Dilemmas in a general theory of planning

An s-frame agenda for behavioral public policy research

We have previously argued thatbehavioral scientists have been testing and advocating individualistic (i-frame) solutions to policy problems that have systemic (s-frame) causes and require systemic solutions. Here, we consider the implications of adopting an s-frame approach for research. We argue that an s-frame approach will involve addressing different types of questions, which will, in turn, require a different toolbox of research methods.

Why Science Can't Settle Political Disputes

Attempts to scientifically “rationalize” policy, based on the belief that science is purified of politics, may be damaging democracy

The problem of knowledge in the Anthropocene

In the twentieth century, debates about economic planning were largely shaped by arguments concerning knowledge and the acquisition of information. As the century drew to a close, the dispute was a...

Morality vs. Politics as a Framing Problem: How (Not) to Misunderstand the Fight Against Climate Change

Topoi - This paper is guided by two research hypotheses: (1) In contemporary public discourse, many of the most urgent political problems are predominantly framed and understood in moral terms; (2)...

PUBLIC POLICY NETWORKS AND ‘WICKED PROBLEMS’: A NASCENT SOLUTION?

The last two decades have seen a shift in public services organizations from hierarchies to networks. Network forms are seen as particularly suited to handling ‘wicked problems'. We make an assessmen...

The Tragedy of the Commons

The population problem has no technical solution; it requires a fundamental extension in morality.

The i-frame and the s-frame: How focusing on individual-level solutions has led behavioral public policy astray

An influential line of thinking in behavioral science, to which the two authors have long subscribed, is that many of society's most pressing problems can be addressed cheaply and effectively at the level of the individual, without modifying the system in which the individual operates. We now believe this was a mistake, along with, we suspect, many colleagues in both the academic and policy communities. Results from such interventions have been disappointingly modest. But more importantly, they have guided many (though by no means all) behavioral scientists to frame policy problems in individual, not systemic, terms: To adopt what we call the “i-frame,” rather than the “s-frame.” The difference may be more consequential than i-frame advocates have realized, by deflecting attention and support away from s-frame policies. Indeed, highlighting the i-frame is a long-established objective of corporate opponents of concerted systemic action such as regulation and taxation. We illustrate our argument briefly for six policy problems, and in depth with the examples of climate change, obesity, retirement savings, and pollution from plastic waste. We argue that the most important way in which behavioral scientists can contribute to public policy is by employing their skills to develop and implement value-creating system-level change.

Field Theory: AI as Social Science Question, Object & Tool

Uses of advanced artificial intelligence are changing how societies organize labor, govern, produce knowledge, and make meaning. In light of these developments, this essay argues that AI models, tools, and systems pose three interrelated imperatives for social science: they demand renewed attention to social theories of how technology, human experience, and social order are entangled; they require study as objects of inquiry in their own right; and they offer capabilities that may transform—or upend—the practice of social investigation itself. From Weber’s analysis of rationalization to Du Bois’s study of technology and inequality to contemporary scholarship on algorithmic governance, the essay examines what social science distinctively offers: the capacity to historicize the apparently unprecedented, to trace connections across scales, and to center those most affected by technological change. It identifies how algorithmic systems are remaking the distribution of opportunity and risk as a central task of social inquiry and asks what futures social science might help bring into being.

Wicked problem

In planning and policy, a wicked problem is a problem that is difficult or impossible to solve because of incomplete, contradictory, and changing requirements that are often difficult to recognize. It refers to an idea or problem that cannot be fixed, where there is no single solution to the problem; "wicked" does not indicate evil, but rather resistance to resolution. Another definition is "a problem whose social complexity means that it has no determinable stopping point". Because of complex interdependencies, the effort to solve one aspect of a wicked problem may reveal or create other problems. Due to their complexity, wicked problems are often characterized by organized irresponsibility.

Putting nudges in perspective

Conventional economic policy focuses on ‘economic’ solutions (e.g. taxes, incentives, regulation) to problems caused by market-level factors such as externalities, misaligned incentives and information asymmetries. By contrast, ‘nudges’ provide behavioural solutions to problems that have generally been assumed to originate from limitations in human decision making, such as present bias. While policy-makers have good reason for exploiting the power of nudges, we argue that these extremes leave open a large space of policy options that have received less attention in the academic literature. First, there is no reason that solution and problem need have the same theoretical basis: there are promising behavioural solutions to problems that have causes that are well explained by traditional economics, and conventional economic solutions often offer the best line of attack on problems of behavioural origin. Second, there is a wide range of hybrid policy actions with both economic and behavioural components (e.g. framing a tax or incentive in a specific way), and there exist many societal problems – perhaps the majority – that arise from both economic and behavioural factors (e.g. firms’ exploitation of consumers’ behavioural biases). This paper aims to remind policy-makers that behavioural economics can influence policy in a variety of ways, of which nudges are the most prominent but not necessarily the most powerful.

Who Decides Who Decides? - Sociocracy For All

Who Decides Who Decides is a book for starting groups with sociocracy - a guide for governance and decision-making that's clear and inclusive.

How we rank the world's most pressing problems (and why)

We started with global health, then pandemics. Now we focus on AI risk. How our views changed and what problems we'd recommend you work on today.

New Studies: How Commercial Forces Make Science Less Reliable

Computational social science has been distorted by commercial forces, and AI is making it worse.