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Actionable AI: Data science meets social science
Replaceable. How many of you hear that word in the back of your mind when you read the term “artificial intelligence,” in reference to the value you add to your organization? That hard knot in the back of your throat is recognition that we’re now entrenched in technology innovations that will shape our world — and jobs — forever.
Last month, in a heavily shared and discussed AdExchanger interview, former AOL Sales Chief Jim Norton said ad dollars are swinging back to content.
Norton explained that high-end premium digital content was scant, so “advertisers have quickly realized that in an algorithmically driven world wired to a race to the bottom on both scale, efficiency and pricing, you end up with this real need to get back to a premium ad environment and user experience.” (Note: He was not replaced by AI, and instead has been snapped up by Condé Nast to help the mass media company position itself as a key digital premium player.)
That algorithm is artificial intelligence, or “AI,” and you have likely read this term or heard it in meetings and conferences more than once this month. This buzz-term du jour is everywhere — at dmexco and Advertising Week, in the halls of media agencies, publishers and tech platforms.
But backed against a wall, could you explain what it means? Let’s unpack it and agree upon a definition: AI is machine learning used to predict the likelihood that a given tactic will produce a certain outcome and that the amount spent on that marketing tactic will produce desired advertising results.
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