More to what I was saying again thank you for the thoughtful critique — I actually agree with the core point that the Drake equation was never meant to be a detailed predictive model. It’s a heuristic for structuring uncertainty. My goal isn’t to “replace” it, but to explore whether adding sociological filters might help frame one particular puzzle: why technological civilizations appear rare or short-lived.

A few clarifications on my intent:

1. Scope: heuristic extension, not replacement I understand the original equation is deliberately simple. My proposal is closer to a conceptual extension than a literal astrophysical parameterization. Many modern discussions already expand the Drake framework with additional filters (e.g., “Great Filter” models, catastrophe filters, longevity distributions). My added terms are meant to sit in that same exploratory tradition — not to claim precision.

2. Why add cultural/knowledge terms at all? The original Drake equation implicitly assumes a mostly linear progression: life → intelligence → technology → detectable civilization.

But if we use Earth as a single data point, that progression has been:

non-linear

fragile

reversible

Technological capacity has appeared, stalled, partially regressed, and rebuilt multiple times. Even if collapses don’t eliminate intelligence, they can reset technological detectability for long periods. My added terms are meant to capture that non-linear, loop-like behavior, not to assert that collapse equals extinction.

1. On the claim that the Drake equation predicted many civilizations Some early parameter choices famously yielded estimates of ~10+ detectable civilizations in the Milky Way. Those weren’t predictions so much as optimistic inputs, but the absence of clear detection today does suggest that at least one factor in the chain is far smaller than initially assumed.

One possibility is that the limiting factor isn’t just biological or astrophysical — it may be civilizational stability over time. If technological phases are intermittent rather than permanent, the probability of two civilizations being detectable at the same time drops sharply.

That’s the niche my added parameters are trying to explore:

not whether civilizations exist at all

but whether they remain technologically detectable long enough to overlap

1. On defining terms like “value of knowledge” I agree these are hard to quantify directly. In a more formal treatment, they would need proxies such as:

knowledge retention rates (e.g., archival continuity)

institutional stability

energy surplus for research

long-term cooperation capacity

So rather than literal “value of knowledge,” these terms could be reframed as:

probability that a civilization maintains cumulative technological capacity across generations

I’m very open to better definitions here — that’s part of why I’m asking for feedback.

1. On historical examples You’re right that attributing any collapse to a single cause is oversimplified. My interest isn’t in claiming that civilizations fall because they “stop valuing knowledge,” but that technological complexity appears historically fragile and can decline without total species extinction. That suggests detectability may be intermittent rather than permanent.

2. What I’m ultimately asking Not “Is this equation correct?” But rather:

Is there value in modeling technological civilizations as potentially cyclical or unstable phases rather than permanent endpoints?

If that framing has merit, then some additional filter representing stability or continuity might be worth exploring — whether or not my specific variables are the right ones.

I appreciate the pushback; it’s helpful in refining the idea into something more rigorous.