The concept of automation, and the analysis of it using task-based models, leads to some general rules that appear to govern the interaction of machines and workers. Here are six fundamental tendencies in the operation of automation and its interaction with human labour that aid in assessment:

Labour is being replaced by automation.

If a machine can perform a task that humans currently perform, it will do so with greater precision, speed, and at a lower cost—but such substitution has limitations.

Machines replace tasks, not jobs.

A job is a collection of tasks, and even in the most extreme scenarios, machines are unlikely to replace all tasks in any one occupation.

Automation has the potential to increase demand and thus create jobs.

Automation-driven cost and quality improvements can boost demand to the point where any job losses are offset.

The addition of capital and labour promotes innovation.

When machines perform routine, time-consuming tasks, human capacity is freed up to develop new products and tasks.

Technology possibility is not the same as technological reality.

There are numerous reasons why technological adoption falls short of potential, so equating technological potential with likely projected outcomes is a mistake.

Workplace activity that isn't taken over by automation is complemented by it, increasing the value of the remaining human tasks.

MIT economist David Autor offers a simplified framework for calculating the net impact of automation on employment and wages. He emphasises three primary dynamics in it:

What technology does not replace, it enhances.

Workers who perform tasks that machines can perform are more likely to benefit from automation than workers who perform tasks that machines can complete.

Wages will be determined by how easily in-demand roles can be filled.

Wage gains for remaining human-completed tasks will be greater as entry barriers (e.g., education, training, certification) rise.

The number of jobs in an industry will be determined by the complex interaction of price, quality, and wealth changes caused by automation.

In the AI era, almost no occupation will be unaffected by technological change. Office administration, production, transportation, and food preparation are among the most vulnerable occupations. Such jobs are considered "high risk," with more than 70% of their tasks potentially automatable. All of these activities involve either routine, physical labour or information collection and processing.

However, "high-risk" jobs account for only one-quarter of all jobs. The remaining, more secure jobs cover a broader range of occupations, from highly educated professional and technical roles to low-paying personal care and domestic service work characterised by non-routine or abstract activities and social and emotional intelligence. 

Automation will occur everywhere, but the extent of its impact will vary depending on the local industry, task, and skill mix. Smaller, more rural communities appear to be significantly more vulnerable to the automation of current-task content than larger ones. This relationship holds true when comparing metropolitan areas to rural areas as well as metros of varying sizes. Workers' educational attainment will be critical in the country's 100 largest metros.

The labour market is sharply segmented by educational attainment, gender, age, and racial-ethnic identity, ensuring that some demographic groups will bear a greater burden of adjusting to the AI era than others. The likely divisions are obvious: Men, youth, and less educated workers, as well as underrepresented groups, appear to be particularly vulnerable to automation in the coming years. Young workers and Hispanics will be particularly vulnerable.

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