Rodrigo Hernández-Ramírez , João Batalheiro Ferreira
{"title":"The Future End of Design Work: A Critical Overview of Managerialism, Generative AI, and the Nature of Knowledge Work, and Why Craft Remains Relevant","authors":"Rodrigo Hernández-Ramírez , João Batalheiro Ferreira","doi":"10.1016/j.sheji.2024.11.002","DOIUrl":null,"url":null,"abstract":"<div><div>This article examines the transformation of design work under the influence of managerialism and the rise of Generative Artificial Intelligence (GenAI). Drawing on John Maynard Keynes’s projections of technological unemployment and the evolving nature of work, it argues that despite advancements in automation, work has not diminished but rather devalued. Design, understood as a type of knowledge work, faces an apparent existential crisis. GenAI grows adept at mimicking the output of creative processes. The article explores how the fear of the end of design work fueled by the rise of GenAI is rooted in a misunderstanding of design work. This misunderstanding is driven by managerialism—an ideology that prioritizes efficiency and quantifiable outcomes over the intrinsic value of work. Managerialism seeks to instrumentalize and automate design, turning it into a controllable procedure to generate quantifiable creative outputs. The article argues why design work cannot be turned into a procedure and automated using GenAI. Advocates of these systems claim they enhance productivity and open new opportunities. However, evidence so far shows that flawed GenAI models produce disappointing outcomes while operating at a significant environmental cost. The article concludes by arguing for a robust theory of design—one that acknowledges the unique ontological and epistemic boundaries of design work and underscores why design cannot be reduced to a procedural output.</div></div>","PeriodicalId":37146,"journal":{"name":"She Ji-The Journal of Design Economics and Innovation","volume":"10 4","pages":"Pages 414-440"},"PeriodicalIF":1.8000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"She Ji-The Journal of Design Economics and Innovation","FirstCategoryId":"90","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2405872624000960","RegionNum":2,"RegionCategory":"社会学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"0","JCRName":"HUMANITIES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This article examines the transformation of design work under the influence of managerialism and the rise of Generative Artificial Intelligence (GenAI). Drawing on John Maynard Keynes’s projections of technological unemployment and the evolving nature of work, it argues that despite advancements in automation, work has not diminished but rather devalued. Design, understood as a type of knowledge work, faces an apparent existential crisis. GenAI grows adept at mimicking the output of creative processes. The article explores how the fear of the end of design work fueled by the rise of GenAI is rooted in a misunderstanding of design work. This misunderstanding is driven by managerialism—an ideology that prioritizes efficiency and quantifiable outcomes over the intrinsic value of work. Managerialism seeks to instrumentalize and automate design, turning it into a controllable procedure to generate quantifiable creative outputs. The article argues why design work cannot be turned into a procedure and automated using GenAI. Advocates of these systems claim they enhance productivity and open new opportunities. However, evidence so far shows that flawed GenAI models produce disappointing outcomes while operating at a significant environmental cost. The article concludes by arguing for a robust theory of design—one that acknowledges the unique ontological and epistemic boundaries of design work and underscores why design cannot be reduced to a procedural output.