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27%—that’s the percentage of Americans who use AI several times each day.
AI has been everywhere for a long time. From the early days of Microsoft’s office assistant “Clippy” to the Ring doorbell, from CAPTCHA to facial recognition. The first phase of AI was “weak AI” with “narrow intelligence” to do a singular task like the Roomba vacuum. This gave way to stronger and regenerative AI that we see today that doesn’t just simulate a human process, but also human intelligence. This AI has programming that reflects cognitive abilities and is able to help make predictions from large sets of information, solve problems, or classify things. A few examples include Jasper and ChatGPT.
While AI has implications across many industries, what is particularly useful to the advertising sector is generative AI, which can provide images in response to a spoken prompt. The largest boost in performance is when machines and humans work together to leverage complementary strengths. As Fluency’s Eric Mayhew said, “it’s like digging a hole with a shovel, versus an excavator – you’re moving the same earth, but with less effort.”
The Boston Interactive Media Association (BIMA) and the Greater Boston Chamber of Commerce recently put on a thought leadership event at Hill Holliday that gathered a panel of advertisers—who are using AI in various capacities—to speak to what’s coming. With an exponential growth of data, complex consumer behavior, and a world increasingly focused on privacy, AI has never been better positioned to revolutionize advertising.
Noor Naseer, VP, Media Innovations and Technology at Basis Technologies kicked off with an informative presentation on AI, and then was joined by Eric Mayhew, Co-Founder, President & Chief Product Officer at Fluency (an ad ops platform for scale and automation) and Gupta Media’s Founder Gogi Gupta, for an open discussion on how AI is being adopted in different aspects of the advertising landscape.
Here are the key takeaways:
While the future of AI, or “Super AI” may be programming that can exceed human capabilities, AI doesn’t currently outperform human intelligence. Currently, AI can deliver information that isn’t exactly wrong, but isn’t always correct either. AI provides the most value when it can automate mundane tasks to preserve human energy. As Gogi Gupta put it, “AI can help demystify large data sets, especially where humans are likely to make errors.”
Here are a few examples of the value of AI for advertisers:
Another reason why AI works best when humans and machines work together is because it needs to be trained in order to work properly. As Eric Mayhew said, “there is a lot of natural bias in data sets with AI that may be externally influenced.” He noted this as a skill to be taught. Current employees will also need to be upskilled to ensure that they fully understand what AI tools exist and how they might benefit their organization. Gogi Gupta added that “expertise is not widely distributed. AI is trying to do this, but it is narrowly defined.” While AI tools will help, he asserted that folks will “still need to figure out where they are going.”
This is giving rise to new professional opportunities and job titles, from Prompt Engineers who refine and optimize AI prompts, to Machine Learning Engineers who develop algorithms to power AI, to AI strategists that ensure AI meets compliance standards. Gogi also emphasized that
But it’s not just new titles that will be coming to organizations as AI adoption gains speed. There will be a responsibility from the top down to ensure that AI is used appropriately. There are a lot of open questions currently and a lack of clarity on legalities. For example, are AI-produced images protected by copyright law? Are there different legalities about what is used to train AI versus what AI generates? Organizations will want to develop AI playbooks to mitigate risk and protect their brands in the interim until clear laws answer these questions.
Eric Mayhew expects that in 2024 we will see a lot of regulation around AI. While the EU and China are ahead of us in this regard, he noted that the “U.S. is close.” In the meantime, he urged that any organizations leveraging AI should understand data use and “what these systems will do with their [clients’] data,” and “put governance in place to make sure hallucinations don’t happen.” By hallucinations, he’s referring to the fact that AI can sometimes produce outputs that are not grounded in reality and/or are lacking factual accuracy, which can occur for a variety of reasons, including biases in the training data or limitations in the model’s understanding of context.
While Fluency sees larger clients training on its own private model data sets, Eric said he thinks the future holds local models that can provide self-trained, clean data and AI results that will be sold, like audiences.
From Gogi Gupta’s perspective, he can see a future where X (formerly Twitter) will sell data which will come properly termed and conditioned. He added that while innovative and scrappy companies are currently using AI, “when Apple and Amazon offer it on their clouds it will be great.”
Some of the panelists’ favorite AI tools include Bard, Claude, ChatGPT, Amazon Polly (a text to speech tool) and an AI assistant called Hey Gen (a speech to avatar system). Adobe was also cited as “one to watch” with its tool Firefly, which rolled out exactly what designers need.
Along with more regulation, in 2024 we’ll see more applications of AI and machine learning that will give people more time back at work, removing frustrations and increasing efficiency.
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