Neural and Social Networks: An Interview with Manuel Castells

Manuel Castells

BI: For the last 25 years you have thinking about the network society and about horizontal versus vertical ways to conceive of society. Could you recap what led you to those thoughts originally and what has changed since you wrote those original ideas?

MC: First of all, rather than a thinker, what I am is an empirical sociologist. When I arrived at Berkeley in 1979 it struck me that we were clearly in the midst of a major technological revolution: scientific, technological, and industrial. This revolution seemed to me similar to what happened in the English Midlands in the mid-19th century, or what happened in Berlin at the end of the 19th century with the chemical-electrical revolution. So, my instinct then, after I had finished a major book on urban social movements, was to ask as a researcher “what’s next”?

What was next happened to be in front of me. What I decided was to work on two things. First, I decided I should try to grasp the key transformations that were happening not just technologically but in terms of the social, political, and organizational dimensions of networking. Second, my work was global from the very beginning. Even while working in Silicon Valley on the transformations going on there, I also did extensive field work in Japan, in China (at a moment when China was very difficult to penetrate), in Latin America, back in Europe, and in the Soviet Union. If you don’t do global work, implicitly you propose the notion that the technological transformation is something one-dimensional that always produces the same effects. But what I have observed is that technology changes completely in different contexts. The culture, the institutions, the history, the geography of every place transform the interaction between technology and culture.


BI: It is hard for many of us today to imagine what life was like before the rise of the network society. Life was constrained by physical space, with people living together in a community that was bigger than the individual. The shift was to the emergence of a network that is not bound to place, but revolves around individual lives. Can you briefly elaborate on that?

MC: The most famous distinction in sociology was Ferdinand Toennies’s Gemeinschaft and Geselschaft [community and society]. The idea was that, at first, we were all in closed communities and modernization meant that we would grow into a much broader society, lose associations, etc. Today, the myth of the integrated communities has been debunked.

But what is perceptive about what you say is that the debate is about whether we can find a balance between the tight community, securing but repressing and controlling at the same time, and then the opening up of relationships in which the individual is able to be individual and yet still socialize. The cultural-technological revolution rather than theory is what gave us the answer: networks. Individuals exist socially, not isolated, on the basis of networks. The transformation of communications technology has changed everything because we are at the same time together and distinct, autonomous and able to cooperate in projects. Therefore, a new kind of sociality has emerged, and ultimately a new kind of politics as well.

BI: Reading your MIT piece on the me-centered society, it occurred to me that if the last election revealed anything, it is that the political institutions we have and the way we institutionalize elections is absolutely inadequate to the forms of communication and self-organization that we have right now.

MC: That’s the subject of my last book, which I just published. It’s called Rupture: The Crisis of Liberal Democracy (being translated by Polity Press). It takes the crisis of legitimacy, and the role of communication, going case study by case study: Trump, Brexit, Macron, different countries.

BI: If you think back to Habermas and the emergence of the public sphere, we see the historic importance of newspapers for the idea that there is a shared reality. How can one reconstitute a public that revolves around knowledge, rather than intensity? Or is this even desirable?

MC: Habermas is all about the public sphere built around political institutions, with the Constitution being the centerpiece of all that. This requires deliberation in society, direct deliberation by citizens, consensus, etc. (Although, he always added he was talking about Western Europe and mainly Germany.) Where is the public sphere today? There has been a shift from the institutional public sphere to the communication network public sphere, which—by the way—is global, local, national, everything, because it is about the networks, and that is the fundamental transformation.

BI: This raises a series of complicated questions. One way to think about the etiology of say, the fake news crisis, for example, is that as we have created all of these networked interactions and what didn’t come along with that was the sense of social trust which we obtained when everyone was reading the same newspaper or watching the same TV station. The rise of network society has occurred in parallel with the collapse of centralized authorities capable of establishing shared truths. How much of that relationship is a happenstance—or is it an inevitable effect of these networked arrangements?

MC: We are already there. One of the things that we should do as researchers and thinkers is to think about the reality that has been transformed, not about what should be. What I think is happening, first of all, is that there is a massive panic in the institutions at large, that, “Dammit, we don’t control information and communication anymore, and this has been the source of power throughout history.”

Second, the notion that people only refer to their own source of information and opinion is the most stable research finding in all communications research. People don’t read or watch to inform themselves but to confirm themselves.As to fake news, that also presupposes that traditional media is all the same, all that they publish is true. Political manipulation through twisted or fabricated information is as old as humankind. What has changed is that instead of having centralized blocks controlled by either corporations or governments, now everyone has their own silo.

