Abstract: The world is changing at an increasingly rapid pace. In the span of only a few short years, we have witnessed technological progress, population growth, and globalization to a degree not seen in the lifetimes of our ancestors. Machines are also becoming smarter and more capable. As automation increases in domains where human labor and decision-making were once necessary, it will become increasingly difficult for individuals to create value and meaning through work. And, if one does find a niche, further changes may soon take place-new technology will acquire new skills, and people will continuously need to adapt. As a consequence of this growing dynamism, it is no longer sufficient to adapt to any one environment; humans and society must learn to adapt to change itself-they must increasingly learn to learn. In this paper, we begin with a brief account of how brains and minds work based on a theory broadly known as predictive processing (Friston, 2003; Clark, 2013). According to this view, humans come to understand and perceive the world by making predictions, a process that is therefore at the heart of understanding how humans deal with unpredictable circumstances. We then discuss research on how humans and machines respond in situations characterised by volatility, uncertainty, complexity, and ambiguity (VUCA), and the role of agency in social and moral situations. We conclude by arguing that learning-to-learn and meta-learning strategies are key capacities that currently distinguish humans from machines. For society to be generally adaptable to change, we propose that social structures and education systems will need to nurture skills that foster general and transferable learning capacities (rather than, or in addition to, specific skills). For humans to flourish in the future, governments are also encouraged to incentivize citizens who possess skills to become teachers and mentors. Society can be made robust when experts are inclined to teach those who are willing and able to learn. Ruben Laukkonen: ruben. This document, as well as any data and map included herein, are without prejudice to the status of or sovereignty over any territory, to the delimitation of international frontiers and boundaries and to the name of any territory, city or area. 2 │ Overview In this paper, we describe the challenges posed by VUCA: Volatility, Uncertainty, Complexity, and Ambiguity. We begin by providing a brief review of human behavior and decision making in VUCA situations. In doing so, we hope to illustrate how human minds and brains typically respond in unpredictable situations, and then based on this review, provide some recommendations about how to prepare for an increasingly dynamic world. We then compare human and machine abilities. The comparison to "intelligent" machines is valuable because it highlights the specific human capacities that are not easily replicated in computers. The challenge of building artificial intelligence (AI) also reveals important insights into the human skills and competencies that are likely to be important in the future. The distinguished fellow at the Institute for the Future, and best-selling author, Bob Johansen (2013), said that, "The ultimate dilemma is to take the VUCA world and change it from a threatening thing, which it certainly is, into a world that is not only threatening but also laden with opportunity." To this end, we provide actionable methods for individuals and society to become robust and adaptable to many future outcomes and possible opportunities.