In early February, a bold test could begin in a handful of Russian schools. The number of participating institutions would be small. A neural network would review student essays in Russian language, literature, social studies, and other school assignments. Supporters claim it could save teachers time—perhaps around 20 percent—but the author questions the basis for such savings and why it could not reach 100 percent. Still, the testers are convinced they know better.
In theory, it might be possible for AI to shoulder much of the teaching load, even shaping students’ sense of national identity. If a neural network can grade work, why not rely on it for writing tasks as well? The idea is not merely about efficiency; it suggests a reallocation of time for both teachers and students. There are anecdotes about AI-written articles: some say the AI drafts in a foreign language before translation, then pass inspection by veteran educators who acknowledge that the piece, with some flaws, meets the assignment requirements. The impression is that the AI could complete tasks quickly with well-chosen literary examples, saving time across the board.
The broader point is to consider bringing AI into everyday life more openly, especially in areas where human capacity is stretched. This includes public administration, where automation might streamline processes and decision-making.
There is a steady stream of publications on this topic. Some voices sound an alarm, warning that machines could steadily gain influence and upset established systems. Others counsel calm, arguing that artificial intelligence will never fully replace human cognition. Questions about empathy, emotion, and genuine creativity linger. Do modern AI systems ever truly replicate human warmth or the nuances of personal connection? Critics wonder whether such traits will ever be fully replicable by machines, especially when decisions impact people’s lives.
Journalism itself has shown that AI can produce standard news copy that a typical reader would find indistinguishable from work written by a human. Meanwhile, contemporary media often relies on familiar stereotypes and unexamined assumptions, highlighting risks in how information is framed and consumed.
Thus, if AI begins to generate notes and reports according to procedural manuals, many participants may simply relax and reclaim time for leisure and recreation. Historical parallels are invoked, noting that during previous industrial shifts some experts insisted machines would never supplant skilled labor. The current era echoes that debate, with automation now touching call centers, online ad targeting, banking analytics, and driverless transportation networks. The trajectory points toward ongoing automation and the emergence of new roles that demand creativity rather than repetitive, rule-bound work.
Forecasts from international bodies suggest a net job balance: tens of millions of roles may be displaced by AI and robots, while nearly as many new opportunities could appear—often in design, analysis, and creative problem-solving domains.
Defenders of AI argue that some limits remain. Critics claim that emotional intelligence, authentic creativity, and true empathy are beyond machine reach. They point to human nuance in service and relationships as uniquely challenging for automation. Yet observers note that people themselves are shaped by corporate policies and social pressures, and that creativity can appear constrained in many workplaces. The fear is that society might drift toward rigid behaviors shaped by algorithms, with personal growth and spontaneous insight gradually sidelined.
In this light, a future where machines guide many decisions does not imply a loss of humanity. Instead, it invites a recalibration of roles where cognitive labor, emotional understanding, and social intelligence become the truly defining assets. Societies may still value human initiative, curiosity, and moral judgment even as automation handles repetitive tasks and data-driven decisions. The idea is to imagine a world where collaboration between people and intelligent systems leads to more open inquiry, more informed choices, and a broader spectrum of opportunities for creative work.
Ultimately, the question remains: how should societies balance efficiency with meaningful human activity? The answer will shape policy, education, and everyday life as AI becomes a more common partner in work, learning, and civic life. The perspective offered here reflects a personal view and may not align with editorial positions.