One of my hobbies is business history, and I always find wonderful insights in looking back on earlier economic and societal transitions that reflect the current situation. One of the most interesting themes that I am using to interpret economic and organizational challenges is following really large transitions over longer periods of time. In this case, it is the transition from the agrarian to industrial economy, followed by the transition to the service economy, and now leaping quickly forward into the knowledge economy. Each cycle seems to be following a version of Moore’s Law, the compacting of time as transitions accelerate. The stress that is so apparent in the current transition to the knowledge economy is the speed of change is challenging even the most flexible and intelligent human interpretive capabilities, not just the geographic and education migratory capabilities of larger labor pools.
In its vast scale and tremendous ability to produce wealth and power, the railroad was, the diplomat and historian Charles Francis Adams Jr. wrote in the late 1860s, “an incalculable force practically let loose suddenly upon mankind; exercising all sorts of influences, social, moral, and political; precipitating upon us novel problems which demand immediate solution; banishing the old before the new is half-matured to replace it.” It might be, he concluded, “the most tremendous and far-reaching engine of social change which has ever either blessed or cursed mankind.”
“A.I. is not equivalent to railroads. For one, rail travel met an immediate need whereas, outside of highly technical fields, artificial intelligence is still a product looking for a market.”
Though I do not know Jamelle Bouie, his insights here shed considerable light on my current thinking, and I am grateful for his thoughts. My only suggestion to Mr. Bouie’s comments is that I believe that LLMs/AI are immediately responding to a widespread need to allow non-technically trained people access to the full power of modern technology. In a rapid democratization through a natural language programming of sorts, a liberal arts or trades trained individual can now harness the full power of computational capabilities to solve professional and personal challenges and inquiries. These tools were reserved over the last two decades for most specialized software engineers and their managers and business owners through the interpretive services and platforms they created.