Artificial intelligence (AI) will create more opportunities, similar to what happened more than a century ago, when tractors moved into farms, displacing some farm workers, but making farming a better business. As those farms became mechanized, the number of people employed in agriculture dropped, but farm outputs and productivity accelerated. The old Rev Malthusian postulation that man (and woman) would run out of food due to food production accelerating in arithmetic progression in a world growing in population geometrically, was evidently punted for good.
Today, in the European Union, less than 5% of the working population are employed in agriculture, and yet, they produce enough to eat and export. In Africa, we hover in the excess of 65%, producing poverty where farmers need help with food!
The AI race is opening another phase of that massive labour translation where most people in some of the things we do would be displaced and dislocated. The invention of AI and the new species of AI systems we’re experiencing will have consequential impacts in the natures and forms of work.
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As ChatGPT blasts its scientific magics, Google is putting Mind into Brain: “Google Brain and DeepMind—the company’s two main AI units, which have long operated separately—would work together more closely on efforts to build large algorithms. ‘I expect a lot more, stronger collaboration, because some of these efforts will be more compute-intensive, so it makes sense to do it at a certain scale together,’ Google CEO Sundar Pichai.
As that happens, a new basis of competition has been opened by Google: “Google published details about its AI supercomputer on Wednesday, saying it is faster and more efficient than competing Nvidia systems. While Nvidia dominates the market for AI model training and deployment, with over 90%, Google has been designing and deploying a chip, called Tensor Processing Unit, for artificial intelligence since 2016, partially for internal use.”
Yes, the hardware will create a separation. Apple won the mobile world by creating proprietary hardware that powers exclusive software. Google understands that redesign and is going for an x-factor. Indeed, for the AI systems to advance at the software level, the hardware which crunches the bits and bytes must evolve. If you control that evolution in machines, you win the race. Every software is limited by the hardware which runs it; expanding that nexus will provide massive opportunities. That explains why Apple will play a role because it knows how to make great chips especially for consumer markets.
Hardware will advance and AI systems will accelerate in performance, and what happened in farms more than a century ago will begin to take place at scale in companies. But as that happens, AI will make the European labour laws go global as technology redesign causes dislocations in markets. Yes, you cannot just fire workers – and governments will demand that as adoption begins to transform industries.
After announcing the largest rounds of layoffs in their history, US big tech companies are now learning how difficult it is to reduce headcount in Europe.
In the US, companies can announce widespread job cuts and let go of hundreds if not thousands of workers within months — and many have. Meanwhile, in Europe, mass layoffs among tech companies have stalled because of labor protections that make it virtually impossible to dismiss people in some countries without prior consultations with employee interest groups.
This has left thousands of tech workers in limbo, unsure about whether they’ll be affected by negotiations that can drag on indefinitely.
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Comment 1: Hey Ndubuisi, great post! I definitely agree with your point about the importance of AI hardware in the development and adoption of AI-powered solutions. It’s not just about the software or algorithms, but also about the hardware that can efficiently and effectively run those algorithms.
The AI tractor example you mentioned is a perfect illustration of this. By developing hardware specifically designed for AI-powered farming equipment, John Deere was able to significantly improve the performance and capabilities of their tractors. And as you mentioned, this is just the tip of the iceberg – there are so many other industries and applications where AI hardware can make a huge difference.
Overall, I think it’s exciting to see how AI hardware is evolving and becoming more specialized. It opens up new possibilities for innovation and could really transform the way we live and work. Thanks for sharing your thoughts on this topic!
Comment 2: It’s getting more interesting.The AI supercomputers will incorporate specialized hardware acceleration technologies, such as graphics processing units (GPUs), tensor processing units (TPUs), or field-programmable gate arrays (FPGAs), which are optimized for AI workloads.
These specialized hardware accelerators can significantly speed up AI computations, making AI supercomputers more efficient and capable of delivering higher performance compared to general-purpose computing systems.
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Brain and Mind by Google. Once the software battle in the AI space is won, the real war shifts to hardware, with its high barrier to entry, only few come unscathed.
As for sacking workers indiscriminately in the name of newfound technology, it will become much more difficult, because you may be required to provide actual proof. It is not enough to cover everything by thundering loads words like ‘efficiency’ and ‘restructuring’.
Maybe stock value will no longer rise with lower workforce, rather with larger one, with this inverse, all the shenanigans will cease.