Highlights:
The Sustainable Development Goals (SDGs) are 17 sets of goals with 169 targets to be achieved by 2030. As political aspirations, they aim at a future that is yet uncertain. In other words, this future is not deterministically given to us, but has yet to be socially constructed. Therefore, concrete policy tools are needed to deal with and shape this uncertain future. This report argues that the natural tool for doing so is to use foresight methods. Foresight involves bringing together key agents of change and sources of knowledge, to develop strategic visions and anticipatory intelligence (Miles et al., 2008: 11), to shape the future, and it is often executed through participatory consultations. Foresight not only provides approaches and methods about scanning issues that can be measured today (i.e. trends), but also informs policy-makers about future issues or wild cards that are not yet considered in policy design but must be tackled today if we are to develop our societies in a sustainable way. Foresight makes particularly sense in addressing sustainable development challenges. It is vital for any forward planning or policy activity to be able to meet future challenges proactively.
One of the main challenges of current foresight exercises is that we live in a period of technological change. Technological change is exponentially fast-paced, all-embracing, and global in nature. An important driver of this current phase of technological change is digitalization. The digitalization of the entire stockpile of technologically mediated information has taken less than 30 years, as less than one percent was in digital format in the mid-1980s (the rest in analogue format on paper, tape, vinyl, etc.), and more than 99 % in digital format today (extrapolated from (Hilbert & López, 2011)). The exponentially fast innovation cycles of digital technology create high uncertainty; its general purpose applicability embraces all sectors, and its inherent defiance of national borders intermingles the most diverse aspects of a heterogeneous world.
All of this leaves us with the aspiration to shape an extremely uncertain and fast paced future. This paper presents examples of how digital tools can help to implement future foresight (as means to help achieving the SDGs). Digital big data footprint can be used to detect empirical realities, artificial intelligence to extract insights from data, and computer simulations to explore future scenarios that are different from today's reality; to explore the world as we would like it to be; the world where the SDGs are the reality. The paper shows that these tools can be extremely useful to foster foresight studies in developing countries. They are cost-effective, scalable, and sensitive to local contexts. The paper explores various practical applications that use these computational tools in order to implement Sustainable Development Goals.
After the Introduction, Chapter 1 focuses on digital tools, namely big data and computer simulations, which can be used to enhance foresight exercises. It also reviews methods from the field of what is nowadays known as 'computational (social) science'. Chapter 2 presents concrete case studies that show the feasibility of using these computational methods in developing countries and for the implementation of the SDGs. Chapter 3 discusses the considerations that need to be taken into account when doing foresight exercises of a digital future. It places foresight efforts into the challenging context of our global reality, especially focusing on the particularities for implementing the 2030 Agenda for Sustainable Development in developing countries, and addresses a caveat about the role, scope, and limits of foresight exercises.
