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

Author:

Aula Ville1ORCID,Bowles James2ORCID

Affiliation:

1. Department of Media and Communications, London School of Economics and Political Science, London, UK

2. Third Sector Research Centre, School of Social Policy, University of Birmingham, Birmingham, UK

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.

Funder

Economic and Social Research Council

Publisher

SAGE Publications

Subject

Library and Information Sciences,Information Systems and Management,Computer Science Applications,Communication,Information Systems

Reference55 articles.

1. Incremental Load in a Data Warehousing Environment

2. AI for the Common Good?! Pitfalls, challenges, and ethics pen-testing

3. Bloomberg (n.d.) Data for good exchange 2014. Available at: https://www.bloomberg.com/lp/d4gx-2014/ (accessed 26 November 2021).

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