How Exactly Will ChatGPT Change Work?

A year ago most of us had never heard of ChatGPT. And for good reason: The artificial intelligence “chatbox” wasn’t introduced by OpenAI, its developer, until November 30, 2022. Now, less than six months later a Google search of ChatGPT produces hundreds of millions of results, making it the most talked about new technology since the previous most-talked-about new technology.

Perhaps ChatGPT and its competitors will revolutionize the way we live and work as much as, or more than Alphabet Inc. (Google), Amazon, Apple or Microsoft. Or perhaps it will be muscled aside by something newer (and presumably better), which is what happened to Kaypro, one of the top-selling personal computers in the 1980s, and CompuServe, the dominant online service provider at that same time.

Several years ago I attended a talk where the speaker discussed the inability to predict the future. His explanation was something to the effect that ‘the human brain thinks linearly and the world changes exponentially.’ If you’re over 30, you probably understand his point.

I’m among those who columnist Kimberly Ross recently described as straddling two generations, with “an ‘analog childhood’ and ‘digital adulthood.’” Late Baby Boomers, virtually all of Generation X—the nearly 66 million American born between 1965 and 1980—and a portion of the Millennial Generation, share this characteristic.

I started working in the late 80s when the computer age, as we know it today, was still a work in progress. When we started using personal computers, called word processors in their earliest iteration, information was saved on floppy discs, which were stored externally—typically in a little box, not in the cloud, which was unknown at the time. Contact information was catalogued on small file cards, which were filed alphabetically in a desk-top file called a Rolodex. Appointment schedules were penciled into calendarized notebooks known as Day Planners. [They’re still sold at Office Depot and Staples if you want to take a look.] Asynchronous communication was by voicemail: “337-ing” a long voicemail meant entering the number 33 to fast-forward to the end and hitting the number 7 to delete. You could only delete at the end of the voicemail.

The point is that in trying to get my head around what ChatGPT will do to the world of work, I could project that many, if not most, jobs involving a lot of writing or coding will disappear. I could also imagine the new jobs required to maintain and evolve the generative AI technology and to check the generated product for accuracy. But I need to respect lessons learned from the past and realize that any predictions I make likely will be wildly off.

Does that mean we shouldn’t try to figure out and attempt to influence what the future will look like?

Absolutely not. In fact, we should do the opposite.

We need to:

1) continuously gauge the market,

2) model potential options and impacts,

3) make predictions; and

4) repeat, then repeat and repeat again—paying special attention, perhaps, to the new startups emerging and failing.

Why? Because, as the late David Pecaut (a one-time BCG senior partner born and raised in Sioux City, Iowa, who earned his greatest acclaim as an urban futurist in Toronto) once said, startups are “generally right and specifically wrong.” But you can learn a lot about the future if you just follow the ideas and funding.

Pay attention to ChatGPT, the Metaverse and all other work- and life-altering technologies. Make predictions; but know they are woefully linear. Then, perhaps, supplement your linear thinking with exponential fiction and fantasy.

I’m a Boston Consulting Group Managing Director & Senior Partner who leads the future of work program.

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