From Nobel Laureates to Neural Networks: AI’s role in sustainable growth

Whilst the spotlight for this year’s Nobel Prize ceremony was placed upon whether Donald Trump would be crowned the “President of Peace”, Joel Mokyr, Philippe Aghion, and Peter Howitt were more quietly awarded the prize for Economic Sciences. Their research into long-term economic growth, particularly the role of innovation and the process of “creative destruction,” was praised for deepening our understanding of how economies evolve and prosper over time. 

In a crude attempt to summarise decades of economic expertise, the economists explored the historical roots of sustained growth, showing how the combination of “propositional knowledge” (scientific understanding) and “prescriptive knowledge” (practical know-how) laid the foundation for technological progress. It is argued that knowing how something works and confirming that it works can lead to much greater advances in technology than just knowing one or the other. 

This fusion enabled societies to move beyond centuries of stagnation into an era of continuous advancement, with each discovery opening the door to a newer, better and more competitive discovery. Aghion and Howitt contributed a formal theory of “creative destruction”, where new technologies replace old ones, driving growth but also disrupting existing industries. 

They go on to state that innovation often faces initial resistance, as new technologies threaten established firms and practices. However, when successfully adopted, these innovations can temporarily give pioneering companies a competitive edge, allowing them to lead their industries. 

Over time, as these technologies diffuse and evolve, the cycle of creative destruction continues, fuelling further progress. The laureates’ research underscores that sustained growth is a dynamic process, one that hinges on the constant interplay between knowledge creation, technological adoption, and the willingness to embrace change despite its challenges.

The points made above feel all too familiar when we look at the spectacular rise of Artificial Intelligence, a McKinsey report recently stated that AI stands not only as a powerful technology on its own, but as a “foundational amplifier of other trends”. 

This development takes the concept of combining “propositional” and “prescriptive” knowledge and launches it into the stratosphere. The way the internet democratised knowledge was a vast leap forward, but, except for a few highly trained and specific computer programmes, the combination of information was still limited by what a human brain could achieve. 

A stunning example is AlphaFold, which won the Nobel Prize in Chemistry last year and has revolutionised research into protein folding. It used to take a PhD researcher 4-5 years to unravel the secrets of one protein, and in 40 years, only 150,000 had been adequately documented. In one year, AlphaFold, using a neural network-based model, was able to document almost 200 million in one year correctly. This is something that would have taken one billion years to complete, according to Demis Hassabis, co-founder and CEO of Google DeepMind. 

As more industries learn to utilise this new technology best and apply its capabilities to their specific needs, our ability to process information and create solutions will rapidly increase. According to a Nobel Prize-winning model, this will also lead to economic growth. 

However, it is important to note that in the process of “creative destruction”, there are always losers. Each time a competitor gains an advantage, they acquire a much larger share of the profits in their industry, enjoying a temporary spot at the top. The rest either focus on getting back there or, in many cases, fail. 

As the speed of these developments and advantages grows, we risk creating an increasingly volatile market, making it harder for businesses to plan and more dangerous if they fall behind. The rapid growth and ability to capitalise on each new development also open the door for monopolies to form quickly as the timeline for R&D shifts from years to months to days. 

Therefore, it is essential to see both the opportunities and pitfalls that each new technology creates. Ensuring that our growth is sustainable, not just sustained, is important. The laureates remind us that if we ignore the risks, the engine of “creative destruction” may stall, and stagnation could return.