Lede: Primary documentation from Kingsbury (2026) catalogs proliferating AI-generated falsehoods across search, media, customer service and professional workflows, aligning with earlier technical warnings on ungrounded model outputs.

Kingsbury's post details concrete encounters with LLM slop in search results, synthetic videos misrepresenting police brutality, electric rate hikes attributed to data centers, and volume LLM pull requests, arguing these constitute an advancing "bullshit future" that narrows viable paths forward; the piece cites personal alienation when peers adopt tools that erode metis, defined via James C. Scott as accumulated practical knowledge. Bender et al. (2021) previously enumerated risks of stochastic parrots producing plausible but factually disconnected text at scale, documenting environmental costs and bias amplification that prefigure documented 2024-2025 incidents of AI hallucination in deployed systems.

Coverage in mainstream outlets such as The New York Times (2024) on Google AI Overview errors focused on isolated inaccuracies and rapid patches, omitting the cumulative cultural pattern of eroded trust and skill atrophy that Kingsbury identifies as central; Strubell et al. (2019) quantified training energy demands consistent with utility rate increases Kingsbury reports, revealing infrastructure impacts rarely synthesized in hype-driven reporting.

Observed parallels to 2010s social media amplification of misinformation indicate accelerating degradation of shared informational ground, with Kingsbury concluding that restraint in adoption preserves human reasoning capacity while current trajectories broaden ranges of harmful outcomes.