Comment by zealon | Hacker News Reader

Comment by zealon | Hacker News Reader

Maybe a bit off-topic here, but I think there is a cause-effect relationship between number of transistors and life expectancy. More transistors implies more computing power. More computing power leads to better/faster information processing, including medical information. This leads to faster patient diagnostics, better treatments (pharmaceutical innovations), earlier and more precise health warnings (lab tests an medical equipment), and so on.

Faster and better information processing leads also to higher food quality (food processing plants), higher life quality (environmental temperature and humidity control), etc.

Germany is a highly industrialized country, so information processing power causes a big social impact.

Maybe, but there is another, perhaps simpler hypothesis: Both the transistor count and life expectancy increase with time.

One way to verify one or the other is to look at a linear hypothesis:

    States: LifeExp, Transistors, Time
    Structural Equation Model [1]:

Model 1:

    LifeExp ~ Time + Transistors + noise_exp_1
    Transistors ~ Time + noise_trans_1

(The 2nd equation means that: Transistors(t) = a * t + noise, and you try to estimate "a" from the data.)

vs Model 2:

    LifeExp ~ Time + noise_exp_2
    Transistors ~ Time + noise_trans_2

If model 2 has more predictive power of LifeExp than model 2 (i.e., noise_exp_1 is lower than noise_exp_2), then according to _this_ model, Transistors causally affects LifeExp. However, this model is way too simplistic and doesn't incorporate other causal paths, such as the one you describe (Transistors -> Computing -> DiagnosticRate -> ...)

[1] http://en.wikipedia.org/wiki/Structural_equation_modeling

Math is not my field of expertise, but I think I get your point. My point was based on a social and economics perspective. I think these other causal paths are fundamental, because they are empirically verified (computing power vs health and life quality).

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