Datification in action

Diffusion and consequences of algorithmic decision-making 1

Authored by: Sue Newell , Marco Marabelli

The Routledge Companion to Management Information Systems

Print publication date:  August  2017
Online publication date:  August  2017

Print ISBN: 9781138666450
eBook ISBN: 9781315619361
Adobe ISBN:

10.4324/9781315619361.ch26

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Abstract

The widespread diffusion of devices capable of recording user data, whether these data are based on social networking or are collected from the sensors included in many new products are leading to a process that we can call ‘datification’ (everyone and everything is turned into data). These data are often subjected to analysis using algorithms either to identify trends (big data) or profile individuals (little data). In this chapter, we aim to illustrate the societal implications of big and little data (and underpinning use of algorithms) for private citizens/society and businesses. We focus on discriminations (related to big data) and privacy concerns (related to little data) and argue that laws and regulations do not currently protect, in full, citizens’ privacy and do not ensure that data-driven discrimination effects are minimized if not avoided. We discuss potential solutions involving the joint effort of citizens, businesses and lawmakers who should focus on promoting the development of new knowledge and innovation (opportunities emerging from big data analytics).

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