BI: This is a good characterization of the information situation in Western democracies. But there is a very different situation emerging in China. In China we see a highly networked society that is not the anarchistic, cacophony we see in the West, but which instead takes the form of the greatest engine of informational control ever invented. So, we have both of these situations at the same time, a real-time historical experiment.

MC: First and most important: most of the discussion in the West about China and the Internet presupposes that all the Chinese people are ready to rebel and are all on the Internet plotting against the government. No! In the world at large less than 18% of Internet interaction, this is a global survey, refers to any political or ideological matter.

So yes, the Chinese system heavily represses certain people—my  friends, let’s say—the few thousand, or even tens of thousands of people (out of a 1.3 billion people society) who dare to challenge this mammoth. But this does not represent the kind of massive repression in China that it would in the U.S., because of the difference of culture and politics.

BI: How is the arrival of AI going to accelerate and change the dynamics we have been talking about?

MC: What I see here is fast learning and fast autonomously thinking machines radically transforming some fundamental activities of human life. To start with, it is transforming the most important human activity throughout history—which has been to kill each other: War. War is what changes cultures, civilizations, moves things up and down, destroys lives, creates grief, creates myths, creates legends, everything.

Drones are extremely important. The people at RAND say our wars now will be fought between drones and grassroots networks, basically. We already have briefcase-sized drones, with tremendous fire power, tremendous autonomy, tremendous capacity in terms of surveillance, information, and decision making over what to shoot or not. In that sense, we have dehumanized the wars.

The other major technological transformation is finally the technological intervention on ourselves—meaning the human body and, therefore, brain.

BI: The Berggruen Institute has been involved in organizing several workshops around AI and the human. One of the most striking observations is the distinction between what concerns people articulate. You can’t help observing that all those who are worried about super-intelligence are AI engineers or entrepreneurs, and those in the social science fields are much more concerned with social disruption, mass unemployment, etc.

This is extremely interesting because for social scientists the machines we make are human made machines which they gain meaning in a human world. Hence, the very basic language of the social sciences applied. For the AI engineers that’s all wrong. The machines have a life of their own. They cannot be understood in the social language and there is a profound epistemic rupture that they feel from their perspective the social scientists don’t get at all. What do you think about this distinction or whether the social science language is sufficient to actually understand and describe artificial intelligence?

MC: For me the most direct practical consequence is that institutions such as the Berggruen Institute should be doing a lot of actual research on these matters. Once again, the good thing about science in the broader sense is we can have all the ideas, all the discussions, but ultimately, we should be able to produce knowledge about new things that are happening.

What is really new about the current wave of technological transformation? What is an epistemological rupture, vis-a-vis what I observed in the 1990s? One thing is similar: networks. Networks have really continued to expand. But what is entirely new, the most serious thing that is happening, is that the more we accelerate our technological development, the less capacity we have to understand it and control it.

This is in excerpt from a conversation between Professor Manuel Castells and Berggruen Institute Vice President of Programs, Nils Gilman, with Berggruen Institute Director, Tobias Rees. Click here to read the full transcript.

composed by Arswain
machine learning consultation by Anna Tskhovrebov
commissioned by the Berggruen Institute
premiered at the Bradbury Building
downtown Los Angeles
april 22, 2022

Human perception of what sounds “beautiful” is necessarily biased and exclusive. If we are to truly expand our hearing apparatus, and thus our notion of beauty, we must not only shed preconceived sonic associations but also invite creative participation from beings non-human and non-living. We must also begin to cede creative control away from ourselves and toward such beings by encouraging them to exercise their own standards of beauty and collaborate with each other.

Movement I: Alarm Call
‘Alarm Call’ is a long-form composition and sound collage that juxtaposes, combines, and manipulates alarm calls from various human, non-human, and non-living beings. Evolutionary biologists understand the alarm call to be an altruistic behavior between species, who, by warning others of danger, place themselves by instinct in a broader system of belonging. The piece poses the question: how might we hear better to broaden and enhance our sense of belonging in the universe? Might we behave more altruistically if we better heed the calls of – and call out to – non-human beings?

Using granular synthesis, biofeedback, and algorithmic modulation, I fold the human alarm call – the siren – into non-human alarm calls, generating novel “inter-being” sonic collaborations with increasing sophistication and complexity. 

Movement II: A.I.-Truism
A synthesizer piece co-written with an AI in the style of Vangelis’s Blade Runner score, to pay homage to the space of the Bradbury Building.

Movement III: Alarmism
A machine learning model “learns” A.I.Truism and recreates Alarm Call, generating an original fusion of the two.

Movement IV: A.I. Call
A machine learning model “learns” Alarm Call and recreates A.I.Truism, generating an original fusion of the two.