👾 Econ 03 | The Future of Work: Applying AI to Production

In the last two articles, here and here, we have discussed how a ‘job’ is part of the wider economic question and how AI/Robotics will inevitably be applied across industry, simply because it’s going to be cheaper and more efficient. Let’s see if we can explore some concrete examples of how this might pan out. 

Like we’ve touched upon before, any economically meaningful activity can be considered a system, with inputs, processing and the output. For it to be meaningful, the output should be worth more than the costs - the input and the processing of it. In other words, the activity must create value, it must generate a profit, be profitable, sustainable.

We took the example of flour, baking and bread as the input, processing and output. This creates value because we find the bread worth eating as opposed to the flour. 

Let’s apply this to whole industries and trace how AI will transform the landscape. Let’s look at the food industry, food being a basic need. 

In agriculture, the inputs are the resources utilized to grow crops, such as seeds, fertilizers and so on. A huge cost however is of course labor. Even though industrial farming has huge amounts of automation, there still are significant labor costs. 

Now let’s look at what’s possible with AI (including Robotics). The entire workflow can be automated by AI/R. A group of robots that can do all of this end-to-end will have a high initial cost, but this is a capital cost, and not an on-going expense. Human labor by contrast is an on-going expense, you have to pay wages regularly. 

Of course there will be some on-going costs with AI/R, such as the electricity they use to operate, and maintenance and monitoring. However, over time, and especially as we find better ways of harnessing energy (a separate area where AI is likely to lead to significant breakthroughs), operating robots will be much cheaper. 

They can, like those ATMs we discussed last time, work 24/7 (perhaps with some downtime for maintenance), they don’t need to go on vacation, and I think we can be reasonably sure they won’t go on strike either!

However, AI-based automation is not going to be a linear process. It’s not a one-to-one equivalence between man and machine, that is, it’s not the case that a single robot will do the task of a single human and for comparable output. AI-based productivity will be higher, with the potential for exponential increase. 

As we discussed in the first article, a key factor here is innovation. AI does not allow us to just literally replace human labor, but AI-powered research is assisting us in making rapid advances in innovation. We will thus not only do the current tasks cheaply with machines, but actually find much better ways of doing them. 

And thus, AI could entail improvements not just in the ‘processing’ part of the production equation, but also in the ‘input’ part. We might find better ways of extracting raw materials we need. We might find, through improvements in processing via innovation, simpler cheaper substitutes to raw materials currently used. We might even do away with certain raw materials altogether. (There is in fact a thoroughly documented study on this already ongoing process, called dematerialization, which I’ll discuss in greater detail in another article.)

Manufacturing - of essential items like clothing (although it can be anything else similar) is another example. While there will be some cost for the raw materials needed, bringing down the cost of labor will have significant ramifications on the overall cost of production and thus price of goods. 

Within a largely free-market system (which is what we have in the developed economies, the industrialized countries), where prices tend to reflect the cost of production, the prices of such goods as food and clothing, in such a scenario, will fall drastically down from current levels. Will they go down to zero or near-zero as in the example of messaging? We might need to explore some more specifics and in depth, but for now let’s settle for a significant reduction in cost. 

We have so far only discussed goods. The other important aspect of the economy of course is services. We know from history that with advances such as industrialization and mechanization, the focus of human labor has shifted from the more physical (and mundane) tasks, such as manufacturing (the word ‘manu-facture’ literally means ‘hand-made’!) to services. 

One can say that this trend will only accelerate. However, there is one countervailing factor this time. Unlike the machines we’ve built in the past, with Generative AI we have, for the very first time in all history, a machine that can talk! A machine that can think!

So it’s not easy to tell how this may pan out. The more straightforward guess would be that AI would simply take over all cognitive tasks as well, and thus all jobs in the services sector. 

However, I propose that it is not as straightforward as that. There are at least a few reasons why, as we shall soon see.

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