DIGITAL LIFE

OECD warns of AI-induced “cognitive laziness”

Over-reliance on generative models may impair human judgment in the long run, according to new OECD data pointing to a pattern of AI-induced cognitive laziness. The document indicates that repeatedly delegating analytical tasks to automated systems can weaken autonomous intellectual skills and diminish critical capacity when these tools are unavailable.

Picture the scene. You’re behind the wheel in an unfamiliar city. Twenty years ago, a crumpled map lay on the passenger seat, eyes shuttling between paper and road, the mind charting streets, landmarks, intersections. Today, a soft, synthetic, almost reassuring voice takes care of everything. Attention drifts off, memory dissolves, and thought becomes a simple act of obedience. The comfort is total, almost anesthetic.

In the same way, when a question arises, there’s no need to search, to doubt, to build an answer step by step. You simply pose it to a machine. Within seconds, an artificial intelligence delivers a clear, well-argued, polished synthesis. The slowness of reasoning has vanished, replaced by immediate efficiency.

We now live in a world of universal assistance, a world where everything seems fluid, rational, effortless. These tools promise to free us from the burden of tedious tasks, to augment our capabilities, to make life simpler. Yet behind this technological comfort lurks a discreet paradox: as we delegate our cognitive faculties, we risk losing the ability to use them. By being constantly assisted, we cease to exercise what made us unique: autonomous thought.

It’s this slow drift—what I call cognitive laziness—that I’d like to discuss today. A laziness born not from disinterest, but from delegation. That of a mind that gradually surrenders to the machine to sort, choose, decide. The temptation of shortcuts becomes permanent, the fatigue of thinking disappears, and with it, the effort that forged lucidity.

Students who use digital assistants for academic assignments show a drop in performance on analog assessments. The OECD’s *Digital Education Outlook 2026* report reveals that introducing these platforms into the educational ecosystem creates an illusion of technical proficiency. Statistical data collected by the international organization suggests that the initial quality of schoolwork produced with computational support does not translate into retained knowledge.

In-person exams conducted without network access showed a reversal in grades for students who rely on automation. Removing intellectual friction during the research and writing phases hinders the consolidation of concepts in long-term memory. The OECD warns of the risk of widespread intellectual disengagement in educational institutions if language models continue to be integrated without criteria for maintaining analog-based analysis.

The illusion of competence in the professional environment... A decline in autonomous judgment is also becoming apparent in the corporate world—a phenomenon researchers liken to the loss of spatial awareness caused by the systematic use of GPS. A study cited by Harvard Business School measured the performance of professionals assisted by generative models. The results show that immediate gains in speed can come at the cost of quality or rigor in certain tasks, particularly when users encounter problems that lie beyond the AI's capabilities.

Professionals using the technology completed tasks 25.1% faster. However, when dealing with complex problems outside their specific area of ​​expertise, users showed a 19-percentage-point higher likelihood of making serious errors. The study further suggests that many employees accept incorrect machine-generated answers without verification, reinforcing the risk of over-reliance on AI in learning and operational oversight.

The loss of critical friction also affects system development and software coding. Research from Stanford University focusing on the use of autonomous computational assistants found that automation reduces the natural skepticism of technical operators. The study quantified output quality and found that professionals assisted by algorithms produce solutions with a higher rate of structural security flaws.

The research highlights a specific cognitive bias in which the user assumes automated work is correct due to the tool's seamless interface. This dynamic eliminates traditional manual validation processes, leading to an accumulation of logical errors that overwhelms senior professionals during the auditing phase. Reliance on generative models alters work structures, necessitating the reintroduction of verification methodologies based on primary sources.

Data presented by the OECD and academic institutions demonstrate that digital tools should serve to amplify, not replace, human intellect. Mitigating skill erosion requires creating artificial barriers that force a period of mental deliberation before resorting to algorithms. The sustainability of technological evolution depends on organizations' ability to preserve critical thinking as a strategic asset that cannot be entirely delegated to automation.

mundophone