When will average people feel AI’s impact?

An essay published by Interconnects examines why average people have yet to feel AI's impact, arguing that the current boom differs from past industrial revolutions in how most people are exposed to technological change. The author frames the moment as the first half decade of what could be a 50-year diffusion process.

The essay states that core aspects of everyday life — family, food, transportation and entertainment — have few direct AI impacts yet. It describes today's touch-points for average people as fringe, marginally beneficial or confusing, citing image generation and enhanced search as small benefits, and associating AI negatively with addictive social media algorithms, AI chatbot addiction and debate over data centers.

By contrast, the essay says the First Industrial Revolution of the late 18th century brought cheaper clothing, cooking ware and reading material, while the Second Industrial Revolution of the late 19th century introduced household machines such as sewing machines, preserved food, indoor plumbing, photography, better light sources and bicycles. It argues even optimistic AI outcomes — new scientific discoveries, advanced therapeutics for rare diseases and potentially sustained economic abundance — risk being too indirect for citizens to credit companies like OpenAI or Anthropic.

The author, writing after a few weeks off for a wedding in New England, says the only AI uses during that time were search and making a wedding seating chart.

The essay says AI today primarily serves the elite, noting knowledge work is roughly half of the U.S. economy and that AI is or will soon be as fundamental as electricity there, with rapid improvements to agents expected in the next 18 months. It cites Engels' pause, described as the period from 1790 to 1840 when British working-class wages stagnated while per-capita GDP expanded rapidly during a technological upheaval. The author agrees with Doug O'Laughlin that tech headcount would likely shrink while knowledge work output explodes, and warns AI's brand could be tarnished and its development kneecapped, likening the risk to American nuclear power.

The essay also cites political backlash intertwined with Big Tech's history, says AI self-labeling as unsafe through doom and mass-unemployment proclamations compounds the problem, and suggests robotics and self-driving could become linked to AI in storytelling. It estimates powerful AI could go from effectively 0% to 90%+ adoption within the lifetime of younger followers, concluding the diffusion story will take longer than the fight against it.