In this paper, we sketch a programme for AI-driven social theory. We begin by defining what we mean by artificial intelligence (AI) in this context. We then lay out our specification for how AI-based models can draw on the growing availability of digital data to help test the validity of different social theories based on their predictive power. In doing so, we use the work of Randall Collins and his state breakdown model to exemplify that, already today, AI-based models can (...) help synthesise knowledge from a variety of sources, reason about the world, and apply what is known across a wide range of problems in a systematic way. However, we also find that AI-driven social theory remains subject to a range of practical, technical, and epistemological limitations. Most critically, existing AI-systems lack three essential capabilities needed to advance social theory in ways that are cumulative, holistic, open-ended, and purposeful. These are (1) semanticisation, i.e., the ability to develop and operationalize verbal concepts to represent machine-manipulable knowledge; (2) transferability, i.e., the ability to transfer what has been learned in one context to another; and (3) generativity, i.e., the ability to independently create and improve on concepts and models. We argue that if the gaps identified here are addressed by further research, there is no reason why, in the future, the most advanced programme in social theory should not be led by AI-driven cumulative advances. (shrink)

Although the terminology of Big Data has so far gained little traction in economics, the availability of unprecedentedly rich datasets and the need for new approaches – both epistemological and computational – to deal with them is an emerging issue for the discipline. Using interviews conducted with a cross-section of economists, this paper examines perspectives on Big Data across the discipline, the new types of data being used by researchers on economic issues, and the range of responses to this opportunity (...) amongst economists. First, we outline the areas in which it is being used, including the prediction and ‘nowcasting’ of economic trends; mapping and predicting influence in the context of marketing; and acting as a cheaper or more accurate substitute for existing types of data such as censuses or labour market data. We then analyse the broader current and potential contributions of Big Data to economics, such as the ways in which econometric methodology is being used to shed light on questions beyond economics, how Big Data is improving or changing economic models, and the kinds of collaborations arising around Big Data between economists and other disciplines. (shrink)

These essays bring Weber's sociology to bear on the current transformation of the political landscape. After the collapse of communism, many states are faced with the challenges of democratization: they need to establish their legitimacy in an uncertain economic climate and within a new geopolitical order. The essays in this volume develop Weberian concepts and apply his comparative-historical method to deepen our understanding of these problems. They cover a wide range of examples, from the United Stated to Western and Eastern (...) Europe, and from Russia and Japan to the Islamic States. (shrink)

This paper draws on Collins’s conflict theory to understand the contemporary surge of populism. It puts forward an account centred on citizenship rights and the state, and on ‘my nation first’ politics in four countries: the US, Sweden, India and China. Collins has identified a capitalist crisis, the dynamics of geopolitical legitimacy, and state-penetrating bureaucracy as three central processes in modern societies. Especially the last of these focuses attention on the conflict between cosmopolitan elites and ‘the people’, construed in exclusionary (...) terms, which is on the rise in all of the four cases discussed here. The paper analyses the similarities and differences between them, and sketches the prospects for populist politics. (shrink)

Cognition, or scientific knowledge, is the fulcrum of Gellner’s philosophy of history. Science, for Gellner, is central to understanding the rise of the West and also to his defence of Enlightenment rationality against postmodernism and other forms of relativism. This way of thinking has recently been challenged, first, by global historians who locate the ‘great divergence’ in the 19th century rather than earlier, and second, by those who assign to the Enlightenment a pernicious role and argue that rationality and scientific (...) knowledge are inextricably bound to particular social contexts, for good or ill. Gellner’s ideas can be defended against these challenges, but this requires, first, distinguishing between rationality and science and, second, tracing the course of science and technology outside of the West. Once this defence is in place, Gellner’s ideas about the relation between cognition on one side and production and coercion can also be re-examined: here, too, his account requires revision since the idea that rationality ‘trumps’ the other two orders needs to be specified on the ground: in everyday life, for example, scientific knowledge is rather remote, and so often does not supersede other social dynamics. This also relates to other tensions in the relation between science, technology and everyday life: as Gellner noted, technology yields rubber as well as iron cages, but consumer technologies are now in some respects on a path towards unsustainable growth. Separating this problem from cognition is a further task. These refinements to Gellner’s ideas provide a basis for rethinking the connection he makes between liberalism and modern cognition. (shrink)

Richard Swedberg, Max Weber and the Idea of Economic Sociology. Princeton, NJ: Princeton University Press, 1998, x + 315 pp.