Article:

Cities have proven to be the most successful form of human agglomeration and provides wide employment opportunities for its dwellers. As advances in robotics and artificial intelligence revive concerns about the impact of automation on jobs, a question looms: how will automation affect employment in cities? Here, we provide a comparative picture of the impact of automation across US urban areas. Small cities will undertake greater adjustments, such as worker displacement and job content substitutions. We demonstrate that large cities exhibit increased occupational and skill specialization due to increased abundance of managerial and technical professions. These occupations are not easily automatable, and, thus, reduce the potential impact of automation in large cities. Our results pass several robustness checks including potential errors in the estimation of occupational automation and sub-sampling of occupations. Studies have provided the first empirical law connecting two societal forces: urban agglomeration and automation's impact on employment. Introduction cities, which accommodate over half of the world's population, are modern society's hubs for economic productivity and innovation. As job migration is the leading factor in urbanization, policymakers are increasingly concerned about the impact of artificial intelligence and automation on employment in cities. While researchers have investigated automation in national economies and individual employment, it remains unclear a priority how cities naturally respond to this threat. In a world struggling between localism and globalism, a question emerges: how will different cities cope with automation? Answering this question has implications on everything from urban migration to investment, and from social welfare policy to educational initiatives. To construct a comparative picture of automation in cities, our first challenge is to get reliable estimates of how automation impacts workers. Additionally, technology-driven efficiency may redefine the skill requirements of occupations and increase employment in both low and high-skilled jobs. Even if we take current estimates of the absolute risk of computerization of jobs with skepticism, these estimates can provide useful guidance about relative risk to different cities that is robust to errors in the estimates pro-vided by Frey & Osborne and Arntzet al. We can interpret the 'risk of computerization' estimates as an educated guess about which occupations will experience greater adjustment due to machine substitution of a large portion of their content. These adjustments represent a significant cost to an urban system from both technological unemployment and expensive worker retraining programs. A priority, it is not obvious whether large cities will experience impact from automation. On one hand, an influx of occupational diversity explains the wealth creation, innovation, and success of cities. On the other hand, cities connect people with greater efficiency. This enables a greater division of labor that increases overall productivity through occupational specialization. However, the division of labor may facilitate automation as it identifies routine tasks and encourages worker modularity. If these modular jobs are at greater risk of computerization, then more workers may be impacted by automation in large cities. These observations pose a puzzle: are the forces of diversity, specialization and the division of labor shaping a city's ability to accommodate automation. Nevertheless, we observe a strong trend relating city size to automation impact that is robust to errors in the automatability of individual occupations and occupational subsampling. For example, the estimates of occupational automation, which we employ in our analysis, would need to be severely flawed (errors over 50%) for the negative dependency on city size to disappear. Recognizing that small cities will experience larger adjustments to automation calls on policymakers to pay special attention to the pronounced risks we have identified. Despite being seemingly unrelated societal forces, we uncover a positive interplay between urbanization and automation. Larger cities not only tend to be more innovative, but also harbor the workers who are prepared to both use and improve cutting-edge technology. In turn, these workers are more specialized in their workplace skills and less likely to be replaced by automated methods in the fore-seeable future.

Question: What specifics from the article above give you hints that it seems to take the approach of social constructivism or technological determinism or is there a combination of both approaches?