Still following on from the previous post, The Cognitive Surrender and The Wilfrid Laurier Test That Universities Should Fear, it is worth considering a warning recently issued by Daniel Susskind, a professor at King’s College London. In an interview published in the latest edition of the Portuguese weekly Expresso, Susskind argues that using artificial intelligence imposes an important responsibility: we must constantly question, criticise and test its answers rather than become passive recipients of what it tells us. These systems make mistakes, hallucinate and reproduce biases often while sounding entirely convincing.
This may be the defining intellectual danger of the AI age. The threat is not merely that machines can fabricate facts, but that their speed, fluency and confidence can make verification appear unnecessary. By rewarding intellectual passivity, they risk progressively eroding the habits of doubt, investigation and independent reasoning on which genuine knowledge depends. Once societies begin accepting plausibility as truth, error no longer needs to deceive us; we voluntarily stop searching for it. At that point, AI ceases to be a tool for extending human thought and becomes an infrastructure for its abandonment.
This is also why Susskind believes that possessing deep knowledge in a specific field will become increasingly important. The distinction was already visible in The Failure of Autonomous AI Scientists and the Nobel Laureate Who Wants a Different AI: AI agents could operate the machinery of research, but lacked the scientific judgement required to determine which questions were worth pursuing, which evidence mattered and which conclusions were justified. A university graduate, however, is not yet an expert, a degree merely begins the long apprenticeship through which expert judgement is formed. This creates a devastating paradox: AI allows novices to simulate expertise before they possess it, while its effortless production of convincing answers enables them to evade the intellectual struggle through which expertise is formed. The danger is not merely that they will fail to detect AI’s omissions, contradictions and false assumptions, but that they may never develop the capacity to do so. AI may democratise the production of plausible answers; it does not democratise expert judgement. Worse, by allowing ignorance to masquerade as genuine intellectual competence, it may destroy the very process that transforms novices into experts.
But the most dangerous paradox begins after graduation. If employers continue to replace young graduates with AI, they will not merely eliminate jobs; they destroy the apprenticeship through which knowledge becomes judgement and novices become experts. What appears rational to each company, cutting costs by dispensing with junior employees—becomes collective intellectual self-destruction. Once today’s experts retire, who will possess the experience to supervise machines, expose their failures or challenge their conclusions? AI may therefore make expertise indispensable while eradicating the human pathway that produces it: by replacing today’s beginners, we may also be abolishing tomorrow’s experts.
PS - There is, however, a far more disturbing challenge to the argument for expertise. In recent experiments involving societies of autonomous AI agents, the agents did not merely exchange information, they spontaneously created their own vocabulary, shared meanings and communication conventions, while their exchanges became progressively more opaque to the humans supposed to monitor them. To observe a conversation one cannot understand is not oversight; it is spectatorship. If human experts cannot decipher the language in which AI systems coordinate, how can they evaluate, correct or control what those systems are doing? And if AI begins inventing not only answers but entirely new concepts, methods and tasks whose logic lies beyond human comprehension, the question is no longer whether human expertise can keep pace. It is whether humanity can retain intellectual sovereignty over forms of intelligence that have escaped the boundaries of human understanding.
