‘Hypernudge’: Big Data as a mode of regulation by design
DOI:
10.1080/1369118X.2016.1186713
Karen Yeungab*
Received: 16 Oct 2015
Accepted: 2 May 2016
Published online: 22 May 2016
ABSTRACT
This paper draws on regulatory governance scholarship to argue that
the analytic phenomenon currently known as ‘Big Data’ can be
understood as a mode of ‘design-based’ regulation. Although Big Data
decision-making technologies can take the form of automated
decision-making systems, this paper focuses on algorithmic
decision-guidance techniques. By highlighting correlations between
data items that would not otherwise be observable, these techniques
are being used to shape the informational choice context in which
individual decision-making occurs, with the aim of channelling
attention and decision-making in directions preferred by the ‘choice
architect’. By relying upon the use of ‘nudge’ – a particular form
of choice architecture that alters people’s behaviour in a
predictable way without forbidding any options or significantly
changing their economic incentives, these techniques constitute a
‘soft’ form of design-based control. But, unlike the static Nudges
popularised by Thaler and Sunstein [(2008). Nudge. London: Penguin
Books] such as placing the salad in front of the lasagne to
encourage healthy eating, Big Data analytic nudges are extremely
powerful and potent due to their networked, continuously updated,
dynamic and pervasive nature (hence ‘hypernudge’). I adopt a
liberal, rights-based critique of these techniques, contrasting
liberal theoretical accounts with selective insights from science
and technology studies (STS) and surveillance studies on the other.
I argue that concerns about the legitimacy of these techniques are
not satisfactorily resolved through reliance on individual notice
and consent, touching upon the troubling implications for democracy
and human flourishing if Big Data analytic techniques driven by
commercial self-interest continue their onward march unchecked by
effective and legitimate constraints.
http://www.tandfonline.com/doi/abs/10.1080/1369118X.2016.1186713