futureThroughout the last few years, innovation and the advancement of technology on a global scale has shot forward. The Voyager has travelled outside our solar system, the Curiosity has discovered evidence of microbiotic life on Mars and scientists have allegedly found a cure for HIV. What’s next for the world of science and technology, when the boundaries between what is invisibly microscopic and unreachably far are now closer than ever?

Researchers at MIT and the Santa Fe Institute have found that some widely used formulas for predicting how rapidly technology will advance — notably, Moore’s Law (which is that everything will improve over time) and Wright’s Law (that progress increases with experience) — offer superior approximations of the pace of technological progress. The new research is the first to directly compare the different approaches in a quantitative way, using an extensive database of past performance from many different industries.

The MIT report is published in the online open-access journal PLOS ONE. The findings could help industries to assess where to focus their research efforts to more accurately predict the economic impacts of policy changes. 

To carry out the analysis, the researchers amassed an extensive set of data on actual costs and production levels over time for 62 different industry sectors; these ranged from commodities such as aluminum, manganese and beer to more advanced products like computers, communications systems, solar cells, aircraft and cars.

“There are lots of proposals out there,” Jessika Trancik says in a MIT press release, for predicting the rate of advances in technologies. “But the data to test the hypotheses is hard to come by.” Knowing which models work best in forecasting technological change can be very important for business leaders and policymakers. “It could be useful in things like climate-change mitigation,” Trancik says, “where you want to know what you’ll get out of your investment.”

The rates of change vary greatly among different technologies, the team found. “Information technologies improve the fastest,” Trancik says, “but you also see the sustained exponential improvement in many energy technologies. Photovoltaics improve very quickly. … One of our main interests is in examining the data to gain insight into how we can accelerate the improvement of technology.”

Creative commons photo courtesy of Josh Hudnall