The Co-Evolution of Policy and Technology: Integrating a Technology Perspective into Feedback Theory

Policy feedback is experiencing a revival in public policy research. Well-known early champions of feedback established a set of guiding questions, i.e. how “new policies create a new politics” (Schattschneider, 1935) and why “policies determine politics” (Lowi, 1972). Numerous researchers have applied these questions to (often very detailed) case studies (e.g., Campbell, 2003; Mettler, 2005). In terms of theorisation and conceptualization, Pierson’s seminal work (Pierson, 1993) had a lasting impact on general assumptions about feedback and feedback mechanisms, leading to an emphasis on path-dependency and policy lock-in. Positive feedback, in this view, is self-reinforcing, i.e. serving to stabilize or expand early policy choices, resulting in stable policy regimes. Researchers like Jacobs and Weaver (Jacobs & Weaver, 2015) instead argue for studying more closely self-undermining feedback that sets in motion processes reducing a policy’s political viability over time, rendering it unstable and resulting in policy change or termination (see also Campbell, 2012; Patashnik, 2008). Conceptually, Jacobs and Weaver (Jacobs & Weaver, 2015) argue that there is little justification for associating positive feedback mechanisms with the outcome of policy lock-in or stability, and for associating negative feedback mechanisms with policy change. Instead, they argue that positive feedback can be a key driver of policy change, while negative feedback can be a powerful stabilizing force. More empirical work, using this broader perspective on policy feedback, is needed to improve our understanding of the feedback mechanisms that result in policy stability or change. At the same time, feedback thinking remains predominantly applied in the (broadly defined) field of social policy (Beland, 2010; Burroughs, 2017). Generally, researchers in the field of social policy are, particularly in the US, interested in the partisan or voting effects of feedback processes from comprehensive policies like the Affordable Care Act (e.g., Béland et al., 2018). While this interest is certainly valid, it nonetheless leads to a narrow understanding of feedback as a policy output-mass feedback loop. Crucially, such an understanding does neither necessarily include elite feedback (e.g., from interest groups), nor the bigger socio-economic system that is targeted by policy in the first place. In other words, policy-induced outcomes are not systematically endogenised in feedback theory, leaving open the question of the precise role of feedback mechanisms in the long-term interplay between politics, policy and outcomes. While an earlier generation of studies of policy, politics and technology interactions effectively used policy feedback arguments (Jacobsson & Lauber, 2006; Strachan et al., 2009; Szarka, 2007), they did so almost entirely implicitly (see Laird & Stefes, 2009 for a rare exception). More recently, there is a growing and explicitly theorised interest in questions of long-term policy stability and change, policy effectiveness and the role of politics from researchers investigating socio-economic transitions (Meadowcroft, 2009; Geels et al., 2017; Roberts et al., 2018; Breetz et al., 2018; Schmidt & Sewerin, 2017). For these researchers, policy-induced technological change takes centre-stage, based on an understanding that grand societal challenges like the transition to a carbon-free energy system need policy intervention to foster technological innovation, nurture new actor(s) (coalitions) and limit the power of incumbents. A number of conceptual contributions even explicitly discuss how feedback logic can be harnessed for steering the temporal dynamics of policy (stability and) change (Levin et al., 2012; Jordan & Matt, 2014; Rosenbloom et al., 2019). Similarly, some researchers build implicitly on feedback concepts when discussing how the sequencing of policy can lead to self-reinforcing pathways and, over time, to a ratcheting-up of policy ambitiousness (Meckling et al., 2017; Pahle et al., 2018). Besides these conceptual contributions to the literature (explicitly and implicitly) dealing with feedback, researchers from the field of socio-economic transitions also have contributed important empirical insights: Lockwood (Lockwood, 2013) and Stokes (2013) have highlighted the continued existence of negative feedback, threatening the continuation of the UK Climate Change Act and the Ontario Feed-in Tariff, respectively. These findings tie in with the discussions about the prevalence of self-undermining feedback provoked by Jacobs and Weaver (Jacobs & Weaver, 2015) and others (see above). Integrating this emerging literature, focused on the nexus of politics and policy-induced technological change, into feedback theory seems a promising way forward: while policy feedback is a key concept in policy research across a number of disciplines and policy areas, it remains largely undertheorised and unspecified from a conceptual and methodological standpoint. Systematically thinking about technology and, specifically, the co-evolution of policy and technology is key for understanding long-term policy stability and change and the role of feedback therein. We argue that focusing on technology (or technological change) as policy-induced socio-economic outcome is key: technology (or technological change) is pervasive in modern societies but features high degrees of variance. More specifically, three reasons speak for analysing the co-evolution of policy and technology: First, technological change is a highly relevant phenomenon, as it is the primary driver of economic development (Schumpeter, 1942) and fundamentally changes the way humans live and interact with each other and with their natural environment. It is also the driver but also solution to societal challenges and