Weâre headed down the wrong road with generative AI.
Over the last few months, Iâve been struck by the messages from major gen AI solution providers. Unfortunately, those messages feed the frenzy for implementing generative AI in creative and marketing operations.
Take, for example, this recent quote from OpenAI CTO Mira Murati in response to a question about AI replacing humans: âSome creative jobs maybe will go away, but maybe they shouldnât have been there in the first place.â
Really?
But sheâs not the only one making statements along these lines. OpenAI CEO Sam Altman has claimed that AI would handle â95% of what marketers use agencies, strategists, and creative professionals for today.â
And, of course, thereâs this famous quote from economist Richard Baldwin at the 2023 World Economic Forum Growth Summit: âAI wonât take your job. Itâs somebody using AI that will take your job.â
Now, itâs not that these statements are entirely true or false. If you peel any of these statements apart, youâll hear some people say, âWell, what they meant by that wasâŚ.â
And thatâs the problem. Itâs not the accuracy of the statement â itâs the interpretation.
Tech companies make technology the hero of the story. Theyâre telling people to feel lucky to be worthy of such amazing tools. And theyâre frothing up the argument that human creativity is a problem to be solved.Â
Thatâs ironic when you consider how every one of these technologies used the products of human creativity to evolve. Â
During this gen AI gold rush, business leaders are rushing to tell investors, analysts, customers, and audiences how many roles they can replace with the technology in the name of efficiency.
But will some early adopters regret these decisions? Two researchers think so. They published an article in Harvard Business Review last year arguing that although the initial numbers might âlook good, especially in cutting costs, the company will miss the opportunity for big gains by creating substantial value â or a defensible future niche.â Â Â
I see this happening in some companies that have replaced content creators with generative AI. Yes, they are producing more content than ever â theyâve succeeded in creating efficiency in producing content at scale.
And the content they create? Itâs average. Itâs neither bad enough nor good enough to be remarkable. Itâs just average.
And itâs leading us into an age of sophisticated mediocrity.
A wicked problem is hard to solve because of âincomplete, contradictory, or changing requirements that can be difficult to recognize.â Information researcher Jeff Conklin described wicked problems as those ânot understood until after the formulation of a solution.â
Think of the way you organize your kitchen. It might work well enough for you, so you canât see how much better it could be until someone suggests changes that make it work much better. Only then do you realize that you did have a problem worth solving.Â
Wicked problems are rampant in marketing. Your content or marketing approach might be working OK. You know it isnât quite humming on all cylinders, but thereâs nothing so dysfunctional that fixing it becomes a priority.Â
But then you try to fix something minor and realize many other operational areas need improvement, too. Are the problems significant enough to warrant the disruption? Unfortunately, you wonât know until you try.   Â
Unfortunately, those hyperbolic statements about gen AI replacing people or teams have created what appears to be a wicked problem in creative and marketing.
Business leaders hear about gen AI developments and think, âThis is such a cool innovation. We must have a problem it can solve â we just donât know what it is.âÂ
Then, because of the hyperbolic promises about gen AI replacing agencies and creatives, the sentiment shifts to, âSome of our creative jobs probably are redundant and outdated. Maybe thatâs the problem generative AI can solve for us.â
Iâm not saying there arenât some organizations that employ more people than needed or that could improve efficiency or productivity. And those are wicked problems.
But implementing gen AI as a (theoretically) cost-effective replacement for humans who interact with customers or create content usually isnât a way to solve a wicked problem.
Itâs solutionism.
Solutionism, a term popularized by tech critic Evgeny Morozov, describes the belief that every problem can be solved with a technological solution.
And solutionism is at the heart of all these statements made by generative AI solution providers.
When Mira Murati says that some creative roles âshouldnât have been there in the first place,â sheâs feeding into the notion that the need for creative roles is a problem that can be solved with technology.Â
When Sam Altman says â95% of what marketers use agencies, strategists, and creative professionals for todayâ will be handled by AI, heâs suggesting that inefficiency in the art of creative marketing needs to be corrected.Â
And the bumper sticker warning âAI wonât take your job, but someone using AI willâ suggests that generative AI is the hero we should demonstrate our worthiness to.
Buying into these statements pushes us into the era of sophisticated mediocrity. It means we accept the trade of diversity of human thought for a sophisticated solution to a nonexistent problem.
No CEO wakes up and says, âWe have too many people with too many creative ideas. Letâs save some money and get rid of them.â But when CEOs tell their teams to figure out how many (or which) resources they could jettison by implementing gen AI, theyâre forcing that calculus. Â
There are things we can do to avoid this trap. The biggest is to take one all-important first step: Understand and document the opportunity to which you plan to apply AI. That may sound like a no-brainer, but I see more and more companies fail to do it with generative AI.
Just last week, it was reported that 20,000 energy giant Chevron employees are testing Microsoftâs Copilot, a suite of AI-powered chatbots and other tools in Microsoftâs Office 365 apps that can answer questions and generate email drafts. The problem? According to Bill Braun, the companyâs CIO: âWeâre a little dissatisfied with our ability to know how [well] itâs working.â
My take is they will continue to be. You canât give 20,000 people a solution to a problem that doesnât exist and expect them to report back accurate value.
With any productive rollout of an enterprise-wide innovation, you have to first understand what value you want to assess. And to do that, you must understand the existing process that merits assessment. It will be impossible for Chevron to truly get an overall value until it understands what itâs trying to solve.  Â
Iâm not arguing against using generative AI. Iâm warning against using specific arguments to advance the technology. There are plenty of wicked problems to uncover in content and marketing. And many activities we do every day might be improved with technology like generative AI.
The key is understanding the difference between solving a real problem and forcing technology solutions to problems that donât exist.
And thatâs how you avoid sophisticated mediocrity.
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