You should never want a $1 MRI (4 reasons why)

Just yesterday a friend and I had one of those debates that starts casual and turns into a real mental workout. The deeper we went, the more it forced me to clarify my thinking about markets, pricing, and how we interpret signals in a world that’s constantly shifting.

Here’s how it started:

Imagine a future where getting an MRI only costs $1, and this happens naturally in a free market, with no government subsidy or artificial distortion.

Is this automatically a win for humanity? Would MRIs, now accessible to all, be more valuable than ever?

At first glance, this sounds obvious:
Lower costs → more access → better outcomes. Right?

As my friend continued making his point, I got lost in thought over his seemingly obvious assumption.

I thought about what prices actually signal—and how markets work—I realized something:
A $1 MRI would actually tell you something very different about that world. And it wouldn’t necessarily mean patients are better off because of it. And the reason isn’t even the oft-cited worry of overdiagnosis and incidentalomas.

If you immediately thought a $1 MRI would be more valuable, you made a fundamental statistical mistake. Let’s break it down:

First, what does a price actually reflect?

To understand this, you have to be clear on what a price is, and what it means.

In any functioning free market, the price of a good reflects more than just its cost of production. It emerges from two forces:

Supply-side costs — how expensive it is to produce
Demand-side value — how much people are willing to pay for it, compared to everything else they could buy

Price is not simply about cost. It is about scarcity and relative value at the margin— meaning, compared to all other available options, how much does society prioritize this good?

That’s why high-margin luxury goods can stay expensive even if they’re cheap to produce — because demand is strong, relative to supply.

And it’s why older technologies — even if still functional — can see their prices collapse when something better comes along.

Would supply-side cost savings alone explain a $1 MRI?

One possible argument is:
"Maybe MRIs got radically cheaper to produce — so they now cost $1, but they’re still just as useful as today."

At first, that seems plausible. But when you follow the logic of markets, it doesn’t hold up.

If MRI production costs dropped massively, but MRIs remained the most valued diagnostic tool, what would producers do?
Simple: they would keep prices higher — and enjoy larger profit margins.

In any market where a product remains relatively scarce and highly valued, companies have no incentive to collapse their prices — because customers are still willing to pay.

Prices don’t naturally fall to near-zero unless they are forced to.

Which brings us to the next piece:

What would actually force MRI prices to $1?

In a free market, there are only a few ways for this to happen:

✅ New, superior diagnostic technologies emerge — that do a better job than MRIs in many (or most) cases
✅ Consumers (patients, doctors, hospitals) shift their demand toward these new options
✅ MRI producers face growing competition, and must lower prices to stay relevant
✅ The MRI is no longer relatively scarce or highly prioritized — so its price drops toward marginal cost

In other words:
A $1 MRI tells you that other diagnostic tools have now surpassed the MRI in relative value — otherwise, MRI prices would not collapse to this level.

Why this isn’t just “cheaper is better for the patient”

At this point, some people may still think:
"But even if MRIs are relatively less valued now, isn’t this still better for patients? It’s cheaper! More access must be good!"

Here’s why that’s not the right conclusion:
A price collapse signals competition — and in this case, it would mean that newer diagnostic technologies have emerged that are superior to MRI in meaningful ways.

If MRIs were still the best or most useful tool in most situations, prices wouldn’t collapse all the way to $1 — because many buyers would still pay $100, $200, $500 for the tool they need most.

The fact that MRIs must now compete at $1 also necessitates that:
✅ Other tools are providing better outcomes or greater value to patients in the care process.
✅ The MRI is now used in fewer cases, or in more marginal roles.
✅ Most patients are now being served by superior diagnostics — not the $1 MRI.

Therefore, the $1 MRI is not inherently “better for the patient” — it is in fact a signal that better options now exist, and that patients are likely actively choosing to get superior care through those newer non-MRI tools.

This to me, is a beautiful example of the most common mistake people make in predicting and analyzing situations. People forget to update their priors.

Why you must update your priors — the Bayesian point

Here’s where Bayesian reasoning helps.

When you observe a $1 MRI, you cannot hold your prior belief that “MRI is still central to care and the best tool we have.”

The price collapse is evidence that the market has shifted — that superior alternatives are now in play. The more extreme the price drop, the stronger the evidence that the MRI is no longer the best option in most contexts.

Without burdening you with mathematics (though I recommend you look it up), this is how proper Bayesian probabilities work:

• You observe new data: MRIs now cost $1 in a free market.
• You update your prior: We are now likely in a world where superior technologies exist — and where MRI plays a diminished role in care.

Why the alternatives are likely not just marginally better — but vastly superior

The size of the price collapse matters.

A trivial innovation — one that only slightly outperforms MRI — wouldn’t force MRI prices all the way to $1.

MRI producers could still charge $100, $200, $300 — many buyers would pay, if MRI remained competitive.

The fact that MRI prices have collapsed to $1 signals that the alternatives are not just marginally better — they are vastly superior in most cases.

This is a key point many people overlook:

👉 The greater the price collapse, the stronger the signal that the gap between the old tool (MRI) and the new options is large.

An analogy: rapid antigen tests vs PCR

Think of rapid antigen COVID tests vs PCR tests:

• Antigen tests are cheap and fast — but they are not the gold standard for accuracy.
• PCR tests are slower but more accurate — and remain the top choice when clinical certainty matters.
• As better diagnostics emerge, cheap antigen tests become more marginal — useful in some cases, but not the primary choice.

If antigen tests were forced to sell for $1, it would reflect that superior options now dominate the market for serious use cases — and antigen tests are now only used in peripheral roles.

The same logic applies to the $1 MRI: The fact that it is $1 means it is no longer the primary, most valuable diagnostic tool in that world.

Final takeaway

If you observe a future world where MRIs cost $1, here is what you should conclude:

✅ The medical ecosystem has changed.
✅ New diagnostic tools exist that outperform MRI in many or most cases.
✅ The MRI now plays a smaller, less central role in care.
✅ Patients are now being served by better alternatives in most situations.

A $1 MRI is not “more useful” — it is less useful relative to the other available options. That is exactly what the market price is telling you.

And most importantly:
Cheaper is not automatically better for patients — especially when it signals that newer, superior tools now dominate the care pathway.

Broader lesson

This little debate taught me a deeper truth about markets:

Prices reflect scarcity and relative value — not just cost or intrinsic usefulness.
And when prices change drastically, you must update your priors about what else has changed in that market.

This principle applies everywhere:

• AI
• Consumer tech
• Energy
• Healthcare
• Education
• Labor markets

Whenever you see a big price shift — don’t stop at “costs dropped.”

Ask:
What else must have changed in this market? What does this price tell me about new alternatives and evolving demand?

Or my favorite question to always ask:
What conditions must be true to produce these outcomes?

If you enjoyed this breakdown — I’d love to hear what other examples have you seen where falling prices signal a deeper market shift, or other instances where people tend to think one thing but reality is another?

Next week at some point I’ll be sharing a few examples from everyday life where you and I probably keep making Bayesian reasoning mistakes by failing to update our priors. Knowing this will help you get better at predicting things. Prediction allows you to gain leverage. Everything I write here is to help you gain leverage.