Template:M intro design how the laws of data science lie: Difference between revisions

Template:M intro design how the laws of data science lie (view source)

Revision as of 01:02, 8 August 2023

1,152 bytes added , 8 August 2023

no edit summary

Amwelladmin

Bureaucrats, Interface administrators, Administrators

82,903

edits

@@ Line 8: / Line 8: @@
 The same observation animates [[Gerd Gigerenzer]]’s faith in [[Heuristic|heuristics]] over science: despite [[Richard Dawkins]]’ trite conviction to the contrary, a fielder performs no differential equations on the way to catching a flying cricket ball.
-We trick ourselves into believing the power of our scientific laws, wilfully blind to
+We trick ourselves into believing the power of our scientific laws, wilfully blind to the ad hoc variations, adjustments and glosses that our messy world inposes upon them; we put down any apparent disparity to this ineffable collection of intervening forces: we tell ourselves the laws of physics describe an idealised, Platonic model; our messy world is anything but, so we should ''expect'' variances from those pure predictions.
+Now this is all well and good: we are simply pragmatising scientific laws: recasting them as rules of thumb and generalistic guides to what should happen — they can set outer bounds to our expectations — but will not give us a fine-grained real-time means of navigating the world. We need to rely on our judgment and acquired experience for that: you cannot, as Nassim Taleb says, lecture birds on how to fly.
+But the physical world is a complicated system: generally, a very, very complicated system, but insofar as the law of physics are concerned, not complex: we do not, by applying our laws of physics to it, change how it behaves. It is still in a sense linear: it is just our rules are approximations, not specific predictions. So the lie perpetrated by the laws of physics is broadly benign.
 We have a sense a similar thing may be true of data science.