Revisiting More Work for Mother: Generative AI and the Transformation of Work

Ruth Schwartz Cowan’s More Work for Mother (1983) examined how technological innovation (such as the flower mill, iron stove, or microwave) affected the American household. In the first instance, these inventions appeared to make life less burdensome, but in reality, they not only failed to do so, they worsened existing labor inequalities along gender lines. While these technologies often emancipated men from burdensome tasks (milling, collecting wood, and household tasks generally), mothers and women now had to do existing tasks by themselves, such as cooking, cleaning, and childrearing, as men left the house to work in various industries. Some tasks were to be performed more often, such as washing clothes once the washing machines made their appearance or cooking individualized meals for husband and kids at various times a day as the freezer in combination with the microwave created a ‘time-machine’ for food. This seminal text provides an important model for how to study the effects of technology on various forms of labor while remaining sensitive to varying effects on gender, race, class, and various other workplace vulnerabilities. Cowan provides us with at least two important lessons about the disruptive effects of technology on work. (1) The effects are never black and white, they don’t make things just better or worse, either emancipate or oppress. In fact, (2) we cannot rely on existing criteria for assessing the positive or negative effects of technology on social practices. Indeed, what Cowan shows so well is that new technologies affect labor practices in ways that make us reassess the meaning of many aspects of work, what counts as time consuming, burdensome, the location of work, hours of work, reasonable compensation, and so on. These technologies transform the meaning of work, its spatial and temporal organization, and the standards of what counts as ‘good’ or ‘just’ work and workplace practices. An interesting case study to help us think with Cowan about digital technology is Schrage’s “A Spreadsheet Way of Knowledge.” (1999) This analysis of the impact of spreadsheet technology introduced in the late 70s and early 80s on various types of office work shows how digital technology changed the meaning of office work, what counts as valuable work, what counts as fruitful collaboration, and what counts as good evidence or argument for the quality of work itself or new products and business. But as I’ll argue, these impacts were different when compared to current impacts of Generative AI like ChatGPT and Gemini on the workplace. After discussing Cowan and Schrage as important case studies for thinking about (digital) technology and labor, I re-apply their key insights to Generative AI in three different types of workplace: the household, the creative industry, and education. As I will argue from emerging data on their deployment, these technologies also create more work for some and not others, altering the frequency of work, the duration of work, the spatial organization of work, and the nature of specific tasks themselves.