Novum Organum: The original “How To Not Be Wrong”

When I visited with Alan Kay and Bonnie MacBird in June, one of the ideas that he got me thinking about was Sir Francis Bacon’s Novum Organum (1620, wikipedia link), for ‘new instrument of science.’ Bacon understood human tendencies for bias long before behavioral economics. His book was the prototype for the modern popular book “How to Not Be Wrong: The Power of Mathematical Thinking” which advocates for mathematics as an approach to addressing human biases and limitations.

Bacon aimed to construct a foundation for real science, a body of knowledge that we could trust despite the fact that our minds are weak and that we are easily swayed. He lists four “idols” — the biases which keep us from thinking objectively and scientifically. Wikipedia has a short description for each. A couple that I found particularly striking:

• Idols of the tribe: The things we get wrong because we like to see things at human scale and in regular structures. I read these as including the ideas we like because everyone else likes them, like picking a programming language because it’s popular and not because it suits the task.
• Idols of the cave: The things we get wrong because of our unique education and background. Bias due to privilege (and assuming that everyone else has the same privilege) seem to fall in here.
• Idols of the market: I just kept thinking “computational thinking” here. Idols of the market include words “which spring from fallacious theories” and “that are the result of imprecise abstraction.”  Unsupported theories of transfer and terms which we can’t actually define and test are part of Bacon’s warnings about “the market.”

I haven’t read the whole document — it’s available on Project Gutenberg, but it’s tough going.  I have found that Bacon talks about issues not in the Wikipedia article that are are significant today. For example, Bacon decries making decisions based on too “few experiments” which is explicitly a concern addressed in the efforts to replicate prior results (e.g., article here).

I keep thinking about what Bacon would say about computing education research. CER has some deep research questions it’s pondering (which I plan to address in some future blog posts). How do we make sure that we’re doing Science and not just following our Baconian idols?