Objectives: Job creation, Import reduction, High productivity, Affordability
Requirements: Domestic supply chain, Skilled workforce, Tech upgrades, Education reforms.
In conventional economics, growth is driven by the following factors: innovation, workforce, production and sales. But with time, everything has to go through upgrades in order to be ready for the future.
Today, AI / Machine Learning has become the talk of the town in recent times. Tomorrow it will be nano technology, quantum computers.
Here, we have to define the roles of human beings, how much we can depend on machines and what we needs to be kept under control.
While we normalize induction of machines in everyday jobs, we have to prepare the workforce having advanced skill set.
The computers are excellent at work but we need to ensure they don’t take up tasks unless programmed to do so.
Machine Learning is capable to complete repetitive tasks i.e. serving at restaurant, loading a cargo, packaging etc.
AI works well with human skills such as creativity, deep thinking, emotional intelligence etc. We can bifurcate work at factories in three categories.
Task done by machines reviewed by humans
Tasks done by humans using machines
Task only done by humans only
AI is making a lot of errors in analysis, and it will continue this way indefinitely. Therefore, instead of getting the whole task, AI can do a portion of it more accurately on repeat.
AI will fill the gap to reduce production costs on low skill repetitive jobs that are frequent in production line. Some factories operate this way already, but it has to be more standardized at large scale.
This will reduce the dependency of US corporations for low-skill jobs. Machines do not take salaries, insurance, wellbeing covers so the overall production cost will come down.
It is important to note that AI will create more jobs in time to come. Necessary training for skill development will help to retain job in market with new designation.