mega-trends, such as climate change, the aging society, or digitalisation. Technological change is political (Winner, 1980) and, importantly, feeds back into the policy process (Schmidt & Sewerin, 2017). As such, agency in policy dynamics evolving around technological change will be particularly important, and feedback can be expected to be particularly strong (Lauber & Jacobsson, 2016). Second, technological change can happen fast or slow (Grubler et al., 2016) and trigger very different reactions by actors relevant in policy process. Innovation happens by building on and combining existing knowledge (Arthur, 2009). It can be competency enhancing, i.e., reinforcing existing institutional and market structures; or it can be competency destroying, i.e., reducing barriers for new entrants, thereby threatening incumbent actors (Christensen & Rosenbloom, 1995). Different types of technological change (fast, slow, competency enhancing or destroying) can result in very different feedback mechanisms Third, public policy and regulation have a strong influence on technological change (Lundvall 1992; Rosenberg 1982). Often, the public sector is the largest risk-taker in the development of new technologies, providing guidance, coordination, and finance, while creating demand, for example, through state-owned enterprises or public procurement (e.g., for the military) (e.g., Mazzucato 2015). Innovation scholars have argued that, more specifically, policy design features are highly important in explaining the effectiveness of policy approaches to induce technological change (Kemp & Pontoglio, 2011; Schmidt & Sewerin, 2018). There is renewed interests in conceptual and empirical questions related to policy design in the public policy literature (Howlett, 2014; Howlett & Cashore, 2009; Cashore & Howlett, 2007; Schaffrin et al., 2015; Peters et al., 2018). In policy feedback research, on the other hand, ‘policy’ or ‘policy change’ in different ways, often quite abstractly. In the words of Jordan and Matt (Jordan & Matt, 2014), “to [Pierson’s] evident frustration […], the policy feedback literature has continued to focus on rather broad elements of policy such as programmes and policy regimes” (Weaver, 2010; May & Jochim, 2013). The lack of attention towards the micro-level of policy design changes means that both theoretical assumptions about and conceptualizations of feedback effects of policy design are missing. Also, new technologies might result in new opportunities or challenges, which require new or significantly redesigned and adjusted policies (Hoppmann et al., 2014), i.e. new technologies might be “too” successful for the original policy to handle. This is in contrast to assumptions in feedback literature both from Jacobs and Weaver (Jacobs & Weaver, 2015) who theorize new policy options as primarily resulting from policy failure and from Pierson’s (Pierson, 2000, 1993) earlier notion of positive feedback leading to narrowing of available policy options because of lock-in. Technological change represents a highly relevant and diverse, sometimes even extreme, empirical field to study the systematic interplay between politics, policy and socio-economic outcome. Therefore, we argue that the integration of a technology perspective into policy feedback research would allow for the sharpening of theoretical assumptions and conceptualizations of key elements of feedback thinking. Empirically, we expect technology-feedback studies to produce highly relevant insights that can complement and potentially (partially) revise existing knowledge about feedback. The prime objective of this workshop is bringing together two diverse literatures and scholarly fields, namely policy feedback and innovation studies. To this end, we propose research questions (see below) that aim at addressing key theoretical and methodological issues stemming from integrating a technology perspective into policy feedback theory. We thus seek to facilitate greater conceptual and empirical clarity in the study of feedbacks, enabling a new wave of empirical studies. In this sense, this workshop expands significantly the scope of feedback-focused workshops at previous Joint Sessions (e.g., workshop #14 of the 2016 Pisa event, which focused specifically on public opinion). Research Questions *What role do technology-inherent differences play for long-term feedback loops? Does policy-induced technological change, for example, in the health sector play out differently than in, for example, the energy or transport sector? To which extent is the co-evolution of policy and technology sector-specific? *What are the mechanisms linking policy, technological change and politics? For example, does policy-induced technological change expand or narrow policy options and why? *What is the role of policy design for inducing interactions between policy, politics and technological change? Does policy design have a direct impact on the intensity of feedback effects? *How can the methodological challenges of studying the co-evolution of policy and technology be overcome? For example, how can research design effectively cater for the hen-and-egg problem underlying this co-evolution? *What is the role of political institutions in the co-evolution of policy and technology? For example, what is the effect of institutional variation on the intensity of (positive or negative) technology-policy feedback loops? *What is the role of agency in the long-term interactions of policy, politics and technological change? How can researcher effectively study, e.g., technology-related policy beliefs or preferences in (repeated rounds of) policy designing? *What (direct or indirect) impact do technology-spillovers have, both cross-sectoral and cross-country? Put differently, how does technological change in one jurisdiction feed back into the politics of another? 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