The first sociological experiments have been conducted in the second and third decades of the twentieth century, accompanied by a fierce debate about the possibilities and limits of the approach, which anticipated many of the critiques currently raised against the method. The chapter traces the development of experimental research in sociology from these beginning to modern perspectives. One of the reasons for the marginal position of experimentation in sociology has been the reluctance to give up full control of potentially intervening variables (called the ex post facto method) in favor of randomization. Inspirations from social psychology and, later, economics, have finally resulted in the experimental designs that are currently used in sociology.

This chapter explains why countries obtain nuclear latency. It introduces the drivers and constraints of latency. It conducts a statistical analysis to determine which variables are correlated with nuclear latency onset, and then analyzes twenty-two cases to identify the main motives for getting latency.

Traditional economics tells us that to meet policy goals, government should only do the minimum needed to fix a ‘market failure’. A new understanding shows that when the goals are innovation and change, a ‘do the maximum’ approach can be more effective. We should stop aiming to achieve ‘decarbonisation at least cost’, and instead aim to move to the clean economy at maximum gain.

A movement is gathering to overthrow the intellectual incumbents of economics. Started by students, advanced by academics, and funded by philanthropists, until recently it has remained largely unnoticed by governments. Now the world’s largest emerging economies are starting to take an interest. For the sake of avoiding dangerous climate change, the revolution cannot come too soon.

Estimates of the economic costs of climate change rely on guesswork in the face of huge uncertainties, and arbitrary judgements about what is important. The models can produce any number their creators want them to; and typically, they trivialise the risks. Despite being described as ‘worse than useless’ by leading academics, economic analysis of this kind has been credited with a Nobel Prize, and it continues to inform government policy.

Economics is not just about the allocation of scarce resources – how to ‘divide up the pie’. It is also about the creation of novelty, and the formation of new structures – how to make a pie in the first place. The new science of complexity, allied to old ideas of political economy, can help us understand how to create and change things quickly and at large scale. New economic thinking of this kind predicted the global financial crisis, but has barely begun to be applied to policy. It could transform the way we respond to climate change.

People often assume that to give ourselves a fighting chance of avoiding catastrophic climate change, we need either inspired political leadership, or a moral revolution in society. Both would be nice to have, but there are more plausible ways to make faster progress. They involve thinking differently. We need science that gives us risk assessment instead of prediction; economics that understands change instead of assuming stability; and diplomacy that focusses on international collaboration instead of unilateral national action.

The economics used by governments is based on ideas from the 1870s, when economists adopted the language of science, but not the method. To make the maths easy to solve, they assumed the economy was simple, predictable, and static. Nobody believes these assumptions are true, but they still shape analysis that informs policy. When the economy is complex, uncertain, and changing, this kind of analysis can lead us to bad decisions.

The financial system fulfils several quintessential roles within the economic framework. For instance, it expedites transactions by administering a secure and robust payment system. This mechanism not only assures the secure transference of financial assets but also accommodates transactions across borders, thus facilitating arm’s-length commercial interactions on a macro-economic scale. The financial system is also instrumental in mobilising savings from households that possess financial resources surplus to their immediate consumption needs. In doing so, it enables these households to accrue returns on their capital, thereby enhancing their consumption possibilities in subsequent periods.

In recent times, banks, financial organisations and technology companies have leveraged emerging technologies such as artificial intelligence, big data and blockchain to transform the global financial market at an unparalleled pace. The term ‘Fintech’, a blend of ‘financial’ and ‘technology’, has become a part of common vocabulary. Generally speaking, ‘Fintech’ refers to the application of technology in providing financial services. The Financial Stability Board (FSB) describes Fintech as ‘technologically enabled innovation in financial services that could result in new business models, applications, processes or products with an associated material effect on financial markets and institutions and the provision of financial services’.

The nature of modern economies, and their ideological dimensions. The cultural challenges of capitalist economies and their “socialist” alternatives.

This chapter provides a motivation for this book, outlining the interests of economists in artificial intelligence, describing who this book is aimed at, and laying out the structure of the book.