“Initially, prior to the first industrial revolution, people primarily engaged in agricultural and seasonal work, following natural rhythms that had persisted for thousands of years. However, with the advent of the industrial revolution, there was a significant shift in work patterns. This transformative period saw the emergence of a work model wherein humans became subordinate to machines: Over the past two centuries, human behavior has adapted around machines, with work hours aligning with electricity availability and tasks becoming increasingly standardized, often on production lines. This model, initially prevalent among factory workers, gradually extended to white-collar professions as well. As a result, our entire economy has become entrenched in a productivity-driven concept of work, characterized by mechanistic principles.

We are now entering a period of enormous shifts due to AI.

The first thing to say is that this technology is evolving by leaps and bounds. The biggest leap happened first in 2000, and then in 2020 there was a huge leap, a leap that no one expected to happen.

In 2000-2005 and right after, an approach to AI that was not the dominant one till then, created due to cheaper computational power and an increase in the availability of data, in connection with the development in some statistical models of machine learning, gave AI the form it has today, which is based on neural networks (Neural Networks) – in contrast to another form of AI that worked with what we call “symbolic logic”. Suddenly we have systems that can, for example, recognize faces. In 2017, a paper came out from a group at Google, that talked about a type of neural network architecture called “transformers”,  upon which LLM-GENAI is based. This is a huge leap, because before that we had an artificial intelligence that was “narrow” i.e. each system had a specific application-now we have a general purpose intelligence system that behaves to us as we thought AI would behave to us in 20-30 years. This is evolving incredibly quickly. So, even due to speed, I don’t think we can react with relative safety. Let’s say regulators already tried to come up with an AI Act that was based on a view, perception and awareness of how AI works that could already be outdated. So the biggest impact of AI today is its speed.

Consider an example regarding intellectual property (IP). AI systems are trained using data from the world wide web. Suppose you’re a writer, artist, or photographer who has authored a book. The AI can learn from your work, and if instructed, it can generate a follow-up piece that emulates your style and content, essentially writing on your behalf.

In economics, there’s a phenomenon known as the “lump of labor fallacy.” This misconception suggests that if someone takes a portion of available work, the remainder will persist. It’s commonly believed that the amount of work accessible to individuals is fixed. However, this notion is flawed. Our economy demonstrates that new forms of labor continually emerge even as existing tasks are completed. AI systems, such as LLMs, exhibit emerging behaviors, including some capabilities for mathematical calculations despite lacking specific training in this area. As a result, new professions have arisen to study the behavior of these machines.

With the ever-evolving landscape of tasks, there’s an increasing demand for upskilling to remain competitive and enhance productivity. As technology advances, the necessity for ongoing learning and skill development becomes even more critical in ensuring success in the workforce.

This highlights Microsoft’s strategic positioning as a leading developer of AI technology, given its essential role in powering infrastructure worth tens of millions of dollars. The energy consumption of GPT Chat, for instance, is comparable to that of the entire nation of Greece, emphasizing the scale of operations involved. Recognizing the potential for robust artificial intelligence development, Silicon Valley invested heavily in data and computing power, resulting in the creation of advanced AI models like LLMs. These tech giants, including Microsoft, maintain a stronghold in this domain. Microsoft’s “Co-pilot” initiative exemplifies this trend: as a white-collar worker, I now have an AI system at my disposal, significantly enhancing productivity. For example, with the assistance of an LLM, I could complete a PhD in one month instead of three years. The LLM would handle tasks such as information collection, reading, summarization, leaving me to direct the process efficiently.”

“We think that AI does not possess creative capabilities itself, but that’s not true, GEN AI actually does. Take, for instance, industries like cinema or theater, traditionally requiring collaboration among various professionals. With modern AI systems, it’s conceivable that only a director would be necessary, rendering other roles redundant—this shift partly explains recent strikes in America*.

Similar to how the internet transformed print media, today’s LLMs, versatile and imaginative, are reshaping the workforce landscape. This poses a threat to experts, as proficiency in crafting effective prompts becomes paramount; the better the question, the more insightful the LLM’s response. While the skill of inquiry remains a distinctly human trait, AI, particularly Generative AI excels in generating answers.

