Automation and Job Replacement in the Eyes of Conservatives and Liberals

Abstract

Technology and humans have coevolved over time, and continuous technological developments have helped improving humans’ quality of life. In this dissertation, I investigate consumers’ perceptions of the effects of technology and automation on time-orientation and how those perceptions vary as a function of political ideology. The first aim of this dissertation is to determine whether consumers perceive a relationship between time (tradition or modernity) and product production (by humans or by automation). The second aim of my dissertation is to determine whether political ideology plays a role in how consumers respond negatively to changes due to automation; in particular, whether conservative consumers perceive the consequences of greater automation more negatively than liberal consumers. In the opening sections of this dissertation, I review literature on various negative perceptions consumers have about technology (i.e., algorithm aversion, perceived loss of identity due to reduced consumer input, technological singularity, cyborg and dehumanization, uncanny valley, and automation) and then provide a narrower lens on consumer perceptions of impacts of automation on the labor force. I follow this literature review with a summary of the relevant research on political ideology, examining conservatism versus liberalism. Next, I report the methodology and results of six studies, the first two of which examine the relationship between time-orientation (tradition or modernity) and automation production (primarily by human or by automation), and the last four of which examine the time orientation and preferences for tradition over modernity in the context of political ideology. Results, in general, support my hypotheses. In Studies 1 and 2, consistent with hypotheses, I show that consumers perceive a product manufactured by automated approaches (e.g., an algorithm-based computer program) to have a more modern appeal and a human-made product to have a more traditional appeal. Similarly, consumers perceive products having a traditional (modern) appeal to be mainly produced by humans (automated approaches). In the next four studies, I hypothesize and empirically show that consumers who support a conservative political ideology respond more negatively to technology-driven changes (e.g., job replacement) and products produced by automated methods (vs. humans) than liberals. The different views of technology by conservatives and liberals exist even when national surveys suggest that liberals and conservatives have been similarly impacted by technology in a negative way (Study 3). Further, while conservatives consistently respond negatively toward changes due to automation because conservatism embraces tradition and the past, liberals do so only when they are prompted to think about the meanings associated with tradition (Study 4). In Study 5, participants are given a scenario in which firms either replace humans with automation, or automation does not replace humans. Results indicate that conservatives consistently felt a collective nostalgia for the past, regardless of condition, whereas liberals felt this nostalgia only when the scenario stated that firms are replacing humans. Finally, in Study 6, I show that when learning products are manufactured primarily through automation (and not by humans), conservatives perceived seeking jobs to be increasingly difficult, which spilled over to lower their evaluations of those products, whereas the same effects for liberals did not occur. The dissertation contributes to the extant literature related to technology adoption and time perception (e.g., how consumers associate technology with time orientation), political psychology and automation (by documenting another instance in which conservatives and liberals express diverging views), and research on handmade products (i.e., conservative consumers prefer products produced by humans more than liberal consumers). Practically, using the current research findings, I derive ideology-based recommendations to help firms that are considering an increase in the use of technology and automation, specifically by targeting conservative and liberal consumers differently. I also comment on how results might be used by policymakers to address increasing divisions between the political left and right.