Stepping back from Data and AI for Good – current trends and ways forward

IF 6.5 1区 社会学 Q1 SOCIAL SCIENCES, INTERDISCIPLINARY
Ville Aula, Jameson Bowles
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引用次数: 1

Abstract

Various ‘Data for Good’ and ‘AI for Good’ initiatives have emerged in recent years to promote and organise efforts to use new computational techniques to solve societal problems. The initiatives exercise ongoing influence on how the capabilities of computational techniques are understood as vehicles of social and political change. This paper analyses the development of the initiatives from a rhetorical slogan into a research program that understands itself as a ‘field’ of applications. It discusses recent academic literature on the topic to show a problematic entanglement between the promotion of initiatives and prescriptions of what ‘good’ ought to be. In contrast, we call researchers to take a practical and analytical step back. The paper provides a framework for future research by calling for descriptive research on the composition of the initiatives and critical research that draws from broader social science debates on computational techniques. The empirical part of the paper provides first steps towards this direction by positioning Data and AI for Good initiatives as part of a single continuum and situating it within a historical trajectory that has its immediate precursor in ICT for Development initiatives.
从数据和人工智能走向美好——当前趋势和前进方向
近年来,出现了各种“数据向善”和“人工智能向善”倡议,以促进和组织使用新的计算技术解决社会问题的努力。这些举措对如何将计算技术的能力理解为社会和政治变革的工具产生了持续的影响。本文分析了这些举措的发展,从一个修辞口号到一个将自己理解为应用“领域”的研究项目。它讨论了最近关于这一主题的学术文献,显示了在促进主动性和“好”应该是什么之间的问题纠缠。相比之下,我们呼吁研究人员后退一步进行实践和分析。该论文呼吁对倡议的组成进行描述性研究,并从更广泛的社会科学关于计算技术的辩论中进行批判性研究,为未来的研究提供了一个框架。该文件的实证部分通过将数据和人工智能促进良好举措定位为一个单一连续体的一部分,并将其置于一个历史轨迹中,该轨迹在信息和通信技术促进发展举措中具有直接先导作用,为朝着这一方向迈出了第一步。
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来源期刊
Big Data & Society
Big Data & Society SOCIAL SCIENCES, INTERDISCIPLINARY-
CiteScore
10.90
自引率
10.60%
发文量
59
审稿时长
11 weeks
期刊介绍: Big Data & Society (BD&S) is an open access, peer-reviewed scholarly journal that publishes interdisciplinary work principally in the social sciences, humanities, and computing and their intersections with the arts and natural sciences. The journal focuses on the implications of Big Data for societies and aims to connect debates about Big Data practices and their effects on various sectors such as academia, social life, industry, business, and government. BD&S considers Big Data as an emerging field of practices, not solely defined by but generative of unique data qualities such as high volume, granularity, data linking, and mining. The journal pays attention to digital content generated both online and offline, encompassing social media, search engines, closed networks (e.g., commercial or government transactions), and open networks like digital archives, open government, and crowdsourced data. Rather than providing a fixed definition of Big Data, BD&S encourages interdisciplinary inquiries, debates, and studies on various topics and themes related to Big Data practices. BD&S seeks contributions that analyze Big Data practices, involve empirical engagements and experiments with innovative methods, and reflect on the consequences of these practices for the representation, realization, and governance of societies. As a digital-only journal, BD&S's platform can accommodate multimedia formats such as complex images, dynamic visualizations, videos, and audio content. The contents of the journal encompass peer-reviewed research articles, colloquia, bookcasts, think pieces, state-of-the-art methods, and work by early career researchers.
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