Theories about dark energy – mind-bending, highly creative, and occasionally nuts

Like all the rest of us, scientists are magical thinkers.  You can most easily see this when scientists struggle to explain an unexpected result, like the accelerating expansion of the universe.  In Slate, Matthew Francis runs through some of the made-up theories that haven’t yet been proven wrong or right.  These are barely distinguishable from superstition or science fiction.  And the vast majority – probably, in the long run, all of them – are likely to be proven wrong.  “Dark energy” itself is an invented concept whose sole purpose is to explain an unexpected observation.  As I understand it, there is no “energy” that scientists can identify, and the word “dark” is used solely to indicate that we don’t know what we’re talking about.

An unexpected observation cries out for explanation that will yield expected observations (predictions).  So scientist strive to make up stories that will lead to better predictions.  But there’s no reason to think that those stories actually correspond to what is out there in the universe.  There is also no reason at all to think that the realities of the natural world can be described accurately by human language.

But scientists have no other way to communicate about their findings than to use language, either co-opting words that already have some other meaning (e.g., “dark”) or creating words (e.g, “quark”).  I’m pretty sure that these words have no meaning outside their scientific context.



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Finding confirmation bias in famous experiments – the Robert Millikan edition

In the NYT, political scientist Michael Suk-Young Chwe recalls his Caltech physics professor showing students Robert Millikan’s lab notes from his famous oil-drop experiments that established the electrical charge of the electron:

“The notebooks showed many fits and starts and many “results” that were obviously wrong, but as they progressed, the results got cleaner, and Millikan could not help but include comments such as “Best yet — Beauty — Publish.” In other words, Millikan excluded the data that seemed erroneous and included data that he liked, embracing his own confirmation bias.”

He also suggests – less credibly – that science take a lesson from literary criticism, a field that – in his view – has “real standards of scholarly validity.”

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