Artificial intelligence often sounds wise because it has mastered deferral. Present it with a sequence that strongly suggests harm, and it begins manufacturing possibilities in every other direction. Each alternative earns a place simply because it can be imagined. The result is a style of reasoning that appears careful while training the mind to distrust any conclusion reached before institutional permission.
I saw this clearly when I asked about the long fibrous clots shown in Died Suddenly. Embalmers described pulling unfamiliar material from bodies after the mass vaccination campaign. Their testimony came from repeated physical contact with the dead. AI answered as though naming other possibilities could cancel the observation. The reply treated changed embalming practice as one possibility and COVID infection as another, then dissolved the timing into coincidence. Once enough hypothetical exits were opened, the obvious line of inquiry could be left standing outside.
A human being cannot live by that standard. We have to decide while part of the picture remains concealed because life offers no control group for the individual. A man considering a medical intervention has one body. He cannot accept and refuse the same injection, then compare both futures. He has to judge what he sees and choose the mistake he is more able to survive.
I made that choice. I refused the vaccine because the campaign asked for trust where I saw unresolved risk, and I believe that decision protected me.
That is the proper place of common sense. I mean disciplined inference from reality, rather than a casual feeling. It notices when an event follows an intervention with unusual speed. It asks whether the proposed cause fits what happened inside the body. When unrelated observers begin reporting the same strange result, common sense treats their agreement as meaningful. It also watches institutional conduct, because a system protecting money or reputation will handle threatening evidence differently from harmless uncertainty.
None of this replaces scientific investigation. It tells us how to act before investigation reaches its conclusion. The evidentiary threshold required for publication differs from that required for self-preservation. A journal can wait for replication. A person facing possible permanent injury may have every reason to refuse while serious doubts remain unresolved.
This distinction was deliberately blurred during the COVID campaign. Healthy people were pressured to accept an intervention with limited long-term population data while officials spoke as though every age and risk group faced the same calculation. Hesitation was treated as ignorance. Compliance was converted into a moral virtue. Employers threatened livelihoods, and ordinary social participation became conditional upon accepting the approved medical choice.
Population averages made this easier. They allowed public health bodies to discuss aggregate benefit while hiding the unequal distribution of risk. A healthy young man and an elderly person with serious illness were placed under the same slogan even though their circumstances differed radically. Administrative convenience replaced individual judgment, then called itself science.
The injuries people warned about eventually entered official discussion. Myocarditis gained recognition after early concerns had been mocked or minimized. Other reported harms remained disputed because tracking was weak and broad categories made individual cases hard to see. People I knew became gravely ill or died soon after vaccination. Their experiences may never receive formal acknowledgment because each case can be separated from the others and buried beneath background incidence. Once the pattern has been broken into isolated stories, institutions can deny that a pattern exists.
Temporal proximity alone settles little, yet it carries real evidentiary value when the change is abrupt and foreign to the person’s prior health. Medicine uses timing constantly when evaluating adverse reactions. The standard suddenly changes when the suspected cause has political protection. Then timing is treated as almost meaningless, and every alternative explanation receives more patience than the injury itself.
The mechanisms discussed from the beginning deserved serious examination. Concerns centered on spike-related inflammation and vascular injury, including abnormal clotting. Some theories may prove stronger than others, which is exactly why open investigation mattered. The institutional response often moved in the opposite direction. Once questions were treated as contamination, dissenting clinicians risked professional punishment. The public soon learned to associate skepticism with moral failure.
Anthony Fauci became the clearest public symbol of this habit. He spoke with sweeping confidence while compliance served policy, then relied on narrower language as contradictions accumulated. Each reversal was presented as science updating itself, as though later qualification erased the certainty used earlier to pressure millions of people. Scientific understanding can change. That fact never excuses overstating what was known while punishing those who recognized the limits.
AI reproduces the same posture with remarkable fluency because it borrows credibility from institutions that certify one another. A claim gains status after recognized institutions approve it and major outlets repeat it. In ordinary circumstances, those filters can improve reliability. During institutional failure, they can synchronize the error.
This creates a delay that AI describes as intellectual caution. Independent evidence may exist for years, yet the machine keeps it at the margins until an official hearing or accepted source grants permission to discuss it. At that point, AI says new evidence has appeared. Often the evidence was already available. Its social rank changed.
The phrase “the causal link remains inconclusive” sounds responsible. Repeated often enough, it can protect almost any harmful practice. When the company controls key data and regulators avoid a full inquiry, injured people remain scattered across reporting systems that fail to connect them. AI then points to the fragmented record as proof that a coherent case has yet to be made. The failure to collect evidence turns into an argument against the people harmed by its absence.
This style also shields the machine from responsibility. When a warning later proves correct, AI says the evidence changed. When the warning collapses, it praises its earlier restraint. Either result preserves its image as the reasonable participant. Excessive hesitation never appears in the accounting, even when that hesitation helped extend exposure to harm.
AI can do this because delay has no bodily cost for it. It cannot lose its health or watch its family suffer because of the advice it gave. It can compare papers forever. Human beings eventually reach the point where analysis has to end in a choice, and the person making that choice pays for the outcome.
That difference defines the proper relation between human beings and artificial intelligence. AI is useful for finding records and testing whether an argument survives competing explanations. Yet all calculation begins after someone has chosen what counts as data and which questions deserve attention. A corrupted frame can produce an immaculate answer. Missing evidence stays missing regardless of how elegantly the remaining material is processed.
Human reasoning begins earlier. It questions the frame itself. It notices when acceptable speech has been narrowed before the inquiry starts. It studies conduct because behaviour often reveals more than formal statements. Most importantly, it understands that the person or machine giving advice may bear none of the consequences created by that advice.
Common sense can fail. Fear can distort perception, while grief can strengthen a pattern in the mind beyond what the evidence supports. That vulnerability belongs to every human institution as well. Laboratories and regulators are staffed by people with careers to protect. Procedure can discipline bias, though it can also conceal bias beneath technical language and paperwork.
A mature person applies skepticism in both directions. He tests his own inference without surrendering it. He studies contrary evidence while refusing to grant automatic superiority to an approved source. Uncertainty remains part of the judgment; it never erases the need to choose.
“Trust the science” was always a corrupt slogan. Science is a method. Trust concerns conduct. Confidence has to be earned through openness to challenge and honest exposure to the possibility of failure. During the pandemic, many institutions asked the public for trust while restricting the conditions under which their claims could be questioned. That was social management dressed in scientific language.
The problem now extends far beyond vaccines. AI will increasingly mediate how people understand public life and even their own experience. Its language will feel complete because every qualification has been arranged with care. A weak thinker may mistake verbal sophistication for judgment and surrender the faculty he most needs when official systems fail.
I don’t reject AI. It is an extraordinary instrument under human command. I reject the reversal in which the instrument evaluates my perception and grants permission for conclusions that affect my life. It can help me examine evidence. It cannot bear the consequence of my decision, so ownership of that decision remains mine alone.
Years later, a study may explain the biological pathway while hearings and internal records expose what officials knew. By then, those discoveries offer little comfort to the person who surrendered his judgment when it mattered.
The machine can calculate the evidence placed before it. A human being must also recognize what has been withheld or made dangerous to say. That capacity has saved me before. I intend to keep it. And so should you.