to flawed decision-making and false assumptions. When they show up in the marketing process and guide marketing decisions, they can contribute to the perpetuation of harmful stereotypes and marginalisation of already marginalised communities. 

In AI, bias is the default. This creates a systematic feedback loop between humans and AI that is extremely powerful and extremely dangerous. We start with human bias; the stereotypes and assumptions that we have created as a society over thousands of years. These inform the stories we tell, the data we generate, the decisions we make and the systems we build.

Then, our AI tools are built and trained with this biased data; such as healthcare histories, online behaviour and even books.

AI tools don’t just reflect this biased data, they amplify it at a much greater speed and scale than humans can do on their own. When we look at a typical campaign process and all the opportunities for bias to creep in from a human perspective, it’s already a huge problem. Overlay this human bias with layers of AI in any process, and the bias at play is even more vast.

It can feel scary and overwhelming but we can still break the bias in AI by being consciously inclusive through inclusive prompting and critical output analysis.

Here are 5 key takeaways from Creative Equals on how to do this:

1. Set your inclusive marketing strategy
2. Train your AI models on diverse data sets
3. Educate your teams on bias
4. Learn how to inclusive prompt and reiterate
5. Apply across the marketing process and all AI tools 

Creative Equals can help with all of those things. Let’s get the industry talking about Bias in AI, and tackle it together.

Photo Credit: Bronac McNeill

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