Why intelligence can no longer be society’s measure of human value in AI era

The author also points out a deep irony. The abilities that AI struggles most to replicate are those society has long treated as lower-order. Embodied care, manual dexterity, ecological stewardship, and context-sensitive judgment remain difficult to automate. Yet these are precisely the skills that have been systematically undervalued in education and labor markets.

A new scholarly paper argues that the long-standing belief that cognitive ability equals merit is approaching a breaking point. The implications extend beyond jobs or productivity and reach into how societies define dignity, value, and belonging.

Published in AI & Society, the article titled “The End of Cognitive Meritocracy” offers a stark assessment of how AI destabilizes what the author calls the dominant hierarchy of human worth. Written by Deniz Fraemke of the Max Planck Institute for Human Development in Berlin, the piece argues that modern societies are organized around an unspoken assumption that abstract cognitive performance is the highest and most legitimate basis for distributing opportunity and respect. AI, the author contends, is rapidly rendering that assumption untenable.

How cognitive merit became the measure of human value

Modern societies, the article explains, are structured around a hierarchy that treats abstract reasoning, analytical problem-solving, literacy, and planning as higher-order abilities. These skills dominate education systems, hiring criteria, and professional advancement. Conversely, manual skills, embodied intelligence, caregiving, sensory acuity, and routine cognition are consistently ranked lower, regardless of their social importance.

This hierarchy is not presented as neutral or inevitable. The article argues that it is a historical construction shaped by industrialization, bureaucratic governance, and standardized education. Over time, it hardened into a moral framework in which intelligence became synonymous with deservingness. Success was framed as earned through merit, while failure was often interpreted as a lack of cognitive ability or effort.

This system disguises structural inequality as fairness. Cognitive abilities are influenced by genetics, early childhood environment, nutrition, and access to education. When societies reward certain cognitive profiles above all others, they effectively turn biological and developmental differences into lifelong advantages or disadvantages. Under the banner of meritocracy, a narrow range of talents receives disproportionate dignity and reward.

The result is a hierarchy of human worth that reaches far beyond income. Prestige, self-respect, and social recognition become tied to cognitive performance. Occupations that require abstract reasoning are elevated, while forms of labor essential to social functioning, such as care work, craftsmanship, and maintenance, are devalued. The article argues that this ranking has become so entrenched that many people perceive it as natural rather than constructed.

This framework has shaped how societies approach education and work for decades. Students are sorted early based on cognitive performance, with standardized testing reinforcing the idea that intelligence can be measured, compared, and ranked. Labor markets then extend this logic, using credentials and analytical skill as gatekeepers to opportunity. Until recently, the system appeared stable because humans occupied the top of the cognitive hierarchy.

Why AI strikes at the core of cognitive hierarchy

AI disrupts this arrangement with unprecedented speed. The article notes that contemporary AI systems now perform tasks once considered the pinnacle of human intelligence. They draft legal arguments, analyze medical images, generate scientific text, predict outcomes, and plan complex processes. These are precisely the domains that modern societies have treated as evidence of superior human value.

This creates a paradox. The abilities used to justify social stratification are becoming the ones where humans are least competitive. If intelligence remains the primary measure of worth, the logic of cognitive meritocracy points toward human obsolescence. Machines do not merely match human performance. They scale it, reproduce it instantly, and improve it continuously.

The article challenges the popular reassurance that humans will simply move up the value chain. It argues that human cognition has biological limits. No amount of training or motivation can push human neural architecture beyond certain bounds. AI systems, by contrast, are not constrained in the same way. They can expand in speed, memory, and complexity without fatigue or diminishing returns.

The author also points out a deep irony. The abilities that AI struggles most to replicate are those society has long treated as lower-order. Embodied care, manual dexterity, ecological stewardship, and context-sensitive judgment remain difficult to automate. Yet these are precisely the skills that have been systematically undervalued in education and labor markets.

This mismatch exposes a strategic error embedded in cognitive meritocracy. Societies have spent decades rewarding the forms of intelligence most easily replicated by machines while neglecting those that distinguish human contribution. As AI advances, the hierarchy that once favored abstract cognition becomes a liability rather than an advantage.

The article further warns that AI does not merely replace tasks. It inherits and amplifies human norms. If cognitive hierarchies are embedded into algorithms that govern hiring, healthcare access, or social services, they will be enforced at scale. AI-driven systems already screen job applicants for analytical traits while discarding signals of practical competence or care-oriented skill. Once machines outperform humans cognitively, such systems risk classifying humans as deficient by design.

The existential choice AI forces on society

If societies persist in defining worth through cognitive superiority, AI will eventually outperform humans by that very standard. In such a world, humans risk becoming surplus according to their own moral framework. The danger is not that machines become hostile, but that they become efficient executors of values that no longer serve human survival or dignity.

The author argues that this outcome is not inevitable. AI also creates an opportunity to confront the fiction that intelligence equals worth. When machines permanently surpass humans in abstract reasoning, ranking people by cognitive ability may lose legitimacy. What has long been treated as natural could be revealed as a temporary historical obsession.

This shift would require revaluing human plurality. Instead of treating intelligence as a single axis of merit, societies would need to recognize multiple forms of contribution. Care work, ecological maintenance, manual skill, and social coordination would need to be treated as central rather than peripheral. Such a transformation would challenge existing institutions but could align social values more closely with what remains uniquely human.

The article warns against complacency. The same technologies that could destabilize cognitive hierarchies could also harden them. If AI is trained and deployed within existing systems of cognitive elitism, it will reinforce inequality with unprecedented efficiency. Algorithms do not question the values they inherit. They scale them.

The choice, the author suggests, is stark. Societies can cling to a hierarchy that measures worth by intelligence and risk allowing AI to render humans irrelevant. Or they can let go of that hierarchy and redefine value in a way that reflects the full range of human capacities. The collapse of cognitive meritocracy could be destructive or liberating, depending on how institutions respond.