An S-Shaped Adventure: Predictions -- 20 Years Later

Insights into accuracy of social scientists´forecasts of societal change., 2022

Abstract: How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments. Social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N=86 teams/359 forecasts), with an opportunity to update forecasts based on new data six months later (Tournament 2; N=120 teams/546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than simple statistical models (historical means, random walk, or linear regressions) or the aggregate forecasts of a sample from the general public (N=802). However, teams were more accurate if they had scientific expertise in a prediction domain, were interdisciplinary, used simpler models, and based predictions on prior data. One-Sentence Summary: When forecasting societal change, social scientists were no better than the general public or naïve statistical benchmarks.

Futures, 1974

This article originated as part of a larger study on the relevance to forecasting of values, attitudes and the notion of quality of life carried out for the project entitled STAFF (Social and Technological Alternatives for the Future). This study will be published in the Spring of 1975 as part of a volume concerned with philosophies and methodologies of futures research, under the editorship of Sol Encel and Pauline Marstrand.

Anthropological Measurements of Philosophical Research, 2024

This paper aims to explore social forecasting through the lens of a transdisciplinary approach with respect to holistic human nature. The complexity of social forecasting is that it deals with the multifaceted phenomenon of a human being, a human who is both the creator and the creation of the social spaces, for whom all economic, social, political, scientific, cultural achievements, problems and prospects acquire meaning only in the context of him/herself, his/her life, his/her destiny. Thus, the phenomenon of a human being is the key to understanding the dynamics of modern transformational processes and to creating promising models of the future development of the human society. Since in forecasting we try to anticipate the future that is not yet defined and may have different development trajectories, a transdisciplinary approach to forecasting that embraces what is within disciplines, at the intersection of disciplines, and beyond all disciplines can become the most fruitful approach. A human being brings a high degree of unpredictability and uncertainty into all social forecasts. Nowadays, the complex multifaceted nature of an individual as a biological, psychological, and social being needs a deeper understanding that requires joint efforts of representatives of various scientific fields. Through mutually enriching work within a transdisciplinary paradigm, representatives of different scientific fields and directions may create a kind of guidebook designed to form and explain a new reality, a new future. Within such an approach, not a competition between theories, methodologies, and protocol decisions, but a common goal, common dreams and aspirations for a better future of humanity should come to the fore. A transdisciplinary approach to social forecasting has a potential to consider all sciences in a humanitarian context, taking into account complex multifaceted human nature. It goes beyond traditional boundaries providing opportunities not only to synthesize and integrate solutions to a problem, but also to rise above it. Transdisciplinarity, recognizing the existence of different realities, provides a broader view of the world, a deeper understanding of phenomena and processes that contribute to the development of new projects for a better future of a human and humanity.

Futures, 2006

This article attempts to answer the question, whether and how it is possible to make scientific forecasts in social sciences through the investigation of the actual scientific-philosophical problems and methodological aspects of futures studies. 1 Following a critical analysis it describes the scientificphilosophical features of uncovering and forecasting the possible futures from the classic predictions to the latest approaches. In the methodological chapter it turns its attention to the impossibility of making scientific predictions and demonstrates the methods with the help of which-reacting to the challenges of uncertainty, instability and various changes-futures studies can perform its original function, i.e. supports present decisions providing information about the future. q

nature human Behaviour, 2023

How well can social scientists predict societal change, and what processes underlie their predictions? To answer these questions, we ran two forecasting tournaments testing the accuracy of predictions of societal change in domains commonly studied in the social sciences: ideological preferences, political polarization, life satisfaction, sentiment on social media, and gender–career and racial bias. After we provided them with historical trend data on the relevant domain, social scientists submitted pre-registered monthly forecasts for a year (Tournament 1; N = 86 teams and 359 forecasts), with an opportunity to update forecasts on the basis of new data six months later (Tournament 2; N = 120 teams and 546 forecasts). Benchmarking forecasting accuracy revealed that social scientists’ forecasts were on average no more accurate than those of simple statistical models (historical means, random walks or linear regressions) or the aggregate forecasts of a sample from the general public (N = 802). However, scientists were more accurate if they had scientifc expertise in a prediction domain, were interdisciplinary, used simpler models and based predictions on prior data.

