Technologies like artificial intelligence are spreading fast across industries and every-day’s life. These tools promise great productivity gains, but their benefits are not equally accessible to everyone. Some individuals learn quickly and have success, while others struggle to adapt. This uneven adoption of technology is not just a question of personal effort. It has deep consequences for how the economy functions and how income is distributed. My research asks a simple but fundamental question: what happens to inequality when technology favors some people more than others?
The Knowledge Economy
To explore this question, I build on a class of theoretical economic models known as the “knowledge economy.” In this view, the main input to production is not machines or capital, but the knowledge that people bring. Firms are organized hierarchically: workers face problems of varying difficulty, and if they cannot solve them, they pass them up to more skilled managers.
Technology plays a central role in this setting. Better technology, like digital platforms or AI assistants, reduces the cost of completing task, or passing incomplete ones to the higher floors. This sounds like unambiguously good news. But the model shows that it is not so simple. The allocation of human resources depends on wages and profits balancing out across skill levels. For this balance to exist, income profiles must be “smooth” enough. If technology breaks that smoothness, the economy may fail to match workers and firms efficiently.
A contribution of my work is to provide a precise description of when this balance holds and when it collapses. I show that even if nobody loses their job directly to a machine, technological change can still push certain groups, especially mid-range workers, out of employment.
How Inequality Evolves
The results of the model reveal a surprising pattern. The effects of technology on inequality are non-monotonic, meaning they do not move in a straight line.
- Early stage: When technology first improves, highly skilled workers benefit the most. They can use the new tools more effectively, and their wages rise faster than others. Inequality increases.
- Middle stage: As the technology spreads further, less skilled workers also gain. They benefit from being paired with stronger managers who can now supervise larger teams. Inequality temporarily decreases.
- Advanced stage: If technology continues to advance, the middle of the skill distribution becomes problematic. Workers with average ability become too costly compared to those just above or below them. Firms prefer to hire combinations of slightly higher- or lower-skilled individuals. This breaks the smooth allocation of workers and creates a form of structural unemployment.
This sequence shows that technology does not simply replace or complement labor. It reshapes the entire structure of the labor market.
These results have important implications. First, they show that the impact of technology on inequality is not predetermined. Depending on where an economy stands, technological progress can either worsen or improve income distribution. Second, the greatest risk lies not only in automation of routine jobs, but also in the instability that hits middle-skill workers when the economic balance breaks down.
For students and young researchers, the lesson is that economic models can help us think beyond simple slogans like “AI will take our jobs.” The real question is about timing, distribution, and equilibrium. It is often said that technology “creates winners and losers”, but it also changes the very rules that decide who falls into each group.
If societies want to take advantage of the power of digital transformation while avoiding its risks, they need to anticipate these dynamics. Training, lifelong learning, and safety nets become essential. Without them, technological innovation could create not only higher inequality but also deep inefficiencies in how the economy uses its human resources.
In short, technology is a powerful driver of growth, but it can also break the balance that keeps economies sustainable. The challenge for the coming decades is to ensure that innovation raises society as a whole, rather than leaving many stuck in the middle.
Dr. Paolo Morganti
Profesor Investigador/Professor Researcher
Scripta: https://scripta.up.edu.mx/entities/person/pmorganti
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