The following narrative synthesises my notes on reading C.B. Frey’s The Technology Trap into a concise history of industrial evolution, tracing the shifting relationship between human labour and the machine from the 1700s to the AI-driven future of 2050.

The trajectory of industrial history is defined by a fundamental tension: while productivity is the engine of growth, its benefits have rarely been distributed equitably in the short term. During the First Industrial Revolution, the transition from the artisan to the operative marked a period where machines were, quite literally, the "ruin of poor folk." Factories often resembled prisons, breaking complex craftsmanship into simple, repetitive steps. While this mechanisation eventually benefited the general population through cheaper goods, the immediate effect was a "technology trap." Wages fell even as the economy grew, and those replaced by machines suffered in the churn of "technological unemployment."

By the Second Industrial Revolution and into the 1930s, the narrative shifted from replacement to enablement. As technology became more complex, it drove a demand for new, skilled occupations. Education became the primary tool for speeding up technology adoption across Europe and America, allowing the proletariat to join the middle classes. During this era, the wealth of workers became synonymous with their skills. Where technology was "enabling," it acted as a tailwind for wages; where it was "replacing," it deflated them. This created a widening gap between the "symbolic analysts"—those whose problem-solving and decision-making were aided by computers—and those performing routine, rules-based logic.

As we entered the age of Automation and Information Technology, the "middle-skill" tier of the workforce began to hollow out. A distinct geographical divide emerged between "nursery cities" — hubs of innovation and high-skilled talent—and "regions of despair" left behind by the digital tide. This divergence has fuelled profound socio-political consequences, including the rise of populism and a pervasive distrust of the economy among young adults. In these regions, the link between the degree of automation and shifting voting patterns is undeniable, as those without qualifications see their reality become increasingly detached from the college-educated elite.

We are now entering the AI Age, where the transition from "programmed machines" to "learning machines" fundamentally alters the labour landscape. Unlike previous waves of automation, AI does not need to replicate human methods to achieve human-level results. This requires a complete redesign of jobs and organisational structures. While firms will increasingly rely on data scientists and core business experts, the probability of job survival remains tethered to high qualifications and income.

Ultimately, the lesson of the last three centuries is clear: technology is a powerful driver of wage inequality when education fails to keep pace with innovation. As we look toward 2050, the divide will only sharpen. New jobs will be created at the top of the skill table. Consequently, workers with good skills will thrive under AI; those with poor skills will not work.