Raw LLM Responses

Inspect the exact model output for any coded comment.

Comment
The first wave of enterprise accounting software in the 1980s didn’t create more accounting jobs. It spawned new industries in IT consulting, systems integration, and software development—but only over time. What’s missing in this analysis is the historical pattern: every major technological shift is highly disruptive and often produces long periods of economic dislocation. The main reason is skill mismatch—new systems require expertise that isn’t yet widespread, while existing workers’ skills become redundant. If robotaxis and driverless trucking reach full adoption, millions of jobs will disappear. The framing of the “doomsayer” versus the “naysayer” was also misleading. The so-called naysayer isn’t denying the potential impact of AGI—he’s arguing that current AI doesn’t yet have the capability to achieve it. The real discussion should focus on whether sub-AGI advances—incremental but focused improvements—can still transform industries by automating data-driven decision making. That’s plausible, but not guaranteed. Today’s AI can replicate, assist, and accelerate research, but it cannot originate human-style innovation. It also introduces new risks: errors and omissions that may be subtle and difficult to detect.
youtube AI Jobs 2025-10-28T16:4…
Coding Result
DimensionValue
Responsibilitynone
Reasoningconsequentialist
Policynone
Emotionresignation
Coded at2026-04-26T23:09:12.988011
Raw LLM Response
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