Pub Date : 2023-10-01DOI: 10.1215/2834703x-10734026
Katherine Bode, Lauren M. E. Goodlad
Abstract This introductory article calls attention to the shift from the “big data” discourse of the 2000s to the current focus on “AI” in its supposedly “responsible” and “human-centered” forms. Such rhetoric helps deflect attention from the profitable and surveillant accumulation of data and the worrisome concentration of power in a handful of companies. Alert to this problematic political economy, the issue's editors engage recent theories of data capitalism and argue that attention to processes of datafication helps to elude the pitfalls of data positivism, data universalism, and unintentional criti-hype. As the authors touch upon each contribution to this special issue, they call for critical AI studies to forge an interdisciplinary community of practice, alert to ontological commitments, design justice principles, and spaces of dissensus.
{"title":"Data Worlds: An Introduction","authors":"Katherine Bode, Lauren M. E. Goodlad","doi":"10.1215/2834703x-10734026","DOIUrl":"https://doi.org/10.1215/2834703x-10734026","url":null,"abstract":"Abstract This introductory article calls attention to the shift from the “big data” discourse of the 2000s to the current focus on “AI” in its supposedly “responsible” and “human-centered” forms. Such rhetoric helps deflect attention from the profitable and surveillant accumulation of data and the worrisome concentration of power in a handful of companies. Alert to this problematic political economy, the issue's editors engage recent theories of data capitalism and argue that attention to processes of datafication helps to elude the pitfalls of data positivism, data universalism, and unintentional criti-hype. As the authors touch upon each contribution to this special issue, they call for critical AI studies to forge an interdisciplinary community of practice, alert to ontological commitments, design justice principles, and spaces of dissensus.","PeriodicalId":500906,"journal":{"name":"Critical AI","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135457801","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-10-01DOI: 10.1215/2834703x-10734016
Lauren M. E. Goodlad
Abstract This editor's introduction welcomes readers to a new interdisciplinary undertaking. The community of practice Critical AI addresses hopes to bring critical thinking of the kind that interpretive disciplines foster into dialogue with work by technologists and others who share the understanding of interdisciplinary research as a powerful tool for building accountable technology in the public interest. Critical AI studies aims to shape and activate conversations in academia, industry, policymaking, media, and the public at large. The long and ongoing history of “AI,” including the data-driven technologies that now claim that name, remains riddled by three core dilemmas: (1) reductive and controversial meanings of “intelligence”; (2) problematic benchmarks and tests for supposedly scientific terms such as “AGI”; and (3) bias, errors, stereotypes, and concentration of power. AI hype today is steeped in blends of utopian and dystopian discourse that distract from the real-world harms of existing technologies. In reality, what is hyped and anthropomorphized as “AI” and even “AGI” is the product not only of technology companies and investors but also—and more fundamentally—of the many millions of people and communities subject to copyright infringement, nonconsensual use of data, bias, environmental harms, and the low-wage and high-stress modes of “human in the loop” through which systems for probabilistic mimicry improve their performance in an imitation game.
{"title":"Editor's Introduction: Humanities in the Loop","authors":"Lauren M. E. Goodlad","doi":"10.1215/2834703x-10734016","DOIUrl":"https://doi.org/10.1215/2834703x-10734016","url":null,"abstract":"Abstract This editor's introduction welcomes readers to a new interdisciplinary undertaking. The community of practice Critical AI addresses hopes to bring critical thinking of the kind that interpretive disciplines foster into dialogue with work by technologists and others who share the understanding of interdisciplinary research as a powerful tool for building accountable technology in the public interest. Critical AI studies aims to shape and activate conversations in academia, industry, policymaking, media, and the public at large. The long and ongoing history of “AI,” including the data-driven technologies that now claim that name, remains riddled by three core dilemmas: (1) reductive and controversial meanings of “intelligence”; (2) problematic benchmarks and tests for supposedly scientific terms such as “AGI”; and (3) bias, errors, stereotypes, and concentration of power. AI hype today is steeped in blends of utopian and dystopian discourse that distract from the real-world harms of existing technologies. In reality, what is hyped and anthropomorphized as “AI” and even “AGI” is the product not only of technology companies and investors but also—and more fundamentally—of the many millions of people and communities subject to copyright infringement, nonconsensual use of data, bias, environmental harms, and the low-wage and high-stress modes of “human in the loop” through which systems for probabilistic mimicry improve their performance in an imitation game.","PeriodicalId":500906,"journal":{"name":"Critical AI","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135457826","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：