04 October 2012 by Laura Spinney
WHEN Admiral Zheng He led his fleet out of the eastern Chinese port of Suzhou in 1405, it must have been a sight to behold. The largest of the several hundred ships under his command were the size of modern aircraft carriers and housed 500 men apiece. The fleet made seven expeditions in all, to advertise the might of the Ming dynasty around the Indian Ocean, but having returned to port for the last time it was dismantled, vanishing along with the engineering know-how that created it. For the next few centuries China’s seagoing vessel of choice was a much humbler junk.
It seems incredible that such an impressive, and effective, body of knowledge could have disappeared like that, yet history is full of such examples. When archaeologists began excavating at Pompeii in the 18th century, they uncovered remains of a Roman aqueduct system that was more sophisticated than the one in use at the time. The Egyptian pyramids still haven’t given up all their construction secrets. And going even further back, finds at Howieson’s Poort Shelter in South Africa indicate that people were making highly sophisticated stone tools there until about 60,000 years ago when, for reasons unknown, they reverted to producing much simpler ones.
We tend to think of technological evolution as an exponential curve that starts out more-or-less flat in the early Stone Age and accelerates towards the present. But the idea that we are becoming ever more inventive may be an illusion. Looked at under the magnifying glass, the apparently smooth curve breaks up into a frenetic series of advances, retreats and new advances. In fact, over the whole of human history, we have probably lost more innovations than we now possess.
It is a sobering thought. Just when we were pinning our hopes on producing hi-tech fixes for today’s problems – climate change, overpopulation, emerging infectious diseases and so on – comes the news that we are not advancing inexorably towards technological Nirvana after all. Nevertheless, a better understanding of how technologies evolve could hold some valuable lessons for the future. In building a more fine-grained picture of human technological history, we may identify clues as to what will work and what will not.
One of the long-standing mysteries of human technological evolution is why our Stone Age ancestors apparently showed so little inventiveness in their toolmaking. The oldest tools discovered to date are 2.6 million-year-old stone flakes in what is now Ethiopia. They mark the beginning of a refining process that didn’t culminate in really effective stone hand axes until about 2 million years later. This slow progress, the flat part of the technological evolution curve, has been put down to the limited cognitive abilities of early hominins. Unable to learn from previous generations, each one had to start again from scratch, which explains why they lacked so-called cumulative culture.
Generally considered to be what separates humans from other primates, cumulative culture rests on two key skills: social learning, which is the transmission of knowledge to new members of a group, and over-imitation – the high-fidelity copying of a behaviour, including irrelevant or incidental elements, which allows the behaviour and its context to be passed along together. Some researchers have argued that cumulative culture only made its appearance around 100,000 years ago, with Homo sapiens (New Scientist, 24 March, p 34).
Throughout those apparently uneventful 2 million years, they were hunter-gatherers who lived in extended, itinerant family groups of between 20 and 40 adults, plus children. “These small groups could have been exposed to fairly high chances of the whole group going extinct,” whether because their best hunter was incapacitated due to illness or injury, or because environmental conditions changed rapidly. When a local population died out, all its innovations would have died with it, and sometimes that could have meant the loss of generations’ worth of know-how.
There is an intriguing parallel here with biological evolution. Back in 1983, University of Michigan palaeontologist Philip Gingerich studied how shape and structure changed over millions of years in a wide range of animals. He, too, found an inverse relationship between rate of change and period of measurement and, like Perreault, concluded that this is simply an illusion of perspective (Science, vol 222, p 159). The main difference between the two studies is that, by Perreault’s calculations, technological change happens approximately 50 times faster than morphological change.
As well as challenging preconceptions about the inventiveness of our Stone Age ancestors, these findings have also fuelled a growing realisation that technological innovations are highly prone to extinction. There are many reasons why even seemingly clever inventions don’t catch on, or die out. In the real world, a classic example can be found on the island of Tasmania. About 12,000 years ago, as temperatures and sea levels rose at the end of the last ice age, Tasmania was cut off from the Australian mainland and its inhabitants marooned. Archaeological evidence shows that until the land bridge was severed, Tasmanians possessed a range of complex technologies, including cold-weather clothing, fishing nets, spears and boomerangs. When Europeans arrived 10 millennia later, almost nothing remained. They found people whose technology was the simplest of any known contemporary human group.
