FOR centuries, the growth of civilisation has depended on tools that extended the reach of the human mind. The telescope enabled astronomers to peer into distant galaxies. The microscope revealed invisible organisms. The computer transformed complex calculations into routine operations. None of these inventions replaced human intelligence. Each amplified it.
What we call artificial intelligence belongs to this same lineage, yet the phrase itself may be misleading. In common language, the word ‘artificial’ often carries an unintended implication of imitation or inferiority. Artificial flowers are not real flowers. Artificial sweeteners mimic sugar. Artificial limbs substitute for natural ones. The adjective can suggest something synthetic rather than authentic. That connotation does not accurately describe the most meaningful uses of AI.
When a writer uses AI to draft an article, the system does not independently create a finished intellectual product. The algorithm searches and synthesises information from humanity’s vast digital archive, but the human author defines the purpose, frames the question, chooses the analytical framework, evaluates evidence, verifies facts, revises the prose and accepts responsibility for every conclusion. The resulting work is not purely artificial. It is participatory.
For this reason, a more precise term may be participatory intelligence (PI). This concept captures a fundamental reality: the machine does not possess independent intelligence in the human sense. Rather, it participates in an intellectual process directed by a human being who supplies the purpose, questions, conceptual framework, ethical judgement and final interpretation. The word ‘participatory’ emphasises collaboration rather than autonomy and correctly identifies the machine as an instrument that extends, rather than replaces, human reasoning.
The machine contributes computational speed, vast memory, pattern recognition and rapid synthesis. The human contributor provides intention, context, creativity, scepticism and responsibility. The resulting output is a joint product, but genuine understanding remains rooted in human consciousness. Purpose, judgement and accountability continue to reside in the human mind, which alone bears responsibility for the meaning and consequences of the final work.
This relationship mirrors the way machines have always functioned in economic production. A tractor participates in agriculture but does not understand farming. A lathe participates in manufacturing but does not comprehend engineering. A calculator participates in mathematics but does not grasp mathematical truth. Likewise, large language models participate in the creation of narratives but do not understand truth, morality or meaning as human beings do.
The same principle applies in medicine. Physicians routinely use magnetic resonance imaging, computed tomography, and ultrasound to visualise internal organs, tumours, fractures and blood flow. These machines generate extraordinarily useful images, but they do not diagnose disease. The physician interprets the images, combines them with symptoms, laboratory results and medical history and makes the final diagnosis. No one calls this an ‘artificial diagnosis.’ The machine participates in diagnosis; it does not diagnose.
The pharmaceutical industry offers another example. Modern factories manufacture antibiotics, insulin, vaccines and countless life-saving drugs. Yet no one argues that these factories produce ‘artificial cures.’ The factories participate in the production of medicine, but scientific knowledge, clinical judgement and therapeutic decisions remain fundamentally human.
Public discussion of AI often swings between two extremes. One camp portrays it as a miraculous substitute for human intelligence. Another depicts it as a dangerous force that will erode originality and destroy thinking. Both views miss the central point: the quality of the output depends on the quality of human participation. The human mind remains the pilot; the machine is the engine.
From an economic perspective, AI represents a major technological advance. It sharply reduces the marginal cost of producing text, images, audio and video. Just as industrial machinery lowered the cost of manufacturing and computers lowered the cost of information processing, AI lowers the cost of producing narratives and analyses. When costs fall, supply expands. The world is already experiencing a flood of AI-generated essays, reports, graphics and presentations. This democratises access to intellectual tools and can substantially increase productivity.
But increased output does not guarantee increased truth. Because AI predicts statistically plausible sequences rather than understanding reality, it can fabricate facts, invent references and present errors in polished language. If users accept those outputs without scrutiny, they transfer the risk of misinformation to readers, students, clients and citizens. The economic lesson is clear: information is becoming abundant, but trustworthy judgement remains scarce.
This scarcity is particularly important in journalism. Credibility is a form of institutional capital built slowly and lost quickly. Responsible journalists can use AI to summarise documents, explore data and improve clarity. Irresponsible use can contaminate reporting and erode public trust. In an age of information abundance, trust becomes one of the most valuable forms of social capital.
Education presents a similar challenge. Students who use AI to compare ideas, test arguments and refine drafts may deepen understanding. Students who use it to bypass thought may sacrifice the very learning they seek. Scientific research also depends on participatory intelligence. AI can assist in organising literature, generating hypotheses and analysing data, but discovery still requires human scepticism, methodological rigor and ethical responsibility.
History suggests that powerful tools increase rather than diminish the value of expert judgement. Calculators did not eliminate mathematics. Computers did not end engineering. Medical imaging did not replace physicians. Artificial intelligence is likely to follow the same pattern, enhancing human capabilities while making sound judgement more important than ever.
The real question is, therefore, not whether society should use AI. That question has already been answered. The technology is here and will become increasingly capable. The important question is whether human beings will remain intellectually engaged and morally responsible for what these systems produce.
If they do, AI can become one of the greatest tools ever created for expanding knowledge, creativity and human welfare. If they do not, society may produce more information while generating less wisdom.
Artificial intelligence is more accurately understood as participatory intelligence: a collaborative process in which machines extend human analytical capacity, while purpose, judgement and meaning remain firmly in human hands. Artificial intelligence or, more precisely, participatory intelligence — is transforming the production of narratives.
MRI participates in diagnosis; it does not diagnose. A pharmaceutical factory participates in treatment; it does not heal. AI participates in thinking; it does not understand.
The danger lies not in artificial intelligence itself, but in natural intelligence that chooses to disengage. AI should augment human intelligence, not anesthetise it.
Dr Abdullah A Dewan, former physicist and nuclear engineer at Bangladesh Atomic Energy Commission, is professor emeritus of economics, Eastern Michigan University (USA).
