Ever since I was a kid, I’ve been fascinated by the type of footage you see of silverside fish schooling near a coral reef and starlings forming these large murmurations in the sky. And what’s really remarkable, to me as a biologist, is how little we know about both how and why unrelated organisms like this coordinate these remarkable collective patterns. And yet collective behaviour is not only all around us – it’s within us. Our bodies, of course, are a collective of cells. At the Max Planck Institute for Ornithology, we really try to understand the principles of collective behaviour across scales of organisation in biological systems. In this chapter, I’m going to set out some of the latest research on collective animal migration: how organisms come together and integrate their minds to solve very complex problems during migration across the globe.

Dengue virus, the cause of tens of millions of cases of dengue annually, and Zika virus, the cause of recent explosive epidemics across Latin America associated with congenital defects and microcephaly, are pathogens with a significant burden on human health and well-being. Beyond their toll on health, these flaviviruses, as the genus is called, share a common evolutionary origin, have each adapted to replicate efficiently in the human host, and are spread by similar species of mosquitoes. These commonalities belie important clinical, epidemiological, and immunological differences between them that necessitate continued research into their respective biology. Moreover, these commonalities and differences have real consequences for control efforts in affected areas around the world.

Migration is in the news every day. Whether it be the plight of refugees fleeing Syria, or the outbreak of Zika virus across Latin America, the modern world is fundamentally shaped by movement across borders. This volume brings together eight leading scholars from the arts, humanities, and sciences to help tackle one of the most important topics of our time. What is migration? How has it changed the world? And what does it hold for the future? The present authors approach these questions from a variety of perspectives, including history, politics, epidemiology, and art.

Immigration is the subject that dominates politics in our time, most particularly in the liberal democratic Western countries of Europe, North America, and Australasia. While immigration has become an issue in many other nations – from Singapore looking to manage local attitudes to its large expatriate population, to Colombia facing an influx of desperate Venezuelans – in the liberal democracies it has provoked a backlash against outsiders as politicians as well as analysts of various stripes identify it as an existential question. Immigration for many is not just a source of unwelcome competition in the labour market or a problem for citizens struggling to gain access to over-subscribed public services from transport to health care. The threat it poses is not a financial one, or a matter of inconvenience, but an existential one.1 Immigration poses a threat to fundamental liberal, democratic (American, Australian, Canadian, British, or European) values. It is for this reason above all that immigration must be controlled: to protect those values; and, by doing so, for these countries to take (back) control of their destinies. To some extent, it is the fear of losing control more broadly speaking that drives the imperative to control immigration.

Algorithms are often disparaged, but they are also sometimes overrated. To understand their place in our world it is also important to understand their limits.

In the age of algorithms, new fears have arisen, including the fear that one day we will be overtaken, or even enslaved, by new beings, transhumans favored by natural selection, but also, more simply, by computers or algorithms more intelligent than us. This leads us to a question that computer scientists have been asking since the 1950s: Can an algorithm be intelligent? This question brings up two others. What does the adjective intelligent mean? Can we create an intelligent being?

Algorithms have become an essential component of our professional lives and social interactions, in health care, transportation, commerce, industry. Algorithms are transforming the natural sciences, social sciences, and the humanities, and in doing so, enrich our knowledge. They allow technology to continually push beyond the limits of the possible.

We used to believe that intelligence, like speech, culture, and self-awareness, made us unique. However, diluting intelligence across a variety of faculties contributes to blurring the boundary that separates man and machine. Man is better at speaking Japanese, but machines are better than man at playing chess. Perhaps one day machines will also be better at speaking Japanese. The difference between man and machine seems to be more a matter of degree than of nature, a distinction that enabled us to conceive of the idea of augmented man.

What could we still say was unique about us in the twentieth century?

Algorithms transform the relationship between human beings and nature, and in doing so, transform nature itself. This leads us to examine the relationship between the digital revolution and another transformative factor in our world today: the ecological transition.

The community is usually defined socially as a group of human beings whose life together is made possible by respecting a certain number of rules that define the rights and obligations of each of them. According to this definition, the members of the community are women and men. However, a gradual evolution of this concept has led us to consider that groups of human beings, for example, companies, and associations, can also have rights and obligations and, therefore, can also be considered members of the community.

In using the example of the professions of driver and translator, we implicitly assumed that drivers and translators would always exist. However, it is also possible that these professions may one day disappear if, at some point, algorithms for driving a car or translating a text perform as well as, or even better, than a human. This is also true for many other professions. Of course, this transition also paves the way for new professions to design, implement, and accompany all of these algorithms, but in the age of algorithms, much less work may be required to provide the same goods or services as before.

We have been using symbolic algorithms since the advent of writing, five thousand years ago. How is it then that this concept has suddenly become such a hot topic in the public sphere today? To explain this, we need to look into objects other than algorithms – computers and programs.

In 2002, during a performance/installation, 35 Hours of Work, Benjamin Sabatier sharpened pencils seven hours a day for five days. Sharpening pencils in this way for thirty-five hours is a deviant act, because custom dictates that we use a pencil sharpener for a few seconds, to sharpen a pencil, after which we put it away in a drawer until we need it again. As a consequence, a pencil sharpener is used only a few minutes per year.