Low population density and fragile networks for knowledge transfer were the main reasons for this loss. In other places and eras different influences have been at play. For example, market forces and political or social factors can dictate rates of innovation. A wealthy elite may be essential to sustain a community of craftspeople who need a long training period to learn to make the artefacts the elite desires. Patents, in the modern sense of the word, were invented in the 15th century, before which craftspeople found other ways to profit from their knowledge for as long as possible – ways that influenced the development of the technologies in question. Guilds emerged to protect skilled knowledge, for example, keeping the price high but the pool of knowledge transmitters small, and hence vulnerable to extinction if conditions changed.
Factors intrinsic to a technology may also determine its evolution. An example of this is found in Japanese katana or samurai swords, which remained unchanged for centuries because errors in forging the blades became too costly, discouraging experimentation. A technology may spread at the expense of better alternatives because once established it is too expensive to change tack. An example is the QWERTY keyboard, which is slower to type on than other keyboard layouts, but continues to monopolise the keyboard market in English speaking parts of the world.
Rumour and gossip can shape the trajectory of a technology too. In the past, using a new tool or medicinal herb might have got you branded as a witch, encouraging people to hide or suppress discoveries. Religious institutions still have a special kind of power: by attaching moral or spiritual value to an innovation, they can usher it in, by denouncing it they can prevent its spread.
So, what of the future? Are things different now, enabling technological evolution to continue at an ever-faster pace? Because of the sheer numbers of us on the planet, sparse populations and fragile transmission networks no longer pose a serious threat to innovation. Besides, since the invention of writing, we have been able to store knowledge outside people’s heads and disseminate it widely. But we may have unwittingly introduced other brakes on progress.
Technological progress – as measured by indicators such as the rate of scientific publication and patents filed – has indeed been accelerating exponentially over the past few centuries, but is now showing signs of slowing. The trouble is that we have accumulated so much knowledge, that young people now spend proportionately more time learning from previous generations and less time innovating. Schoolchildren and students tend to learn a subject in the order that it developed historically. For example, physics undergraduates are tested on their grasp of pre-1900 discoveries. “Only at master’s level do they start learning 20th-century stuff” . And that lag is having an impact.
Something else is happening too. As technologies become more complex, the associated contextual or causal knowledge is being lost. People who build cars today do not necessarily understand how a car works, for example, since they may just assemble one part or operate a robot that does it for them. In Fiji, where houses have to withstand hurricanes, anthropologist Robert Boyd of Arizona State University in Tempe has found that locals have a pretty good grasp of why certain materials are better at withstanding hurricanes, but not why certain structural designs work and others do not. “Causal understanding is a very powerful and beneficial thing,” “If you are put in a different situation, due to environmental change, say, you can adapt much more quickly if you understand how a technology works than if you have to adapt as a population by trial and error.”
It is not yet clear how much of a problem this is, since the information tends to be recorded and the body of people who do understand it, while relatively small, is probably still large enough to ensure preservation. One way we are overcoming the problem of that long learning period is through the collectivisation of science. What used to be a predominantly individual activity is now increasingly the occupation of groups who pool their knowledge. And there are potential benefits if it allows us to harness the power of the hive mind.
Protams, kolīdz piedzīvosim lielākus populāciju satricinājumus, līdz ar informācijas nesējiem ies bojā arī informācija. Jau šodien mēs pieredzam nepilnīgu informācijas nodošanu starp paaudzēm, kas izpaužas kā sociāla un intelektuāla polarizācija. Šī procesa atstāšana pašplūsmē nākotnē redz viena galēja stāvokļa iestāšanos – neatgriezeniska klimata maiņa vai resursu izbeigšanās noved pie masveida indivīdu bojāejas, un līdz ar tiem iet bojā arī uzkrātā informācija. Šādā gadījumā nepalīdzēs arī modernie informācijas uzkrājēji (datori un piederumi), jo ies bojā arī spēja nolasīt tajos uzkrāto.