Like a puppy playing with the long stick which is the risk-uncertainty conundrum, we chew energetically on the risk end, letting the uncertainty end drag in the dust. The stick is shaped, I argue, by Newtonian humanism. It combines the scientific and humanist stances that have co-evolved in modern times, constituting a commonsensical, internally inconsistent, worldview. And that view bends the analysis of the political world toward controllable risk, sidestepping or silencing unruly uncertainty.

Bankers rely on sophisticated risk models when they place their bets, informed by what they understand to be the rational beliefs they and others hold about the world. In a financial crisis, however, on a moment’s notice those beliefs can morph into panics, revealing unacknowledged uncertainties that had existed all along (section 1). What bankers, traders, government officials, and many of us do all too rarely is to acknowledge the pervasiveness of an uncertain future that we may intuit but cannot know. Without firm knowledge about the future, actors are guided by confidence-instilling conventions. Social conventions, such as risk-management models, were widely believed in and adopted to control uncertainty. These models generated endogenously a systemic crisis (section 2). The complementarity of the small world of risk with the large world of uncertainty is reflected in economic practices such as accounting and arbitrage (section 3). The Federal Reserve has relied heavily on story-telling (section 4). Going beyond the analysis of finance this chapter ends by discussing the denial of the risk-uncertainty conundrum by the reigning theory in the field of international political economy (section 5).

The Introduction explains the ‘theses and documents’ mode of proceeding, provides a quick overview of the period covered historiography, including recent work by political scientists, explains the economic underpinnings of the religious systems analysed, and introduces the concept of ‘deep structure’.

Chapter 4 elaborates a new theory of chilling effects – as conformity and compliance. The author argues that chilling effects are best understood as a more powerful form of conformity and compliance – just like conformity, chilling effects reflect a behavioral tendency to self-censor and conform in the face of threats like surveillance, uncertain laws, or personal threats. The chapter also elaborates what the author deems the four “chilling effect” factors: observation; uncertainty; personalization or personal threats; and power and authority, which help predict and explain chilling effects. The chapter explains not only why chilling effects are so powerful in their impact on our behavior, but also their additive effects – how each additional chilling effect “factor” amplifies or magnifies the impact and scope of a chilling effect.

Pearl Harbor demonstrates that war can occur when coercion (e.g., economic sanctions) works too well. To investigate this dynamic, we also engage another important, but controversial, question in this case – namely, whether the United States (US) president Franklin D. Roosevelt (FDR) deliberately sought war with Japan as a way to enter the war in Europe. Contrary to some scholars, our analysis concludes that FDR was aware of the total oil embargo that Acheson implemented and that FDR wanted war. Indeed, the US made only one serious attempt to avoid war – the modus vivendi proposal. FDR supported the proposal because he thought it would give the US more time to prepare. Tojo may have entertained the proposal, but he never received it because Chiang Kai-shek and Churchill vetoed it. The latter needed the US to intervene in the war to increase their chances of winning. This is yet another example of alliances promoting war – in this instance, by vetoing a peace proposal. Finally, we consider why Japan was willing to attack the US, even though it knew the US was more powerful.

Decision theory and decision making are multidisciplinary topics. Decision theory includes psychology, especially cognitive psychology, because decisions are cognitive processes. Decision theory also includes math, especially probability, as people often make decisions based on likelihood. Decision making is an applied topic pertaining to business, engineering, science, politics, other disciplines, and of course to personal decisions.

Descriptive models of decision theory explain decisions as cognitive processes, how and why people make the choices they do. Normative decision models describe how people should conceptualize a decision. Prescriptive models include mathematically based analyses that provide actionable solutions to real-world problems.

Decisions are made in one of three environments. Under certainty, the decision maker can make a choice and be sure what the outcome will be. Under risk, the decision maker will make a choice knowing in advance the probabilities of various outcomes. Under uncertainty, the possible outcomes and probabilities are unknown.

