The Economy Of Data

The tech bros have over the past year or so made one message very clear. AI will replace most of our jobs in the very near future. Top of the chopping board in this messaging has been the replacement of computing and engineering jobs that just a few years ago were the crown jewel of the career ladder. Everyone wanted to learn how to code, be a data scientist, develop machine learning models and build drones. We are now told, these skills will not be important anymore and that we should all sit pretty and wait for policies that will give us universal basic incomes.

The bros have stood firm to their words with a show of massive lay offs across departments and regions, citing the efficiency of AI systems even when their revenue reporting has clearly grown due to human influence and input. Most of the companies doing the firing have a big hand in the development of AI systems and have somehow found it convenient to fire the very people that made the systems possible that they are now advertising to the rest of the world.

So, what is really happening?

Most of the companies in silicon valley play an interesting game. Hire excessively to starve the ecosystem’s potential competition and fire at will depending on the market breath cycles. It is no secret that these companies have a core team that run their systems while thousands of others, no matter the qualification, are simply seat fillers for a show of might depending on what the market wants to see. 

In a recent Remote Labor Index, where AI systems were given real life projects from remote work, the human task takers performed 96% better than the AI systems on all tasks. This should tell us something. While AI systems can automate tasks and their completion, humans are able to exercise judgement and nuance which are often required  for the execution of these kinds of tasks.

Vibe coding is a great example of “We are all engineers now”. While the systems can quickly spin off websites and systems within hours in tasks that would have otherwise taken weeks or months to produce, there still exists a gap in what a computationally technical mind can produce and what a non computationally technical person can produce. Yes, these systems have democratized computing but no, they have not made the computing world flat.  

So, what will happen?

In an age where the tech companies are spitting out their tech talent, we still see them hiring for more engineers, this is all while telling the rest of the world that they do not need software engineers or computer scientists. This simply says one thing, the world as we know it today still needs engineers but we need very good engineers.

When you drive around major cities now, the greatest shift has been on the billboards. Companies are opting for AI models, school book covers have AI generated images and this is becoming our new reality. The artists need to be wary of this.

Even with this shift, more companies will be created, because the opportunities still exist. If anyone was wondering where this post is leaning, this is a rallying call to produce more scientists and more engineers! Studying the scientific fields teaches critical thinking and problem solving in a way that is unmatched. AI remains a technology solution and not an end in itself. Having more scientists opens up opportunities for more discoveries, more innovation and who knows, more inventions in the AI space.