Introduction
This article exposes the naive belief that technological progress automatically translates into social progress. This "quasi-theological certainty" ignores human costs, treating them as a transient phenomenon. In reality, how we implement artificial intelligence and automation is not a historical necessity, but the result of specific institutional incentives. Readers will learn why the current innovation model often destroys prosperity instead of creating it, and what role the state should play in fixing this system.
Automation vs. AI: Systemic Traps
Modern debate often confuses these concepts. Automation is a process in which capital takes over labor tasks, while artificial intelligence is its subset based on data-trained models. Believing in their automatic benefit is a superstition because it ignores institutional arithmetic. Tax systems, by taxing wages and subsidizing capital, force the phenomenon of excessive automation. It pays for entrepreneurs to replace people with machines even when productivity growth is symbolic.
This leads to the emergence of "so-so" technologies—solutions good enough to displace a worker but too weak to stimulate real economic growth. Such innovations merely simulate prosperity, generating private profit at the expense of the public sphere. The China shock serves as a warning: it proved that the costs of global changes are geographically concentrated and, without compensatory mechanisms, lead to permanent exclusion and political rebellion.
The Economist-Plumber and the Foundations of Dignity
In the face of these challenges, the state should act as an economist-plumber. This metaphor signifies patiently clearing blockages in the system rather than designing utopias. A key problem is economic stickiness—a phenomenon where labor and capital do not flow freely due to social barriers, housing issues, and the fear of losing status. In such an environment, Universal Basic Income (UBI) sparks controversy. While it reduces bureaucracy, in its modest form, it can become "hush money" for people deprived of a social role.
The authors emphasize that professional work remains the foundation of dignity and recognition. Money will buy survival, but not the sense of being needed. Meanwhile, automation systematically reduces the labor share of national income, which strikes at the stability of the middle class. Technology becomes a tool that, instead of supporting humans, undermines the backbone of the employment structure.
The Trust Crisis and Superstar Firms
The development of AI is not planet-neutral; high emissions and the correlation of growth with energy consumption undermine the vision of cost-free "green growth." The market is dominated by superstar firms that use technology to accumulate capital and limit the bargaining power of workers. The situation is worsened by a crisis of trust in institutions—every reform, even a rightful one, is often perceived as an elite conspiracy. Additionally, the tribalization of opinion and algorithmic polarization block rational debate, turning facts into identity-based projectiles.
Critics of Banerjee and Duflo’s concepts raise three arguments: without automation we will be poorer, competition forces progress, and dignity is a category too vague for policy. While these points hit sensitive spots, they do not invalidate the main thesis: we must stop pretending that progress will solve the problem of the unfair distribution of its consequences on its own.
Summary
In a world where machines increasingly mimic human labor, the question of meaning and dignity becomes central. Is technology bringing us closer to utopia, or is it revealing an existential void, forcing us to seek value outside the labor market? The future does not have to be a race against the machines. The key is to reclaim dignity as a central economic category and to understand that GDP is only a means, not an end. We must redefine what makes us human in the age of algorithms.
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