In this article, I am outlining the importance of the societal problem of upskilling today’s workforce in the age of AI. I am arguing why and how technology can be developed for people first, aiming to deploy and develop algorithms and AI to enhance and augment humans instead of purely maximizing profit through cost-cutting by replacing workers with AI and driving higher productivity gains for companies at the same time.
The Importance of Workforce Upskilling
Tech companies claiming how AI can do the job of hundreds of employees backfired. Klarna is quietly re-hiring employees after mass layoffs with the hopes of AI fully automating previous processes. In fact, ~55% of organizations that executed AI-driven layoffs now regret it.
As Nobel-prize winning economists Acemoglue and Johnsson argue from a deep historical perspective on technology and prosperity, workers need new tasks. E.g. the invention of railway cut many jobs by no longer needing to horse riders but instead opened up whole new industries such as logistics and tourism which created a lot more new jobs. Many sources confirm AI and humans work best together (MIT). Yet, many uprising startups purely focus on full agentic automation and companies are incentivized to adapt it to maximize profits by reducing labor costs.
The AI Tech Aspiration Of Universal Basic Income (UBI)
A common Silicon Valley tech assumption about AI is that eventually something like Artificial General Intelligence (AGI) will drive so much productivity gains and value creation that most jobs will be done by machines and we no longer need humans for most tasks. The positive economic impact would be so large that this could perhaps pay the immense costs for universal basic income so everyone can focus on the creative projects they truly enjoy without worrying about money.
At first sight, I thought so this is basically “socialism”. Wouldn’t the world be better off if everyone can just do whatever they like? Taking a closer look though, this theory has a major consideration, which I’d actually call a major flaw.
Imagine a industry worker on the assembly line suddenly being unemployed due to robots replacing the job. AI is doing most of the work for most people, he gets like many of his friends and family members universal basic income. he can now go and “just do whatever you want”. While it would be awesome for intrinsically motivated people similar to me, well, similar to most people working in tech, I’d have so many ideas and projects I’d love to work on. However, this is not the reality for most.
It is a pure assumption based on a unique tech-optimistic world view to think that the rest of the world thinks the same way. Not everyone in society has the intrinsic motivation to work on things by themselves. In fact, unemployment benefits in western countries already show long-term unemployment.
Imagine: The majority of the world population does not have a job and is being told to do whatever they like. People need something to do. Being connected to their community and contribute to something that can give some form of meaning and the feeling of contribution. Happiness studies show that humans thrive by achieving the goals they set for themselves.
Universal basic income from my perspective is a tech idea ignorant by the very fact that of believing that tech downsides of taking people’s jobs can be compensated by just giving everyone a free monthly pay check. While it is aspirational for repetitive administrative work, the question first needs to be answered what everyone would then be doing. Hence I am making the provoking argument that the idea is flawed and the question comes back to: Wouldn’t it be better to deploy in a way that makes human’s jobs more productive and better by upskilling employees?
Jobs Are Lost While New Jobs in Technology Are Being Created
Looking at European employment change specifically, technology is by far the highest job creation driver. Looking at this excerpt of the video below, shows how Germany lost 200,000 jobs in industry but created 600,000 new jobs in technology.
The Case For Upskilling Talent
Training investments in companies and relevant skills learned on the job not only drive worker satisfaction but also higher productivity. It is enjoyable to mentored and learn from senior coworkers and supervisors. Training of low-educated workers was a key pillar in shared prosperity before the 1980s (source). Especially in Europe and in the US economic growth was driven by educational investments in the workforce and in-company training programs. This ensured a shared prosperity by equipping workers with the right skills to fill new and emerging positions.
New Narrative About Shared Prosperity Instead Of Pure Profits
Tech talent and managers should aim for a new narrative about business and technology. Instead of following the Friedman doctrine of a business’ main purpose being reducing wages and cutting labor costs. Instead, aiming for a shared prosperity. This narrative could counterweigh the Friedman doctrine – often taught in business schools worldwide.
Automation, But The Right Way – Enhancing humans, Not Replacing Humans
Especially in the age of AI, the drive towards more agentic automation of full workflows is majorly being backed by investors.
History shows us however:
“Although the introduction of robots and specialized software has increased output per worker in the industry, there is evidence that investing more in humans would have boosted productivity by more.”
For example Japanese car makers saw discovered around 1980 that due to losses in flexibility productivity was not increasing by pure automation without a human in the loop. Toyota for example reverted the automation efforts and put workers at the central role in their production. The key is to enhance humans in most cases. An architect having the right tools and technology to be 5-10x more effective and better at doing what he does will outperform an AI attempting to replace the architect overall.
Also radiologists are a great example. It was a common prediction that radiologists will lose their jobs due to AI, yet the opposite happened. It requires situational and social intelligence and is beyond what AI is capable to do. In fact, research shows combining radiologists (human expertise) with new technology tends to be much more effective (source).
Y Combinator, silicon valley’s most prestigious startup incubator, states while AI will cut some jobs, AI can drive down costs, which drives demand which then again drives more emerging work – having humans in the loop.
Conclusion
As you are reading this, chances are high you are – just like me – working in tech. Let’s use this thought-provoking article to have a more reflective and thoughtful approach on how the tech industry implements and scales AI in a way that drives higher productivity whilw benefiting humans. Upskilling employees can and will be a key economic driver for companies to benefit from AI not only responsibly but also most productively.
Book and reading recommendations
- Power and Progress: Our Thousand-Year Struggle Over Technology and Prosperity – Acemoglu & Johnson
- Flourish – Martin Seligman
