John Brockman - What Should We Be Worried About?

By building and then immersing ourselves in a succession of designer environments, such as the human-built worlds of education, structured play, art, and science, we restructure and rebuild our own minds. These designer environments are purpose-built for creatures like us, and they “know” us as well as we know them. As a species, we refine them again and again, generation by generation. It is this iterative restructuring and not sheer processing power, memory, mobility, or even the learning algorithms themselves that is the final (but crucial) ingredient in the mental mixture.

To round it all off, if recent arguments by Oxford psychologist Cecilia Heyes are correct, many of our capacities for cultural learning are themselves cultural innovations, acquired by social interactions rather than flowing directly from biological adaptations. In other words, culture itself may be responsible for many of the mechanisms that give the cultural snowball the means and momentum to deliver minds like ours.

Why does this mean that we should not fear the emergence of superintelligent AI anytime soon? The reason is that only a well-structured route through the huge mass of available data will enable even the best learning algorithm (embodied perhaps in multiple, active, information-seeking agents) to acquire anything resembling a real understanding of the world—the kind of understanding needed even to generate the goal of dominating humankind. Such a route would need to be specifically tailored to the initial biases, drives, and action capacities of the machines themselves. If the slow coevolution of body, brain, biases, and an ever-changing cascade of well-matched cultural practices is indeed the key to advanced cognitive success, we need not fear the march of the machines. For the moment, there is simply nothing in the world of the AIs that looks set to provide that kind of enabling ladder.

“Deep Learning” algorithms are now showing us how to use artificial neural networks in ways that come closer than ever before to delivering learning on a grand scale. But we probably need “deep culture” as well as deep learning if we are ever to press genuine hyperintelligence from the large databases that drive our best probabilistic learning machines.

That means staged sequences of cultural practices, delicately keyed to the machines’ own capacities to act and communicate and tuned to the initial biases and eco-niche characteristic of the machines themselves. Such tricks ratchet up human understanding in ways that artificial systems have yet to even begin to emulate.

DAVID DALRYMPLE

Grantee, Thiel Foundation, Nemaload; Program in Biophysics, Harvard University; research affiliate, Synthetic Neurobiology group, MIT Media Lab

When the value of human labor is decimated by advances in robotics and artificial intelligence, serious restructuring will be needed in our economic, legal, political, social, and cultural institutions. Such changes are being planned for by approximately nobody. This is rather worrisome.

If every conceivable human job can be done better by a special-purpose machine, it won’t make any sense for people to have jobs with corporations to earn wages they exchange for goods and services. This isn’t the first time an entire paradigm of civilization has become obsolete; the corporation itself is only 500 years old. Before that, a “job” meant a single project; craftsmen and merchants traveled from city to city, as businesses unto themselves.

The corporation is useful because it can bring hundreds, thousands, or even millions of people together, working toward a common purpose with central planning. Countries are useful for similar reasons but at a larger scale and with the added complexity associated with enforcement (of laws, borders, and “the national interest”). But as technology advances, the context that gives power to those sorts of institutions will shift dramatically. As communication becomes cheaper, higher-speed, and more transparent, central planning becomes a less appropriate tool for bringing people together. One of the most centrally-planned organizations in history, the Soviet Union, was brought down by the fax machine, which enabled citizens to bypass the state-run media. The corporation system is much more adaptable, but we’re already seeing it struggle with the likes of “hacktivist” group Anonymous.

More important, future technologies will be used to bring people together in new, fluid structures with unprecedented productivity. New sorts of entities are emerging that are neither countries nor corporations, and in the not-too-distant future such agents will become less “fringe,” ultimately dominating both industry and geopolitics.

Individual humans will eventually fade even from the social world. When you can literally wire your brain to others, who’s to say where you stop and they begin? When you can transfer your mind to artificial embodiments and copy it as a digital file, which one is you? We’ll need a new language, a new conceptual vocabulary of everything from democracy to property to consciousness, to make sense of such a world.

One possible way to begin developing such ideas is reflected in my title. It’s a bit of wordplay, referring to three disparate intellectual movements: transhumanism, which predicts the emergence of technologically enhanced “posthumans”; human geography, which studies humans’ relations with one another and the spaces they inhabit; and posthumanism, a school of criticism revisiting the usual assumption that individuals exist. These fields have much to learn from each other, and combining them would be a good start to addressing these issues.

For example, transhumanist stories about the future (like most stories) feature individuals as characters. They may be able to communicate ideas to one another “telepathically,” in addition to other new capabilities, like being able to move one’s mind from one embodiment to another (thus avoiding most causes of death). But they are still recognizable as people. However, with high-bandwidth brain interfaces, as posthumanist critics tell us, that might not be the case.

Human geography tends to ignore technological trends unless they’re incremental—or at least easily described in terms of existing concepts. Transhumanist technologies would dramatically change the geographic picture (as a simple example, solar-powered humans wouldn’t need agriculture). These geographic changes, in turn, would have significant consequences for the trajectory of transhumanist technology and society.

Posthumanism is highly abstract. Perhaps predictably, thinkers interested in questions like “Do individuals exist?” or “What is the meaning of identity?” tend to be uninterested in questions like “In light of this, how will equity markets need to evolve?” They also tend to be generally suspicious of technology, often citing the distorting influence of the mass media. If they’re aware of transhumanism at all, they criticize it for its individualism and then move on, rather than looking deeper and seeing the possibility of totally new types of identity structures with these future capabilities. Finally, although posthumanists do talk about economies and societies, it’s usually without reference to real-life data or even historical examples.

Personally, I have little doubt that the next paradigm of civilization will be a change for the better. I’m not worried about that. But the transition from here to there might be painful if we don’t develop some idea of what we’re getting into and how it might be managed.

ED REGIS

Science writer; coauthor (with George Church), Regenesis: How Synthetic Biology Will Reinvent Nature and Ourselves