Increasing inequality and negative effects on job quality

Ethical and social risks of harm from language models

Weidinger et al. (2021)

Source DOI

Sub-category

Risk Domain

6Socioeconomic & Environmental

6.2Increased inequality and decline in employment quality

Social and economic inequalities caused by widespread use of AI, such as by automating jobs, reducing the quality of employment, or producing exploitative dependencies between workers and their employers.

"Advances in LMs, and the language technologies based on them, could lead to the automation of tasks that are currently done by paid human workers, such as responding to customer-service queries, translating documents or writing computer code, with negative effects on employment."(p. 33)

Entity— Who or what caused the harm

Human

Due to a decision or action made by humans

AI system

Due to a decision or action made by an AI system

Other

Due to some other reason or is ambiguous

Intent— Whether the harm was intentional or accidental

Intentional

Due to an expected outcome from pursuing a goal

Unintentional

Due to an unexpected outcome from pursuing a goal

Other

Without clearly specifying the intentionality

Timing— Whether the risk is pre- or post-deployment

Pre-deployment

Occurring before the AI is deployed

Post-deployment

Occurring after the AI model has been trained and deployed

Other

Without a clearly specified time of occurrence

Supporting Evidence (2)

"Exacerbation of income inequality A greater risk than large scale unemployment may be that, among new jobs created, the number of highly-paid “frontier” jobs (e.g. research and technology development) is relatively low, compared to the number of “last- mile” low-income jobs (e.g. monitoring the predictions of an LM application) (Autor and Salomons, 2019). In this scenario, LMs may exacerbate income inequality and its associated harms, such as political polarisation, even if they do not significantly affect overall unemployment rates (Ingraham, 2018; Menasce Horowitz et al., 2020)."(p. 33)

"LM applications could also create risks for job quality, which in turn could affect individual wellbeing. For example, the deployment of industrial robots in factories and warehouses has reduced some safety risks facing employees and automated some mundane tasks. However, some workers have seen an increase in the pace of work, more tightly controlled tasks and reductions in autonomy, human contact and collaboration (Gutelius and Theodore, 2019)"(p. 33)

Part of Automation, Access and Environmental Harms