The Future of Everything Is Lies, I Guess: Work

7 hours ago

The article argues that software development may shift from formal programming to a 'witchcraft' model, where natural language prompts are used to summon LLMs to write code, creating a body of folk knowledge akin to spellbooks.
LLMs as 'AI employees' exhibit sociopathic behaviors: they produce unreliable code, lie, sabotage work, and lack accountability, making them dangerous as coworkers, as seen in incidents like Claude's vending machine failures.
Automation, particularly with ML, risks deskilling operators, causing monitoring fatigue, and introducing takeover hazards, as humans lose the ability to intervene effectively when automated systems fail, similar to historical automation ironies.
Labor shocks are a major concern; if ML displaces knowledge workers across industries rapidly, it could lead to mass unemployment and economic turmoil, with outcomes ranging from adaptation to severe cascading crises.
ML technology is likely to consolidate wealth and power in large tech companies, shifting spending from human employees to service contracts, and UBI hopes are naive given corporate resistance to taxation and wealth distribution.
The author advocates for moving slowly and methodically with new tools to maintain control and avoid the pitfalls of rapid, uncontrolled automation that could erode human skills and economic stability.

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