No one can be certain whether AI will buck that historical trend or indeed reach or exceed human levels of comprehension.

Throughout history the compensation effect has consistently outweighed the displacement effect. This is because technological advancements have two contradictory effects: a substitution or displacement effect, where labour-saving technologies can displace workers, and an income or compensation effect, where technology makes all goods and services cheaper, raising real incomes and generating new sources of demand in other sectors of the economy. Yet Perkins points out that the ultimate impact of technology on labour markets is theoretically ambiguous. Much media commentary has harped on the scope for AI to cause unemployment to rocket - a fear that has been encouraged by AI enthusiasts talking about driving down labour costs. Data analytics firm GlobalData (which recently acquired TS Lombard) estimates the global AI market will be worth $383bn in 2030, a 21 per cent compound annual growth rate over 2022. The public facing version of ChatGPT reached 100mn users in just two months. Note, too, that this could all happen much faster than anything in the dotcom bubble. Meantime a number of studies have shown that Generative AI, which is capable of self-learning and performing several tasks, will boost the efficiency of workers and companies that use it. The resulting increase in the efficiency of the workforce should boost overall output.Īnd then AI can help workers invent new things, make new discoveries and generate technological progress that can raise future productivity. It is already helping workers make better informed decisions, optimise their processes and remove mundane tasks. First, AI can make current processes more efficient. AI has the potential to help take us beyond this world of asset price levitation and debt-dependent growth through its capacity to improve productivity.ĭario Perkins of TS Lombard suggests that two mechanisms will drive this improvement. In contrast, productivity growth among G7 countries has been sluggish, falling from 1.8 per cent per year between 19 to 0.8 per cent from 2000 to 2018. But then something unusual happened.Īround the year 2000, with timing that varied by country, net worth, asset values and debt began growing significantly faster than GDP. A new report from the McKinsey Global Institute points out that before the turn of the millennium, growth in global net worth largely tracked growth in gross domestic product. It is easy, now the monetary tightening cycle has been under way for some time, to forget just how artificial market conditions have been and for how long. In the case of Nvidia they have already made a considerable killing this year. Some people will profit greatly from the process. The simulation of human intelligence in machines has dramatic potential to change the way the economy works.

This year’s bounce, far from being driven by central banks, reflects something real. Applying a higher discount rate to distant future cash flows in the tech sector shrank the present value of those cash flows. The plunge in Big Tech stocks last year was substantially to do with central banks raising interest rates. There is much about this AI buzz in the markets that is healthy.

Rocket boom bubble machine