Overcoming Illusions of Control: How to Nudge and Teach Regulatory Humility
Dunlop, Claire A.; Radaelli, Claudio M.
Date: 14 September 2015
In this chapter we focus on how to use insights from behavioural theory in the process of impact assessment of EU policy proposals. Over the last decade, the European Commission and more generally the European Union (EU) have developed an integrated approach to impact assessment of policy proposals – legislative or not. The impact ...
In this chapter we focus on how to use insights from behavioural theory in the process of impact assessment of EU policy proposals. Over the last decade, the European Commission and more generally the European Union (EU) have developed an integrated approach to impact assessment of policy proposals – legislative or not. The impact assessment process is now a major step in the development of proposals by the European Commission. Recently, the European Parliament being biased in this way!!as invested in analytical capacity to work dialogically with the Commission on this issue. Extant literature has established that the EU impact assessment system is, comparatively speaking (for example, in comparison to the systems of the 28 Member States and the United States [US]), sufficiently robust and comprehensive (Fritsch et al., 2013; Renda, 2011; Radaelli, 2009; Wiener and Alemanno, 2010). In the debate of how to conduct impact assessment and train policymakers, there are calls for integrating the insights of behaviour science into policymaking and design regulatory options that take into account the various biases that affect citizens’ responses (Alemanno and Spina, 2013; John, 2013; John et al., 2013; Sunstein, 2011; Van Bavel et al, 2013; Vandebergh, Carrico and Schultz, 2011). But policymakers have a brain too, and therefore their own choices can be biased. The starting point for this chapter is the potential impact of one over-arching bias – the illusion of control (Langer, 1975). The proposition is that this illusion – which leads humans to over-estimate their competence and ability to control outcomes – may be particularly damaging when the tendency to regulate is institutionalised. Specifically, while the EU impact assessment process obliges policymakers to consider the status quo option (non-intervention), this is rarely ever selected. We should be clear: we do not claim that cognitive biases explain the preference for public intervention. There are different political and economic justifications for intervention. An organisation can also deliberatively decide to manipulate the IA procedures towards interventionist choices. If this is so, cognitive biases have no role to play since the organisation is not misdiagnosing the facts; rather it is manipulating them. Rather, we are interested in increasing policy makers’ awareness of ‘regulatory humility’ (Dunlop and Radaelli, 2015b). We believe this should be encouraged among policy-makers, and specifically that the option of not using public intervention (so called ‘do nothing’ option in IA) be given due consideration – whether it is rejected or not. The classic policy-making literature has always pointed toward the limits of policymaking and policymakers (notably, Hogwood and Gunn, 1984; Simon, 1956; Vickers, 1965: chapter 8; Wildavsky, 1979: especially part 2). The increased complexity of the policy environment, the difficulty of getting evidence into policy, and greater clarity about human biases have all led to a re-discovery of these limitations. The result has been a renewed call for regulatory humility and humble decision-making (Dunlop and Radaelli, 2015b; Etzioni, 2014). We are interested in how EU policymakers might be de-biased in two main ways: first by structuring IA in ways that encourage policymakers act in ways that work with biases and second by using training to stimulate awareness and reflection about the biases and their possible impact on policymakers’ work. The chapter is structured as follows. In section one, we set up the proposition that EU policymakers are especially susceptible to an illusion of control. Then we explore what can be done to combat a pre-eminent bias. We outline two categories of solutions. In section two we look at how the IA system in the EU can be implemented and amended in ways that ‘go with the grain’ of cognitive biases (Dolan et al, 2009: 7). Here, we accept the reality of that policymakers often operate in ‘fast’ mode (Kahneman, 2011). Rather than try to re-wire the policymaker’s brain, we focus on re-wiring the context within which they work to ensure that what is automatic to them is also beneficial to policymaking. In short, how can we nudge EU policymakers to explore the ‘do-nothing option’, and indeed all policy options, with humility about the control they can exercise? Section three takes a slightly different tack. Here we focus on how policymakers can be exhorted to engage in more ‘slow’ thinking about the biases they carry. Such reflection can be triggered through training. We explore the possible teaching tools that can be and are being used including in-class behavioural experiments. The chapter concludes with a discussion of how some of these ideas can be taken forward by the Commission.
College of Social Sciences and International Studies
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