The chapter probes the relationship between law and performance in the context of transitional justice. By analyzing cultural productions and public performances such as films and theater plays, the chapter examines the ways in which lustration has become dramatized through the themes of secrecy, deception, betrayal, and the desire to know and not to know. While these cultural practices offer insight into the public intimate life of lustration, they also show how they become a site and form of social opposition and critical engagement with the terms of lustration and moral autopsy. In particular, the chapter offers a detailed ethnographic study of the experimental theater play by Wojtek Ziemilski, Small Narration (Mala Narracja), which highlights the layered relationship between theater and law and shows the extent to which the judicial and moralized forms of examination and judgment might travel and be contested by alternative forms of knowing, not-knowing, and relating to life, history, and politics.

Information is critical for understanding the conditions of what we care about and cumulative threats to it, so that we can design rules for intervention to protect or restore it. This is about more than just predicting cumulative impacts in the context of project-level environmental impact assessment. It requires gathering and aggregating, in an ongoing way, comprehensive, high-quality and shareable data and analysis, allocating and managing the costs of doing so, and ensuring that information is shared and can be accessed by governments, affected communities, and other stakeholders. Regulatory systems for addressing cumulative environmental problems should be information-makers rather than information-takers. Rules should actively shape the information that is produced, aggregated, analyzed, shared, and understood as legitimate to understand and respond to cumulative environmental problems. More than just a technical issue, information is about power and accountability for cumulative harm and responding to it – a critical influence on environmental democracy, environmental justice, and the rule of law. Real-world examples are provided of regulatory mechanisms that deal with information-related barriers to addressing cumulative environmental problems.

This chapter provides an end-to-end introduction to statistics; this highlights how statistics can be used to develop models from data, to quantify the uncertainty of such models, and to make decisions under uncertainty. The chapter also discusses how random variables are the key modeling paradigm that is used in statistics to characterize and quantify uncertainty and risk.

This chapter examines how exchange participants resolve uncertainties in corrupt transactions by focusing on the buying and selling of government positions, a typical form of corruption in China. Drawing on sixty-two in-depth interviews, this chapter suggests that corrupt transactions are highly embedded in strong-tie relationships, the power structure of which is often imbalanced. Exchange participants who are connected through strong ties have a strong incentive to cooperate and exchange favors because the cost of losing “hostages” (e.g., ganqing – deep feelings of emotional attachment – and human capital investment in maintaining exchange relations) and mianzi (“face,” which is used to describe reputation and social esteem) is high and difficult to recover. We also find that favor-seekers, who are often low-power actors, develop power-balancing strategies, such as bribe payments and disclosing compromising information, to win exchange opportunities and lower the risk of exploitation by high-power actors (power-holders who are favor-givers). Given that corrupt intermediaries are commonly brought in when a strong tie between favor-seeker and favor-giver does not exist, this chapter also empirically examines how corrupt exchanges involving intermediaries are governed. We find that face functions as a primary assurance and enforcement mechanism regulating corrupt transactions facilitated by intermediaries.

This chapter discusses techniques to measure uncertainty/risk and to make decisions that explicitly take risk into consideration. The chapter also discusses how to use principles of statistics and optimization in advanced decision-making techniques such as stochastic programming, flexibility analysis, and Bayesian optimization.

The chapter sets out a conceptual taxonomy for thinking systematically about old and new risks perceived to have a global dimension. It uses the complexity of those worldwide risks and the timeline of the disasters they portend to build the analytical scaffolding for understanding our current dynamic governing practices that are evolving to manage them in their diversity. It also sets out the scope conditions for both feasible insurance practices and for the political utility of insurance metaphors. As risk complexity deepens and time horizons lengthen, the potential role of market mechanisms shrinks, and collaborative government appears increasingly necessary.

This chapter introduces the major themes of the book. Insurance practices and related metaphors began expanding rapidly from a European base some 500 years ago. The simultaneous emergence of the modern state was hardly coincidental. Increasingly complex societies energized by market economies required protection from risks of various kinds. This required mobilizing and organizing private capital to achieve common goals. The deepening of markets and development of financial technologies now increases demands for protection beyond conventional borders. But where the fiscal power of the modern state underpinned national insurance and reinsurance systems, the absence of a global fiscal authority is exposed by rising cross-border, systemic, and global risks. That the background condition for necessary innovation in governance is uncertainty has also become undeniable.