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Sander Olson Interviews

Francis Heylighen


Question 1: Tell us about yourself. What is your background, and what projects are you currently working on?

My background is in mathematical physics, and I got my PhD in 1987 from the Free University of Brussels (VUB). I am presently a Research Professor and a co-director of the transdisciplinary research Center "Leo Apostel" at the VUB.

I have been working at the VUB since 1982 first on the foundations of physics (quantum mechanics and relativity theory). The focus of my research then turned to the evolution of complexity, which I study from a cybernetic viewpoint. I have worked in particular on the evolution of knowledge (including memes), and the creation of new concepts and models. More recently, I have extended the underlying principles to understand the evolution of society, and its implications for the future of humanity. The theoretical framework I am developing intends to integrate knowledge from different disciplines into an encompassing “world view.”

Together with my collaborator Johan Bollen, I have applied this framework by implementing a self-organizing knowledge web, that "learns" new concepts and associations from the way it is used, and "thinks" ahead of its users. As such, it forms a simple model for a future intelligent computer network, the “global brain.”

To study the technological and social implications of this vision, in 1996 I co-founded the “Global Brain Group,” an international discussion forum that groups most of the scientists who have worked on this issue. Since 1990, I am also an editor of the Principia Cybernetica Project, an international organization which attempts to consensually develop a cybernetic philosophical system, with the help of computer technologies for the communication and integration of knowledge.

At the moment, I am focusing on developing what I call “evolutionary cybernetics,” an encompassing theory of how intelligent, purposeful organization can originate and develop through the mechanism of blind variation and natural selection. One of the applications of this theory is the emergence and development of intelligence in the web. I am therefore further researching algorithms that would allow the web to self-organize so as to become more intelligent.

Question 2: Describe your concept of a Global Brain.

The "Global Brain" is a metaphor for the emerging collectively intelligent network formed by the people of this planet together with the computers, knowledge bases, and communication links that connect them together. This network is an immensely complex, self-organizing system that not only processes information, but increasingly can be seen to play the role of a brain: making decisions, solving problems, learning new connections and discovering new ideas. No individual, organization, or computer is in control of this system: its knowledge and intelligence are distributed over all its components. They emerge from the collective interactions between all the human and machine subsystems. Such a system may be able to tackle current and emerging global problems that have eluded more traditional approaches, but at the same time it will create new technological and social challenges which are still difficult to imagine.

Without doubt, the most important technological, economic, and social development of the past decade is the emergence of a global computer-based communication network. This network has been growing at an explosive rate, affecting -- directly or indirectly -- ever more aspects of the daily lives of the people on this planet. Amidst this growing complexity, we need to look ahead, and try to understand where all these changes are leading to.

A general trend is that the information network becomes ever more global, more encompassing, more tightly linked to the individuals and groups that use it, and more intelligent in the way it supports them. The web doesn't just passively provide information, it now also actively alerts and guides people to the best options for them personally. To support this, the web increasingly builds on the knowledge and intelligence of all its users and information providers collectively, thanks to technologies such as collaborative filtering, agents, and online markets. It appears as though the net is turning into a collective nervous system for humanity: a global brain.

Question 3: How does the concept of a Global Brain differ from conventional theories of Intelligence Amplification? How related are the two concepts?

I didn't know there were "conventional" theories of Intelligence Amplification! I just know that several people have proposed that concept to emphasize that computer technology should be used not so much to build independently intelligent programs (Artificial Intelligence, AI), but to develop support systems that would enhance our own human intelligence (Intelligence Amplification, IA), but these people never became part of the mainstream. Two pioneers that come to mind are Ross Ashby, one of the founders of cybernetics, whose contribution was mainly theoretical, and Doug Englebart, the computing pioneer who was the first to experiment with such basic interface elements as the mouse, windows and hypertext.

I believe both of these pioneers would basically agree with the way I envisage IA as supported by an intelligent web. The difference is rather one of emphasis: while "conventional" IA might imagine the amplification of individual intelligence by an individual computer system (e.g. a PC), I emphasize the amplification of individual and collective intelligence by means of a shared information network (the web). The power of the web is something that early pioneers would have found hard to imagine, although Englebart in his later work seems very much aware of it.

Question 4: How much longer do you believe that the Internet will continue growing? Can one truly claim that beyond a certain point the Internet will become sentient?

"Growth" is for me not the main issue. More and more people will use the net for longer and longer times, using ever-faster processors and communication links. Up to the point where every person and every appliance will be connected to the net full-time, I don't see anything that will stop this growth.

More important than quantitative growth is qualitative development: will the net be organized in a more intelligent way, so that it can e.g. autonomously learn, reorganize, make decisions, solve problems... If this deep qualitative reorganization takes off, then perhaps something like "sentience" will emerge, but this will be a very difficult process, fraught with technical, scientific, political, and social problems.

Question 5: Vernor Vinge argues that a group of PhDs with an Internet connected workstation could ace any intelligence test ever devised. Ray Kurzweil argues that as soon as computers reach parity with human intelligence they will necessarily soar past it. Which opinion do you think is more accurate?

I'd rather side with Vinge here. Kurzweil's view neglects the important lessons that have been learned from AI: to build real intelligence into a computer, you don't just need a powerful processor, you need a huge mass of common-sense knowledge and intuition, which you can only accumulate through a life-time of experience interacting with a truly complex environment (this requirement is sometimes called "situatedness" or "embodiment").

