The definitions of forecasting vary to a certain extent, but they all have the view into the future in common. The future is unknown, but the broad, general directions can be guessed at and reasonably dealt with. Foresight goes further than forecasting, including aspects of networking and the preparation of decisions concerning the future. This is one reason why, in the 1990s, when foresight focused attention on a national scale in many countries, the wording also changed from forecasting to foresight. Foresight not only looks into the future by using all instruments of futures research, but includes utilizing implementations for the present. What does a result of a futures study mean for the present? Foresight is not planning, but foresight results provide 'information' about the future and are therefore one step in the planning and preparation of decisions. In this paper, some of the differences are described in a straightforward manner and demonstrated in the light of the German foresight process 'Futur'.

Three key transitions leading to a “safe and just” operating space, with a focus on food systems, emerged during the development of a Foresight study promoted by SCAR (Standing Committee on Agricultural Research1): (a) sustainable and healthy diets for all; (b) full circularity in the use of resources; (c) diversity as a key component of stable systems. As consequence of COVID-19, food emerged again as a central element of life, along with health, after decades in which food security was taken for granted, at least in most developed countries. The COVID-19 outbreak offered the opportunity for a reflection on the importance of resilience in emergencies. Sustainable and healthy diets for all, was shown, during the pandemic, to depend much more on social and economic conditions than on technical aspects of food production and processing. Agriculture and the agro-industry have now a potential to absorb, at least temporarily, workers laid out in other sectors; the pandemic could be an opportunity to re-think and re-value labor relationships in the sector as well as local productions and supply chains. A full circularity in food systems also would benefit from stronger links established at the territorial level and increase the attention on the quality of the environment, leading to the adoption of benign practices, regenerating rather than impoverishing natural resources. Diversity is a key component of a resilient system, both in the biophysical sphere and in the social sphere: new business models, new knowledge-sharing networks, new markets. The three transitions would operate in synergy and contribute to the resilience of the whole food system and its preparation for a possible next emergency. Science can support policy making; however, science needs to be better embedded in society, to have a clear direction toward the grand challenges, to address the social, economic, behavioral spheres, to aim clearly at the common good. We need to re-think the conundrum between competition and cooperation in research, devising ways to boost the latter without sacrificing excellence. We need to improve the way knowledge is generated and shared and we need to ensure that information is accessible and unbiased by vested interests.

The article discusses quality criteria for futures research in the frame of so-called 'Futures Map'. This article is the edited and developed version of the article (Futura 1: 60-77, 2015). Based on the comments concerning (Futura 1: 60-77, 2015), we have developed the Futures Map frame and its validity criteria further. The new edition of the article is more focused on two basic questions. What is the relationship between the Futures Map approach and various scenario approaches? What are the common and different features of the quality criteria suggested in the Futures Map frame and other suggested quality criteria? The comparison is especially focused on the quality criteria defined by the German Netzwerk Zukunftsforschung. We suggest that it is reasonable to handle quality criteria on three basic levels: the philosophical basis; pragmatic general quality criteria; and special quality criteria suitable for specific contexts/uses. The prospects of futures research as a field of science depend first of all on their research methods. The article briefly discusses the choice of research methods as well as the evaluation of particular applications of methods in practical research projects.

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Foresight and Horizon Scanning are often regarded as identical concepts with identical models and purposes. But they can be completely different activities, both in and for any kind of prospective activity as well as for strategy purposes. Scanning is no debate and no strategy building. Whereas Foresight is more process‐oriented and always includes a Horizon Scanning phase, Horizon Scanning is rather found at the beginning of any forward‐looking activity and can be an automatized stand‐alone approach for identifying “things to come” ‐ which often means the identification of new science and technology and providing information about them. This paper wants to shed light on some of the confusions in Foresight and Horizon Scanning (HS) that often occur in organizations, among researchers and practitioners being thus of practical and scientific relevance for using an integrated model. The contribution is backed up by a study conducted for the European Commission (Cuhls et al., 2015) conducted to clarify for the Commission’s Foresight department (A6) how the strategic intelligence part of a foresight, the Horizon Scanning, is intertwined with the sense‐making part in similar projects in other parts of the world. The contribution thus starts with a broad definition of Foresight and of Horizon Scanning, explains findings from the study on objectives, methods used and relates the discussion to the EU standard “Foresight Cycle” derived from EFFLA. The conclusions are relevant for decision‐making and strategy processes in the European Commission, for national foresight processes but also for company's and other users.