Fear and Loathing in Generative AI

I’ve found other conversations on the topic to be similarly loaded—a lawyer friend at Google called the wide release of ChatGPT “incredibly irresponsible”. When I brought up Bard, she shot back, “We’ve been sitting on LLMs for a decade. There’s a reason we’ve held back.” 

Even within the realm of marketing alone, opinions and reactions span a polarizing spectrum from we’re all gonna be unemployed-level fatalism to no robot can EVER do what I do-level denial. On either end, there’s fear. 

It’s a wide-reaching topic. And many worries are practical, to be sure, especially with regard to information accuracy and governance. These have implications on individual health and safety, let alone brand safety. 

But most of the anxiety I’m sensing from these conversations is more personal, with notes of catastrophic thinking, i.e. If AI can do my job, how will I stay relevant? I’ve spoken to a content marketer who balked and told me that there is and never will be a shortcut for deep storytelling. “I interview my subjects and get into their history, their psyche,” she explained.

On the other hand, the owner of an SEO agency said that ChatGPT meant that, ultimately, he might be able to downsize his team to improve margins — but it sure wouldn’t feel good. A 3D artist employed by a major video game company said he’s spending more time on his startup: “The writing’s on the wall.”

It’s true that many vocations that make up our global economy today rely on executing tasks once thought to be uniquely human-dependent. But as marketers, let alone the broader tech landscape, we’ve also been offloading complicated, time-consuming work to AI for years, particularly in areas of data intelligence and programmatic advertising, both replacing jobs and creating entire industries in the process. Let’s not pretend it’s a total shock to the system.

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So lately, I’ve been asking myself, what is it about generative AI that’s so obviously triggering? 

And I think it has more to do with the nature of these new capabilities than the power of them. We’ve long depended on AI to do the thinking for us, but now it’s taking on the doing. And we really like doing ‘the doing’ — writing, designing, building, programming, editing, researching, curating. These are the kinds of tasks that keep us busy, and make us feel productive and useful. Busy hands are happy hands, right?

Conversely, data processing and decisioning are faster and more accurate, eliminating the ample room for human error when outsourced to machine learning. It has produced stronger, more efficient input to support our flesh-and-bone output. This felt like the right relationship, the appropriate power dynamic, between man and machine. 

Generative AI is about output, and it’s undeniably impressive. Estimates claim it will replace around 30% of knowledge work. But also undeniable is that its product is only as good as the quality of its informants. So as bots become great at informed execution, people need to become even better informants — at least 30% better. A 30% productivity boost is quite literally a savings that when leaned into rather than fought, can be reinvested directly into the portfolio of qualitative work like mining for insight, creating guidelines and guardrails, and tuning into the powers of straight-up human observation — the cognitive magic that only happens when we’re freed up from doing enough to just watch, process and think. 

In a world of endless distraction and busyness, maybe the question of the day is what happens when we mortals have to do more of the thinking than the doing? 

Do we really not want to find out?

Against the backdrop of Open AI’s noisy debutante ball, the digital ad industry is going through its own awkward evolution from channel-obsessed to customer-centric. After years of talking about omnichannel marketing, practitioners are finally taking active measures toward it, buying platforms instead of point solutions, unifying teams, shaking up job titles, and rethinking KPIs. Progress is challenging and slow, but it’s happening. And I wonder if generative AI taking on more of the channel-specific execution might just be exactly what we need to get us over the hump. 

So much of the lift of omnichannel marketing stems from the complexity inherent in keeping pace with the mindset and behaviors of today’s unpredictable consumer. We relied on cookies for a long time to construct behavior-based profiles and maintain connections over time. Today, we need to do heavier lifting than that, leveraging first-party data to deepen authenticated relationships and guide campaign strategies that can be executed and automated across channels.

Making time for that overarching effort — the connective tissue — on top of all the tasks that go into creating and optimizing ads within the nuanced ecosystem of each specific digital publisher has been pretty much impossible for every advertiser I’ve come across. Smaller companies with leaner marketing teams are typically spread too thin. Larger teams and programs are so deep in the scale and technical sophistication of their channel activation that they still can’t spare the resources.

Generative AI can ease those burdens and give us back headspace to go analyze our customers based not only on their behaviors but their mindset at each touchpoint and to architect empathetic communications and value exchange. It’s easy to imagine how AI-boosted ad managers and free tools will enhance campaign creation and management, copywriting, and creative production, in addition to what they already do in programmatic media buying, audience targeting, and bid optimization. It’s harder to imagine how marketers will spend their time in order to tackle the trickier task of informing these models and automation with rich enough input for even higher-bar outcomes. We’re pretty rusty when it comes to deep work.
Yet this is also where things can get supremely innovative: knowledge workers with more or less equal access to tools that can increase the speed and quality of the practical aspects of our jobs will have to compete on deeper layers, like creativity and ingenuity, pushing things — and each other — forward.

I think about my kids, elementary school and college students whose eventual career options may be totally different from those my generation had access to, and for whom agility is reportedly the characteristic most crucial for success, outweighing any hard skill, and I’m way more excited than fearful. What a time to be alive — and humans aren’t an idle species; we’ll figure out new ways to spend our time and get paid, so long as we continue to bet on ourselves. 

Talk about upside.