Reasonable people from all sides of the current AI conversation agree that this particular paradigm shift is just different. If you don’t believe that, record 20 minutes of your own stream of consciousness with an application like Otter and ask it to summarize your thoughts. Or download RunwayML and have it turn photos of your friends into videos of them doing the tango.
These tools – and countless others – offer an endless array of capabilities to test the limits of what humanity has created in the centuries to date. Some of it just plain blows the mind.
But while we’re busy having our minds blown, we’re also drifting into something of a context-distortion field.
If you never watched chef and food documentarian Anthony Bourdain, he said “context and memory play powerful roles in all the truly great meals in one’s life.”
That’s true of great technological evolutions, too.
Leaving aside the oversimplification that “AI” is a singular technology (it isn’t), it’s long past time for the “AI is eating the world” bumper stickers to evolve into how we manage this wave of change so it helps people, serves society and protects both.
Here we need some basic parameters.
First, everyone should get AI. Everyone should work and practice with it. Notwithstanding the burst bubble, people who leaned into the internet early developed a sharper understanding of the burgeoning internet economy. The experts say AI will create more wealth and opportunity than the internet. For those who rightly point out the widening gap between the ultra-wealthy and everyone else, we can’t leave people without the tools to participate as another massive tidal wave of change hits the global economy. As one alarming example, an estimated 700 million people in Africa have no access to electricity. For such a young continent with so much potential, we can’t leave nearly a billion people with no access and expect this to go well for the world. On every level – from infrastructure to access to training and enablement, let’s get serious about how this can be humanity’s big moment.
Second, we should remember the things that make humans what we are. EQ is more powerful than AI. While these generative AI tools can simulate engagement at a remarkable conversational level, they are simply gathering information from across the open internet and distilling that into conversational terms. Is it occasionally fun to ask AI for relationship advice or treat it like a loyal pal? Sure. Should we be polite when we work with it and treat it with respect? No harm there. But it’s not another person. It doesn’t care about us the way we care about each other. And most importantly, it’s very hard for it to police its own limitations. Only we can do that.
Third, tools that work great for us as individuals have always worked differently for us as a collective. In other words: any one of us can decide to do something on our own, and that thing can go well or go wrong based on the inputs by the individual. Add a second individual to this scenario, and you have a need for collaboration and coordination. This is a mountain that humanity has been working to climb since the dawn of civilization. Newsflash: we’re lousy at it. Our egos and self-interests and preferences and quirks – these are very difficult to blend in a cohesive fashion. Especially when the task before us is hard.
The term enterprise comes from the old French word entreprendre. It means, “to undertake.” In the context of AI…enterprise AI will follow a familiar path as previous technological waves. Bourdain’s quote – we need context and memory.
New technologies at work cause something of a feeding frenzy. We build a lot; we buy a lot. Some of it crosses over from our personal tools. Some of it gets infused into the tools we’re already using. Anytime a new technology comes to work, it’s an asset. And we need to understand that asset, what it’s configured to do, what data it is allowed to access and who is authorized to direct it. This work is as unglamourous as it is mission critical.
These same new technologies instantly become proxies for the exact same arguments we were already having. “Who put you in charge of that?!” “My way of solving that problem is better than your way!” “Who moved my cheese?!”
If you need a metaphor, think of this like a busy airport. It’s noisy and crowded. There’s equipment everywhere. The schedule constantly changes and things we can’t control often influence the operation more than the things we can.
This isn’t to imply enterprise AI or work AI won’t be exceedingly powerful – it will. But only with the proper governance (a control tower). And that’s not a task we should relegate to an experiment. That’s a big responsibility, deserving of credibility earned from past experience. In other words, we need context from people and systems that have been through big changes before.
And one last point: jobs. History shows that new technologies have an undeniable impact on how the workforce is structured and the jobs filled by people. This is already unfolding in the AI wave. Here the cautionary note is perhaps the strongest. AI must not become a codeword for layoffs. We can’t let it be filed under “maximize profit at the expense of the human workforce.” If we allow it down that path, trust will be shattered beyond our ability to repair it. AI at work should be a cheering moment for people, because we gave them the runway and empowerment to rethink things we all know are broken. Because we figured out how to give people an extra hour or two in their day to be with their family and friends. Because we made this a 1+1=5 equation for people to accomplish so much more with AI’s help.
If we’re mindful of this context, we’ll put AI to work for people. Which is the opportunity of our lifetime.
The opinions expressed in Fortune.com commentary pieces are solely the views of their authors and do not necessarily reflect the opinions and beliefs of Fortune.
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