Such interaction requires very sophisticated sensors, effectors, and neural-type circuits connecting the two. These are extremely difficult to build into any artificial, robot-like creature, but are inexpensively available in any human being. It is much easier to tap into that human experience and augment it with computer memory and processing, than to build a computer intelligence from scrap. Even if such a computer with human-level intelligence would be built, there is no reason why its intelligence would grow faster than the intelligence of a synergetic system consisting of intelligent humans and intelligent computers intimately working together.

Question 6: What is your opinion of molecular nanotechnology? Do you believe that molecular assemblers will ever be feasible?

I don't know enough about nanotechnology to have firm opinions about it. In principle, I don't see any physical obstacles to building molecular assemblers, but the issue that seems to be neglected is control: how do you make an army of microscopic machines do precisely what you want? For simple machine-like functions, such as cogs and wheels, that may not seem too difficult. But then you don't gain such a great deal by building a microscopic lever. You'd rather have nanosystems that can tackle complex problems, like building living cells from scratch. But that will require either an unmanageably complex problem of programming the "software" to execute these tasks, or give the system a large measure of autonomy and self-organization. The latter seems most realistic to me, but the danger is that you lose control, and your nanodevice will not do exactly what you want.

Yet, I am not afraid of “grey goo” scenarios in which nanorobots run amok and destroy everything in their wake. I think we can get the best inspiration for what may happen from existing molecular devices, namely those developed by biological systems, such as enzymes and DNA. Biological self-organization is obviously quite efficient, but it has taken billions of years for evolution to get there, and organisms are still rather unreliable as machine-like “assemblers.” Now and then, something runs amok and a new killer virus appears (e.g., AIDS), but until now, this has never happened on a scale even remotely similar to the “grey goo scenario.” The best way forward to me seems that we should better understand biological self-organization, and support or augment it in a way similar to the way computers may augment human intelligence.

Question 7: What is your opinion of a technological singularity? If you think it is likely, when do you think it will happen?

The more I think about the singularity, the less I believe it is a realistic description of what will happen. It is true that most parameters of technological progress have been showing a spectacular acceleration over the past century, but this doesn't mean that the speed of progress will ever become infinite, as the mathematical definition of a singularity would imply. I have rather the feeling that we can already see the first signs of a deceleration.

The spectacular wave of innovation unleashed by the first user-friendly PCs in the 1980's and of the Web in the 1990's seems to have gotten drowned in complexity and confusion, as software developers are scrambling to keep their systems up-to-date with all the new standards, plugins and extensions, while merely adding esthetic improvements to the existing GUI-Web interface. While we constantly hear announcements of the most spectacular innovations, in practice most of these never reach maturity, because the developers underestimated the complexity of the task environment.

I believe we are confronted with a complexity bottleneck, which will significantly dampen the speed of further progress. The human mind simply is no longer able to cope with the information overload. This also means that all the big software projects that require a lot of coordination between different people and sources of information (e.g., the present "Semantic Web" efforts) either will get seriously delayed or end up with buggy products.

The only way to overcome this will be a shift to a radically different way of tackling problems, where the main burden is no longer on individuals or teams, but on the distributed, self-organizing, synergetic system that I call the global brain. This shift will require a lot of time and effort, and won't just happen instantaneously.

A better model of this transition is not the singularity (hyperbolic function into infinity) but a logistic curve (exponential growth which slows down until it is practically linear, and then slows down further, stabilizing at a new plateau). We are now probably somewhere in the middle, linear part of the curve. Seen from a distance (say with a million-year scale), a logistic curve may look like a step function, which implies a singularity or discontinuous jump between plateaus. In that sense, the singularity is not such a bad model, but in our present, year by year, time scale, the singularity view doesn't make much sense.

If you would ask me when the singularity would take place in the million-year view, then I would answer that we are right in the middle of it. But it may take another 50 years or so to come to an end, unlike a real singularity, which is by definition instantaneous.

Question 8: Speaking of the Singularity, how much longer do you believe that Moore's Law will continue? Do you think that we will ever have molecular electronics?

As you may have guessed by now, I'm not much preoccupied by Moore's Law. The real bottleneck will be organizational: how will we cope with the complexity involved in programming the powerful processors promised by Moore's Law to do more than number-crunching? I believe Moore's Law, or advances in processing speed more generally, will continue long enough to give us more than sufficient computing power for the tasks we would like to achieve.

Question 9: Do you believe that the barriers to machine intelligence are more hardware related or software related? Can we truly have either AI or IA without a software breakthrough?

As I already indicated, the real challenge will be software rather than hardware, and breakthroughs are necessary to achieve both AI and IA. I have no doubts that these are possible, and a lot of good theoretical ideas are floating around. The biggest problem is to integrate all of these into an elegant and encompassing system that would have the power to self-organize and adapt to the problems that are posed to it.

Question 10: What are your plans for the future?

As I said, my main focus now is the development of evolutionary cybernetics, a theoretical framework that would hopefully give us a solid foundation for the integration of all these promising ideas about self-organization, autonomy, distributed knowledge systems, etc. I plan to give lectures on this subject, write a textbook, and a number of papers. At the same time, I plan to test my algorithms for a learning and "thinking" web in a more realistic environment, to demonstrate their practical usefulness. I further want to continue developing and spreading the global brain vision together with my colleagues in the Global Brain Group, through lectures, conferences, publications and websites.


This interview was conducted by Sander Olson. The opinions expressed do not necessarily represent those of CRN.


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