https://archive.md/cd5Hv
"Not long after graduating from the University of Texas at Austin in 2021,
Donald King landed a job as an associate at the London-based consulting firm
PricewaterhouseCoopers. King had always assumed he’d work in business — he’d
started his own hedge fund while still an undergrad — but a few years into the
job, he decided he was more interested in tech than finance. Early in 2024,
after PwC announced a $1 billion investment in artificial intelligence, he
switched roles and started working as a data scientist for the company’s
nascent Global AI Factory.
King worked with engineers at PwC and OpenAI to customize teams of autonomous
AI systems, called agents, for Fortune 500 companies. Normally, multinational
companies contract thousands of people to modernize their backend software.
Home Depot, for example, might enlist an army of consultants to update
inventory or its SAP accounts-payable processes. Recently, though, AI agents
have gotten pretty good at that kind of work. Consultants are some of the most
prolific AI users, and King thought of himself as a kind of pioneer in a New
Age of automation, creating and then deploying agents for PwC’s clients.
“P-dubs,” as King calls it, expected a lot from its workers. King put in
80-hour weeks, which kept the 26-year-old from going out on weekends. But he
made six figures and lived in a one-bedroom high above Hudson Yards in a
building with a pretty nice gym, where he sometimes took camera-off meetings
while doing pull-ups. “I was a meat slave,” he says, “and it was kind of a
dream job.”
The goal was to help clients “do more with less,” as King’s bosses reminded
him, by automating whatever task they threw at his team. Occasionally, when
King lingered on the downstream effects of his work, he felt like Dr.
Frankenstein looking at his monster. “There was a sense of awe and then it’s
kind of shock and fear and almost a disgust,” he says. King knew consultants
were called hatchet men for a reason, but it was becoming clear to him that the
agents his teams built were capable of wiping out not just individual jobs but
entire job categories. “There was a large telecommunications client, and we
were doing some crazy stuff for them. Once, we created an agent that was
literally, like, a Microsoft Teams agent that was pretending to be a real,
human employee,” King says. “That’s when me and my other teammates were like,
‘Whoa, we need to sit and just talk for a little bit. What are we even doing
right now?’ Because that’s someone’s job, and if we have 45 of these agents
working together, how many human jobs is that going to take? Are we just
automating away people’s livelihoods?”"
Via Susan ****
Cheers,
*** Xanni ***
--
mailto:xanni@xanadu.net Andrew Pam
http://xanadu.com.au/ Chief Scientist, Xanadu
https://glasswings.com.au/ Partner, Glass Wings
https://sericyb.com.au/ Manager, Serious Cybernetics
