From big data epistemology to AI politics: rescuing the public dimension over data-driven technologies

Author:

Calzati Stefano

Abstract

Purpose The purpose of this paper is to explore the epistemological tensions embedded within big data and data-driven technologies to advance a socio-political reconsideration of the public dimension in the assessment of their implementation. Design/methodology/approach This paper builds upon (and revisits) the European Union’s (EU) normative understanding of artificial intelligence (AI) and data-driven technologies, blending reflections rooted in philosophy of technology with issues of democratic participation in tech-related matters. Findings This paper proposes the conceptual design of sectorial and/or local-level e-participation platforms to ignite an ongoing discussion – involving experts, private actors, as well as cognizant citizens – over the implementation of data-driven technologies, to avoid siloed, tech-solutionist decisions. Originality/value This paper inscribes the EU’s normative approach to AI and data-driven technologies, as well as critical work on the governance of these technologies, into a broader political dimension, suggesting a way to democratically and epistocratically opening up the decisional processes over the development and implementation of these technologies and turn such processes into a systemic civic involvement.

Publisher

Emerald

Subject

Computer Networks and Communications,Sociology and Political Science,Philosophy,Communication

Reference44 articles.

1. A ladder of citizen participation,2000

2. Datafied and divided: techno-dimensions of inequality in American cities;City and Community,2017

3. Are you ready for the era of big data?;McKinsey Quarterly,2011

4. Smart urbanism and smart citizenship: the neoliberal logic of ‘citizen-focused’ smart cities in Europe;Environment and Planning C: Politics and Space,2019

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