Briefing: Autonomous Vehicles Are Already Here

Written: May 26, 2018 | Language: Chinese | Author: E. J. Original article: https://mp.weixin.qq.com/s/xnJ_oKpHkEiRFk4deHOuMQ (WeChat — not publicly crawlable)

Core claim: Autonomous vehicle displacement will hit truck drivers first, not urban passenger vehicles. The economic case is overwhelming. The human cost — for workers with no union, no degree, and an average age of 49 — has no solution in sight. Written in May 2018, concurrent with Andrew Yang's The War on Normal People but independently and with broader economic modeling.

Manufacturing automation as precedent: US manufacturing employment fell from 17.5 million (2000) to 11.46 million (2010) — a loss of approximately 6 million jobs. Output rose. Approximately 80% of job losses (4.8 million) were caused by automation, not offshoring. The cost differential: $25/hour (human worker with benefits) vs. $8/hour (machine operating cost) = $17/hour savings × 4 million workers × 2,000 hours/year = $136 billion/year in reduced costs. These savings were reinvested in further automation.

Why trucks, not cars: Autonomous driving will first deploy on interstate highways, not dense urban environments. The author's projected sequence: (1) highway autopilot with driver present but resting → (2) convoy systems with one lead driver → (3) fully driverless highway operation → (4) human drivers handle only final urban 10–20 miles → (5) full autonomy end-to-end.

Truck driver profile: 3.5 million truck drivers in the US. 94% male. Average age: 49. Typical education: high school diploma. No union representation for most (many are owner-operators). Average annual income: $34,790 (2016) — above the $30,000 median middle-class threshold. Work conditions: 240 nights/year away from home, 11 hours/day driving. 88% have diabetes, hypertension, or other chronic conditions.

Economic case for automation:

US trucks cause 3,903 deaths and 110,000 injuries annually. 90% result from human error.

The reemployment problem: Manufacturing automation created new jobs — but for different people. Graduate degree holders in manufacturing increased 32% from 2000 onward. Of workers displaced in 2009–2011, 41%+ remained unemployed in 2012. Many exited the labor force entirely. Disability insurance recipients increased by 3.5 million nationally since 2000; in Michigan, half of the 310,000 workers displaced between 2003–2013 enrolled in disability insurance — permanently exiting the workforce. New jobs require credentials these workers do not have.

The cascade effect — $21 trillion at risk: Truck drivers spend approximately $6,000/year eating and lodging on the road (at $25/day × 240 nights). 3.5 million drivers × $6,000 = $21 billion/year in direct service industry spending. Eliminating or halving this spending cascades to fast food, rest stops, vending, motels, and the broader service economies of truck-dependent towns. The $168B/year industry saving comes at the cost of disrupting a much larger service economy. Some towns built entirely around trucking services face potential abandonment within the author's projected timeline.

Timeline (as of 2018): The author projected meaningful autonomous truck deployment within five years — by approximately 2023. Lobbying activity in Washington was already underway. Test facilities for autonomous trucks were operational on the outskirts of several cities.

Author's conclusion: Unlike more speculative future scenarios, autonomous trucking displacement is certain, already underway, and imminent. The displaced workers — middle-aged, high-school educated, unorganized, chronically ill — have no clear reemployment pathway. The economic gains accrue to the industry. The social costs are distributed to individuals, service towns, and public benefit systems.

Note: When the briefing is produced in 2026, it appears full autonomous truck deployment has progressed more slowly than projected in 2018, due primarily to regulatory friction and liability frameworks rather than technical limitations. The economic case remains intact. The displacement, when it arrives, will follow the pattern described. Also, The 2018 projection did not account for COVID-19, which simultaneously accelerated the economic case for autonomous trucking (driver shortages, supply chain fragility) and disrupted the deployment timeline (testing halts, capital market contraction, the shutdown of major players including Argo AI in 2022).

Truck Driver vs. Taxi Driver Comparison (2016)

Manufacturing Job Loss 2000–2010