Generative AI: Unlocking the power of automated marketing
Five key things marketers need to know about generative artificial intelligence
18 January 2023 - 10:43
byAndy Hood
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If you’re reading this article, you responded to work generated by artificial intelligence (AI). The prompt entered into OpenAI’s GPT-3 Playground was, “Write a fun SEO headline for an article about generative AI and marketing”. Once it had been inputted, the AI took about five seconds to deliver the header of this article.
What is generative AI?
AI, as a rule, is simulating, in a machine, the same cognitive processes that we see in people. It’s a way of problem-solving. And you probably use it in your daily life already without even realising — like when your smartphone enhances a badly taken photograph into something worthy of the Gram or when you use Google maps to find the fastest route to your destination.
Generative AI is a type of AI that can generate content in response to prompts — in the form of words, images, video and even music. Instead of typing an image into the search bar of an image library and getting a menu of images that already exist, you type an image description into Dall-E 2 and it generates a menu of images to match what you type. In other words, it doesn’t find images, it makes them.
Generative AI is still in its infancy, but it’s poised to transform the marketing industry, though probably not in the way you think. Here’s what you need to know.
1. AI needs to be trained
In the same way a human can draw a bus out of their head because they’ve learnt what a bus is and what it’s not, AI needs to learn to generate a piece of content. It does this by absorbing data — lots of it! About 2.3-billion (not a typo) captioned images were used to train the image generator Stable Diffusion.
2. The problem is, training data is often biased
AI can only learn from what’s out there, and what’s out there tends to be influenced by human biases. In fact, problems with AI almost always comes down to the training data. We did some research with Lambda Labs’s AI generator StyleGAN 3, which can generate — almost disturbingly — realistic images of people who don’t exist in the real world. What we found was that the AI was able to age the men beautifully, but women started to look more and more masculine the older they got. When we got into the training data, we discovered that the issue was not with the AI, it was the fact that the images of adult women used to train the AI were vastly skewed to the 20-40 age group, meaning the AI just wasn’t seeing enough older women, versus men, to be able to learn what women look like as they age. A big focus of ours at WPP is identifying and eliminating these biases.
More than anything else, generative AI is useful for executing cool ideas that used to be impossible
3. Content generation is more complex than it sounds
Finding the perfect prompts that will get the AI to generate the concept that you’re imagining in your brain is even harder than trying to find representative imagery in a stock library. For starters, the AI needs to have been sufficiently trained — if it’s never seen an image labelled “bus”, you’ll have no joy typing “bus” into your prompt. Instead, you’ll need to describe what a bus looks like, using image references the AI has been trained on. Which brings us to the second conundrum — if you’ve ever played a game like 30 Seconds, you’ll know that describing what you have in your mind vividly enough for it to be reproduced is not always as simple as it sounds. Get it right, though, and your designers will never have to trawl through a stock image or music library again.
4. Generative AI creates possibility
More than anything else, generative AI is useful for executing cool ideas that used to be impossible. This Cadbury campaign in India made it possible for small businesses to create an ad featuring Bollywood megastar Shah Rukh Khan for free, using generative AI.
Andy Hood. Picture: Supplied
5. The future is AI. But not like in your nightmares
Generative AI is not coming for your jobs — nor those of your designers. However, that being said, designers will lose their jobs to other designers who know how to use the tools. That’s because generative AI will become like the Adobe suite of the near future — a tool to make the creative industry faster, more capable and more efficient.
Andy Hood is vice-president of emerging technologies at WPP
The big takeout: Generative AI is still in its infancy, but it’s poised to transform the marketing industry.
Support our award-winning journalism. The Premium package (digital only) is R30 for the first month and thereafter you pay R129 p/m now ad-free for all subscribers.
Generative AI: Unlocking the power of automated marketing
Five key things marketers need to know about generative artificial intelligence
If you’re reading this article, you responded to work generated by artificial intelligence (AI). The prompt entered into OpenAI’s GPT-3 Playground was, “Write a fun SEO headline for an article about generative AI and marketing”. Once it had been inputted, the AI took about five seconds to deliver the header of this article.
What is generative AI?
AI, as a rule, is simulating, in a machine, the same cognitive processes that we see in people. It’s a way of problem-solving. And you probably use it in your daily life already without even realising — like when your smartphone enhances a badly taken photograph into something worthy of the Gram or when you use Google maps to find the fastest route to your destination.
Generative AI is a type of AI that can generate content in response to prompts — in the form of words, images, video and even music. Instead of typing an image into the search bar of an image library and getting a menu of images that already exist, you type an image description into Dall-E 2 and it generates a menu of images to match what you type. In other words, it doesn’t find images, it makes them.
Generative AI is still in its infancy, but it’s poised to transform the marketing industry, though probably not in the way you think. Here’s what you need to know.
1. AI needs to be trained
In the same way a human can draw a bus out of their head because they’ve learnt what a bus is and what it’s not, AI needs to learn to generate a piece of content. It does this by absorbing data — lots of it! About 2.3-billion (not a typo) captioned images were used to train the image generator Stable Diffusion.
2. The problem is, training data is often biased
AI can only learn from what’s out there, and what’s out there tends to be influenced by human biases. In fact, problems with AI almost always comes down to the training data. We did some research with Lambda Labs’s AI generator StyleGAN 3, which can generate — almost disturbingly — realistic images of people who don’t exist in the real world. What we found was that the AI was able to age the men beautifully, but women started to look more and more masculine the older they got. When we got into the training data, we discovered that the issue was not with the AI, it was the fact that the images of adult women used to train the AI were vastly skewed to the 20-40 age group, meaning the AI just wasn’t seeing enough older women, versus men, to be able to learn what women look like as they age. A big focus of ours at WPP is identifying and eliminating these biases.
3. Content generation is more complex than it sounds
Finding the perfect prompts that will get the AI to generate the concept that you’re imagining in your brain is even harder than trying to find representative imagery in a stock library. For starters, the AI needs to have been sufficiently trained — if it’s never seen an image labelled “bus”, you’ll have no joy typing “bus” into your prompt. Instead, you’ll need to describe what a bus looks like, using image references the AI has been trained on. Which brings us to the second conundrum — if you’ve ever played a game like 30 Seconds, you’ll know that describing what you have in your mind vividly enough for it to be reproduced is not always as simple as it sounds. Get it right, though, and your designers will never have to trawl through a stock image or music library again.
4. Generative AI creates possibility
More than anything else, generative AI is useful for executing cool ideas that used to be impossible. This Cadbury campaign in India made it possible for small businesses to create an ad featuring Bollywood megastar Shah Rukh Khan for free, using generative AI.
5. The future is AI. But not like in your nightmares
Generative AI is not coming for your jobs — nor those of your designers. However, that being said, designers will lose their jobs to other designers who know how to use the tools. That’s because generative AI will become like the Adobe suite of the near future — a tool to make the creative industry faster, more capable and more efficient.
Andy Hood is vice-president of emerging technologies at WPP
The big takeout: Generative AI is still in its infancy, but it’s poised to transform the marketing industry.
Web 3.0 and the future of modern marketing
Turning to AI for the answers
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