From the perspective of traditional philosophies of science, economic forecasts may be perceived as the results of purely rational reasoning, applying scientific theories, and econometric modeling. Yet, a sociological view on economic forecasting shows that economic forecasts mobilize more than these conventional epistemic resources. First, economic forecasters are embedded in a huge interaction network including different kinds of economists, policy makers, and representatives of the economy. In the epistemic process of economic forecasting, this network actively helps improve the forecasts in (at least) three ways: it helps forecasters to produce new imaginaries of the economic future and to discover emerging developments, it increases the forecasts' social legitimacy, and it produces a common view on the economic future that helps to decrease uncertainty in markets. Second, economic forecasters mobilize emotions that help them to overcome the shortcomings of quantitative data, statistics, and econometric modeling: they develop a feeling for numbers-and numbers support them in developing a feeling for the economy-they have to control their emotions to keep cool when the economy or politics confronts them with increasing dynamics, and they are impassioned about their work. Drawing on data gathered in numerous economic forecasting institutes in Germany, Austria, and Switzerland, I argue that the main resources in producing credible and accurate economic forecasts consist of various forms of social interaction and the mobilization of emotion.

2018

From parole prediction instruments and violent sexual predator scores to racial profiling on the highways, instruments to predict future dangerousness, drug-courier profiles, and IRS computer algorithms to detect tax evaders, the rise of actuarial methods in the field of crime and punishment presents a number of challenging issues at the intersection of economic theory, sociology, history, race studies, criminology, social theory, and law. The three review essays of Against Prediction by Ariela Gross, Yoram Margalioth, and Yoav Sapir, raise these challenges in their very best light. Ranging from the heights of poststructuralist and critical race theory to the intricate details of mathematical economics and criminological analysis, the essays apply different disciplinary lenses to the analysis of the actuarial turn offered in Against Prediction and set forth both substantive and structural challenges to the book. By means of a detailed reply to the three reviews, this essay provides ...

Journal of Critical Realism, 2006

Despite inroads made by critical realism against the 'scientific method' in social science, the latter remains strong in subject-areas like human resource management. One argument for the alleged superiority of the scientific method (i.e. its scientificity) lies in the taken-for-granted belief that it alone can formulate empirically testable predictions. Many of those who employ the scientific method are, however, confused about the way they understand and practice prediction. This paper takes as a case study empirical research on the alleged empirical association between human resource management practices and organisational performance. By unpacking the confusion surrounding the two basic notions of prediction used, it reveals what is wrong with them, why the scientific method cannot actually make accurate predictions and why, therefore, the scientific method fails to meet its own criteria for scientificity. Finally, explanation is considered in order to prevent any confusion between it and prediction and to offer what we call tendential prediction. 8 In a recent survey of 467 articles on HRM, Hoobler and Brown Johnston, not only found just one article on meta-theory, they also found that 'statistical regression was by far the method of choice, represented in a full 35 percent of the articles studied. Various analysis of variance and meta-analysis accounted for 9 percent and 5 percent

2019

I survey and discuss obstacles to forecasting the future, especially to making accurate predictions, in various areas: in economics with its inadequate models and financial crashes, big business ventures with their cost overruns, the role of novelties, affective forecasting, and ecology. Given the great diversity of these areas, the kind of obstacles are equally diverse. Altogether, I conclude, they should certainly not prevent us from planning for the future as best as we can, if not by means of accurate predictions, then e.g. by means of qualitative estimates and prognoses, or by working out alternative scenarios. Zeiten der Krise sind Zeiten der Kritik