An article published in Nature magazine in autumn 2017 makes for interesting reading. It reports on research carried out by Washington State University and Arizona State University, which shows that the wealth disparity in human societies was insignificant until the development of agriculture. That occurred in different parts of the world around 13,000 years ago. What happened next should be a warning to humans in the age of artificial intelligence (AI).
Land cultivation started when groups of nomads stayed in one location probably due to illness, injury, bad weather, or fear of other tribes. A few individuals experimented with seeds and plants and discovered that they could grow edible crops in dedicated plots and repeat the process each year. That reduced their need to constantly hunt, fish, and search for wild fruit and vegetables. Some grabbed more land than others and became the wealthiest of the group. The wealth gap increased even more, when some people learned how to tame large animals like oxen and horses and used them to till larger areas and, in the case of horses, more effectively fight adversaries and, so, acquire more land.
Having the latest and most powerful technology — in the broadest sense of the word — has always meant riches and power. The industrial revolution, which replaced much animal and human sweat with steam power, made the owners of the steam engines and factories very wealthy. Today’s technological equivalent of oxen, horses, and steam engines are computer systems and, just as in the days of the early humans, those who control that new technology are among the richest. Technology itself, however, may soon upend that age-old equivalence.
Many respected experts predict that the processing power of computers will surpass that of humans within the next few decades. Some of those experts, including Tesla and SpaceX CEO, Elon Musk, and the late theoretical physicist, Stephen Hawking, worry that artificial intelligence machines will eventually become conscious i.e. gain self-awareness, will be smarter than humans, and continue to get smarter quickly. These ultra-smart machines, the experts warn, will pose an existential threat to humanity because humans will not know what they’re thinking and so won’t be able to control them. Of course, nobody knows for sure that this will happen and, if it does, precisely when, but the expert warnings are credible enough to be taken seriously.
Scientists call the hypothetical moment in time when machines become conscious as the “singularity.” If that moment arrives, the experts suggest a number of possible scenarios. The most benign is that the machines will work for the benefit of their human creators and that there would be no reason for them to harm humans. Yet how could anyone be sure that that would be the case, since humans would not know what the machines are thinking? Even today, computer scientists don’t fully understand why complex computers make some of the decisions they make. Autonomous machines that can harm humans already exist. Drones without a human controller can be programmed to locate and attack targets. Some scientists argue that if machines become conscious, they are likely to regard humans as unnecessary and inefficient and eliminate them.
Elon Musk, among others, suggests that the only way to match these super-intelligent machines is to augment human intelligence by joining human brains to the machines. In that science-fiction scenario, the human race would become a race of cyborgs. Since cyborgs’ machine elements will doubtlessly evolve quicker than the biological elements, humans will gradually, but effectively turn into machines. That suggests that Elon Musk’s proposal is not really a solution at all and that the machines will eventually take over one way or another.
Thanks to AI, the rich will get richer until, ironically, humans lose control of the technology they invented. That’s unlikely to happen anytime soon, but it could happen sooner than most people think. When it does, for the first time in human history, being very wealthy will count for very little.