DOI
https://doi.org/10.1007/s12210-020-00972-0

Summary
The goals and targets included in the 2030 Agenda compiled by the United Nations want to stimulate action in areas of critical importance for humanity and the Earth. These goals and targets regard everyone on Earth from both the health and economic and social perspectives. Reaching these goals means to deal with Complex Systems. Therefore, Complexity Science is undoubtedly valuable. However, it needs to extend its scope and focus on some specific objectives. This article proposes a development of Complexity Science that will bring benefits for achieving the United Nations' aims. It presents a list of the features shared by all the Complex Systems involved in the 2030 Agenda. It shows the reasons why there are certain limitations in the prediction of Complex Systems’ behaviors. It highlights that such limitations raise ethical issues whenever new technologies interfere with the dynamics of Complex Systems, such as human beings and the environment. Finally, new methodological approaches and promising research lines to face Complexity Challenges included in the 2030 Agenda are put forward.

Relevance for Complex Systems Knowledge
The XXI century challenges are called Complexity Challenges because they regard Natural, Bioethical, Computational, and Descriptive Complexities. Complexity Science is urgent if we want to tackle the XXI century challenges. Complexity Science grounds on multi-disciplinarity; it requires inter-disciplinarity, and it targets trans-disciplinarity. Complex Systems' study shows that reductionism, which is a cornerstone of the scientific method, is not enough. A systemic approach is also required.
Furthermore, the experimental investigation of Complex Systems reveals that we cannot rely upon the reproducibility of the experiments. Most of the experiments involving Complex Systems are historical events. Complex Systems' investigation demands the collection, storage, and elaboration of massive data sets, i.e., the so-called Big Data. Therefore, it is compelling to contrive smart methods and tools to face the enormous volume and the fast stream of data, their variety (they might have many types of formats), variability, and their relationships. Computer simulations are alternative ways of performing experiments on Complex Systems. It is urgent to accelerate the rate of our computing machines and extend their memory space. New algorithms are inevitably needed to face the Complexity Challenges. There are two promising strategies to succeed. One is by improving the electronic computers, and the other is the interdisciplinary research line of Natural Computing.

Point of Strength
The features of the Complex Systems involved in the 2030 Agenda are presented. Complex Systems can be described as networks that are out-of-equilibrium in the thermodynamic sense and exhibit emergent properties. Furthermore, the scientific method finds insurmountable burdens in predicting Complex Systems' behavior, especially in the long term. The reasons of the unpredictability are explained.