Innovation Is Not Accelerating, Data Shows

Despite the pervasive belief that technological change is accelerating, economic data shows that innovation is not getting any faster. Productivity growth today stands at roughly its post-war average and is significantly slower than the period before 1970, according to the Bureau of Labor Statistics. An analysis by the Federal Reserve Bank also found that business dynamism is decreasing while average markups are increasing.

The gap between technological breakthroughs and measurable economic impact is not new. History shows it takes decades to move from a breakthrough to a measurable impact, because figuring out how to put a new idea to good use is much harder than people realize. Innovation is not a single event but a process of discovery, engineering and transformation, and the final stage takes the longest.

Consider electricity. In 1882, Thomas Edison opened the Pearl Street Station, the first commercial electrical distribution plant in the United States. By 1884 it was serving over 500 customers. Yet as economist Paul David explains, electricity did not have a measurable impact on the economy until the early 1920s, 40 years after Edison’s first plant was built. The problem was not electricity itself but a lack of complementary technologies. At first, the major application was electric light, which had a limited effect. To truly impact productivity, factories needed to be redesigned and work itself had to be reimagined. Later, household appliances like refrigerators and washing machines expanded electricity’s reach, and productivity soared for another 50 years.

The internal combustion engine followed a similar path. The automobile had limited economic impact in the age of the corner store. It was the development of the supermarket, and later the shopping mall and the category killer store, that made the new mode of transportation truly transformational.

Today, economists point to a second productivity paradox. The first lasted from the early 1970s to the mid-1990s, when increased investment in computer technology produced diminished productivity gains. Economist Robert Solow famously noted, «You can see the computer age everywhere but in the productivity statistics.» A paper by researchers at the University of Sheffield offers several explanations: productivity measures were largely developed for an industrial economy, not an information economy; the value of those investments represented only a small portion of total capital investment; and businesses were not necessarily investing to improve productivity but to survive in a more demanding marketplace.

In 1996, with the rise of the Internet, productivity growth began to boom again but then disappeared just as abruptly in 2004. Despite the hype surrounding Web 2.0, the mobile Internet and, most recently, artificial intelligence, productivity growth has remained sluggish for the last two decades. The most likely explanation is that the present and future are very much like the past. While advances in digital technology are astounding, the world is not digital. Most of the economy is still rooted in the homes we live in, the vehicles we ride in, the clothes we wear, the food we eat and the services that keep us healthy. All the gadgets and apps simply do not have that much impact.

Looking ahead, generative AI has been adopted faster than either the personal computer or the internet. Quantum computing promises to be exponentially more powerful than its digital predecessor for many applications. Synthetic biology technologies like CRISPR and mRNA could give us cures for diseases that have plagued humanity since the beginning of time. Yet here again, reality does not meet the hype. Despite all the enthusiasm about AI, there is very little indication that it is improving productivity, and there is even some evidence that «AI workslop» is damaging it. Quantum computing is still years away from proving it can be useful, and while CRISPR has genuinely produced miracle cures, they are still far too expensive to be practical.

Part of the problem is that when new technologies first emerge, we are not very good at using them. Technologies do not implement themselves. The transformation stage requires new skills, new business models and new ways of organizing work. Until those complementary changes take hold, the economic payoff remains distant. The pattern suggests that the current wave of innovation, however impressive, will follow the same slow path from laboratory to broad economic impact.

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Connor Quincy

Technology Reporter

Connor Quincy covers public affairs, politics, business, culture and daily news for Core Memo. The role focuses on verification, context, and clear explanations for readers.

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