Ever since ChatGPT was introduced in November 2022, scientific, business, media and tech spheres have been unnervingly obsessed over AI’s “revolutionary” breakthroughs. In January 2023, ChatGPT was the fastest growing app ever. Anyone with access to the internet, from stressed-out college students to retired grandmothers, suddenly had instant access to one of the most powerful neural networks ever created. One month later, Google and Microsoft announced plans to merge different chatbots with their search-engines to reimagine our interactions with the internet.
While Microsoft’s Bing Chat could not make any logical sense, and Google’s Bard was famously caught making a factual error during its promo pitch, the generative genie still refused to enter its digital bottle, no matter how many mistakes it made.
Both tech companies, after making the numerous, much-needed adjustments, would place both AI assistants in their office software. These chatbots can now summarize emails, generate slide decks and draft complex reports within seconds.
Microsoft also released a generative photo AI. Now you can share whatever image you can think of, from “The City in the Clouds” to Nicki Minaj’s “The Gag City.”
Google has since rebranded its AI as “Gemini.” New name, same unreliable, incoherent results.
There has never been a new product that has gone from the rickety prototype to a virally consumed product, ever. Like many other AI commentators have said, we have barely even begun to scratch the surface of AI’s potential.
But, who cares? With each new AI “breakthrough”, the astonishing is becoming more and more “meh.”
Is it possible generative AI prematurely used all of its 15 minutes of fame? Dramatic claims of AI taking over and becoming Skynet have fizzled out mostly. Now, people discuss how convenient it is to have ChatGPT summarize car insurance policies and lengthy textbook chapters. While the enthusiasm around AI remains positive, multiple AI start-ups with promising futures have cratered, and some of the biggest tech companies still have not smoothed out their AI assistants yet. Rather than jumping on the generative AI bandwagon, managers and high-level decision makers should question the potential future of generative AI. Where could this technology lead us? What risks are involved with adopting AI? Is this as good as AI will get?
Think of the evolution of the automobile. When car manufacturing was commercialized by Henry Ford, everyone wanted one. As the automobile advanced, so too did its capability. From having to reverse up steep hills to force gas into the engine to now starting your car from your phone, cars have come a long way. But now with the most recent automobile breakthrough being the popularization of electric vehicles, how much higher can cars go?
The same question applies to generative AI. Where else does it have to go? As we navigate AI’s unexplored potential, it is crucial to keep an open mind about its application and stand ready to revisit our views of AI as it continues to evolve.
Maybe, the AI hype has already died out. Maybe, AI is going to end up like Bitcoin; a groundbreaking product that was introduced before the world was ready for it. Regardless, the digital age we find ourselves in, is increasingly filled with AI noise. What happens next hinges on our ability to recognize, nurture and foster creative ingenuity.