I read an article, via Instapundit on Artificial Intelligence.
I’ve worked in the corporate IT space for over 30 years.
My primary school years were spent watching American men walk on the moon. I wanted that. At about the same time I found Star Trek reruns and Robert Heinlein. Later as a teen, I stood in line for hours to see Star Wars, ten times different times at movie theaters. A stint in the US Army and a college degree later, it occurred to me that the space adventure was not to be.
As a young adult, I maneuvered myself into IT. I found working with computers to be fun and while it wasn’t space, it seemed to be the future. In many respects it was. The world is much different and in many ways better than it was when I stood in those long lines at the movie theater.
For most of my post-military and academic career, I’ve spent most of my time supporting large organizations IT work. I’ve had a diverse series of positions, initially as an Independent Software Vendor and more lately as a consultant, interspersed with time as an employee.
Over the years I’ve had the honor of working with firms, nearly all of which have brand names you’d recognize. In almost every case, the vast majority people I worked with were nice people trying to do they best they could under trying circumstances.
When I ran my startup we did a lot of work in the corporate search technologies, a precursor to today’s Large Language Model (LLM) AIs.
Business is not academia and the people working in business are not academics. It would also seem academia is not what it was what it was 35 years ago.
During a consulting stint, about a decade ago, I worked for a large company. Make no bones about they were kind to me, as a consultant, when they didn’t have to have to be. In fact I didn’t expect them to. I’m grateful nonetheless.
That firm had a lot of big data problems to solve and had they been realized would have led to significant process changes, cost reductions, higher of availability of their products and greater customer satisfaction.
A gentleman I worked with, a brilliant and charismatic fellow ask the Vice President level leadership, those charged with operating the business, a simple question:
“What would you like to know about your business that you don’t know today?”
I’d been working with the client site for about six months. I’d learned a little about their business, but my primary responsibility was providing them with a Cloud infrastructure. Upon discussing it with my friend, I decided to jot my questions down.
The upshot is they asked one or two additional questions that I did not.
What struck me was not my brilliance, I’m not, but the lack of intellectual curiosity from the people managing the business.
I am far less sanguine about artificial general intelligence (AGI) than Pethokoukis. The examples Mr. Pethokoukis provided about how AI could brighten our future are good ones. Crunching through big data sets is what computers, and by extension AGI are good at. But the examples he provided are all academic in nature, crunching through SETI data for example.
But here is the thing, to get an answer that reshapes an approach to your business, first you must ask an interesting question. AGI still depends upon interesting questions be asked again and again. Can one look for the equivalent of “Bug Eyed Monsters” in corporate data? Sure. But it depends on the ability to ask interesting questions.
To gain expertise in a business, young people must take entry level positions.
My suspicion is that most businesses will use AGI, and even the Large Language Models to grab at the low hanging fruit of the entry level positions and have an immediate effect on their bottom line.
Thereby eating their seed corn.
Think it hasn’t happened? Look at Mike Rowe and his awesome crusade for trade work to the fix serious stupidity of “elite” leadership class. We are about to do the same to knowledge workers.