Overview
There were previously three new technologies that produced major disruptions in the world economy: the steam engine in 1712, electricity in 1882, and programable computers first developed in 1950. The large-scale adoption of computers began when they evolved from tubes to transistors and then to chips. Rapidly increasing processing power led the an escalation in the adoption of computers as they became smaller, faster, cheaper, and used less electricity. The next disruptive technology is AI that can mimic human thinking and learning, which will make people who learn how to use the technology more productive and boost global growth. This increase in human productivity is important as many world economies are slowly because their population growth is slowing causing worker shortages. Making the smaller labor supply more productive will help close the labor gap.
History of AI and Machine Learning
The concept of Artificial Intelligence was theorized in the 1950s by university mathematicians in the US and Britian and received government and private funding to promote commercialization. But successful AI programs were not developed until 2017. The acceleration of the technology occurred with the development of graphic processing units (GPUs) that can handle multiple tasks simultaneously compared to traditional central processing units (CPUs) that process sequentially. That computing power is not just doubling every two years like chips, it had been doubling every six months and last year accelerated with Nvidia’s 2024 processors that jumped by ten times over 2023. One of the reasons their computing power is these processors have become so powerful they are helping design the next generation of processors that are projected to reach the level of human intelligence by 2030. Mark Cuban calls this “The Automation of Automation”.
Besides computing power, the ability to access large amounts of data is a critical component of machine learning. The company OpenAI and their Chat GPT models have been trained on about 45 terabytes of text data from books and over 175 billion parameters. Parameters are variables that AI models adjust during training to improve their ability to make accurate predictions. Google is working on an AI system with over one trillion parameters.
Economic Uncertainty Created By AI and Machine Learning
While the technology is expected to eliminate some jobs and create others, there has been a worry that AI could displace more jobs than it will create and cause large scale unemployment, We at 4thREV believe the roll out will be more measured:
​1. AI and machine learning require vast amounts of electricity to run the server farms and iCloud systems necessary to store and process all the data on which machine learning is dependent and has been projected to increase electricity demand by 30% the next fifteen years beyond existing capacity. So, while the technology will be ready for many more applications in five years. The need for a much larger investment in electrical generation capacity will spread the deployment out over a longer period.
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2. This infrastructure necessary to generate the increase in electricity, support run more server farms and iCloud capacity necessary to support AL and ML will generate many jobs just like the invention of the automobile required the development of petroleum refining, greater oil production and a dealer network to sell and service the cars.
3. Demographic trends will also limit the ability of AI and ML to create high levels of unemployment . Declining birth rates below replacement are already becoming a major economic drag in Japan, South Korea and China and are moving to Europe and the US causing shortages of workers in many fields like engineering, medicine and teaching where AI and ML can assist professionals making them more productive and offset the shortage of professionals.
4. There will also be more, and better products and useful services developed with the help of AI and ML just that will expand the economy and create more job opportunities.
So, while there may be a need for fewer people to do things like computer programing and repetitive jobs, it is certain the rapidly changing economy will create many new jobs and a greater pace of technological change that will make lifelong learning a necessity..