Labor and Creativity

"Intellectual Property and Ownership: Rights to the training data and replicated or plagiarized work in addition to and rights to generated outputs are ongoing legal and policy discussions, often by specific modality.Impacts to people and society will necessarily coexist with impacts and development of intellectual property law."(p. 16)

"Key considerations about the impact of automation and AI on employment center on whether these technologies will generate new jobs or, in contrast, will lead to a large-scale worker displacement in the next future. Narratives about machines taking over the production of goods and services resurfaced periodically: from the early nineteenth-century Luddite movement against the introduction of the spinning jenny in textile manufacturing, to British farmers’ Swing Riots against mechanical threshers, to protests against the dial telephone, introduced in the U.S. during the Great Depression and responsible, according to its detractors, of mass unemployment among telephone operators [221]. Labor in system development such as crowdwork can encompass short-lived relations between independent contractors and their clients offers several advantages over traditional forms of employment. For example, companies can avoid overhead personnel costs (e.g., HR), while contract workers can decide how much, from where, and when to work. However, as contractors, crowdworkers are excluded from employment protective norms. As a result, they can be paid significantly less than minimum wage, have no access to healthcare benefits, are not subject to working time restrictions, and may not have access to holidays or sick leaves [188]. Further, crowdworkers are exposed to increasingly subtle forms of surveillance, which is becoming essential for implementing algorithmic forms of management, understood as "a diverse set of technological tools and techniques to remotely manage workforces [and] enable automated or semi-automated decision-making" [162]. The goal of full automation remains perpetually beyond reach since the line between what machines can and cannot solve is constantly redrawn by AI advancements. This phenomenon, the "paradox of automation’s last mile", is a self-propelling cycle in which every solution to automation problems creates new problems to be automated, and hence new demands for ghost workers [93]."(p. 16)