Moreover, LLMs now exhibit proficiency in understanding social context, addressing a longstanding challenge in AI development—the integration of common sense—previously elusive until recent advancements.I don’t believe there are any skills these models can’t replace. The fundamental concept of work is undergoing a profound transformation, one for which many people are unprepared. Existing institutions must adapt to accommodate these shifts. History demonstrates how technological advancements precipitate significant social, economic, and other transformations. We say that these immense technological shifts will bring either evolution or revolution. Forward-thinking societies endeavor to proactively regulate and assimilate these changes, steering towards the evolutionary path.

“Well, first of all, from an economic standpoint, immediate job loss isn’t an issue for now. However, remuneration for these roles may diminish over time. Societies resistant to change, lacking in social adaptability, risk stagnation. It’s evident that the challenge extends beyond individual readiness; societal preparedness is essential. Flexible societies that embrace change are better positioned to thrive. As a result, we may witness an influx of white-collar workers from nations where wage levels remain stagnant due to limited economic growth prospects. Numerous variables will influence the impact of these changes at the individual but also the economic, societal, and national levels. I think employees would be ready, first of all, for that.”

“Certainly, it’s not just individuals but also companies that will be profoundly affected by these changes. How companies respond to these dynamic changes will be crucial and will vary depending on factors such as their organizational structure, technological adoption, aggressiveness in seizing opportunities, philosophical point of view, and market strategies. Different sectors of the economy will experience varying impacts; for instance, the automation potential in software development could greatly benefit companies in that sector by streamlining processes. The internal restructuring of these companies to capitalize on such changes will be guided by management decisions.”

“This transformation is already underway, exemplified by the rise of individual contractors and freelancers utilizing platforms like Upwork and Fiverr.

These individuals are finding success due to various factors, including better alignment with their lifestyle expectations and the social dimensions of their work. Unlike the rigid model imposed by the industrial revolution, modern society craves flexibility in employment. The proliferation of platforms enables individuals to provide services without the need to establish full-fledged companies- the existence of which were primarily driven by the economic efficiency of consolidating labor under contracts, as outlined by the Theory of the Firm.

However, the emergence of platforms has streamlined this process significantly. Freelancers leveraging these platforms essentially operate as small businesses, collaborating with external partners and forming micro-companies. This dynamic contrasts with traditional organizational structures within companies. Transactions on these platforms prioritize skills over personal attributes or resumes. Work is disaggregating into activities that allow the implementation of talent-on-demand strategies. As a result, hiring decisions are based on the specific skills required rather than generalized qualifications. This shift in the hiring process is particularly significant amidst rapid changes, as companies may find themselves uncertain about their workforce needs.

So, we see that the integration of this evolving landscape into company structures has already begun. Internal platforms are being implemented within companies, allowing them to post jobs or projects for employees to join and collaborate on. This shift emphasizes a shift away from traditional processes inherited from the industrial revolution, towards a model focused on projects and platforms. The goal is to create an internal marketplace for skills, knowledge, and productivity, fostering motivation among employees to acquire the necessary skills to enhance their value within this dynamic environment. Central to this approach is the adoption of systems that facilitate navigation and empower employees to seek greater flexibility and satisfaction in their work.

“This transformation is integral to the digital transformation agenda.

HR plays a crucial role in supporting this shift by redefining performance management and measurement, incentivization methods, skill matching, and the review process. Unlike the annual review process inherited from the industrial revolution, today’s approach is more dynamic and continuous. Despite the challenges of breaking away from established norms, particularly those rooted in the industrial revolution, history has shown that societies unwilling to adapt tend to stagnate and decline. This underscores the imperative for societies to embrace change in order to thrive—a fundamental principle of historical progression.

Furthermore, it is crucial for both unions and workers to not only accept but also actively guide this transformation for the betterment of all workers.”

“Well, I think Greece possesses significant potential and numerous advantages.

Think about it, we have a workforce equipped with new skills, strong higher education institutions, and well-developed infrastructure, including roads and internet connectivity. Greece also stands as a promising destination for companies looking to relocate some of their operations. I’m not familiar with what’s happening right now, but I do think that Greece is poised for progress.”