Asking the right questions

Have you ever had someone tell you: “Oh. That’s a good question.”

If you haven’t, you  should try it. It is quite nice. But which of these do you  think are good questions?

1.”What does this button do?”

If your response to number 1 is to push the button, you might be about to have a bad day. But, if you are honestly asking that question to an expert on the operation of said button, it is the best question to be asking. This is the truth behind the statement from Newton – “If I have seen farther it is because I have stood on the shoulders of giants.” Ask a subject matter expert, good question. Follow this question up with questions like “what should I see when I push this button?” and “What do I do if I don’t see that?”

2. “Does this <thing I am doing> even matter?”

This value based, pragmatic, critical thinking question is at the heart of all good questions. It helps keep you motivated if the answer is yes and if the answer is no, it helps you spend your time more wisely. Good question. Keep asking, ‘Is this important to me personally or professionally?” or “Is this important to some stakeholder in the <thing I am doing>?” This could be your wife, employer, etc.

Cost and benefit or risk and reward analysis is also super important in analysis. In science, statistics and data analysis one can usually come up with a new angle or question to ask of the data or continue trying to squeeze every ounce of precision available to you. For some data sets this matters. Let’s say that there are relatively straightforward means to be 90% confident in the insight from some data.  If you want 99%, it is going to take 10-100x more effort to worry about that last little bit. A good question asks, “is it worth it?” If you see my earlier post about shopping for a vacuum cleaner, it was worth it in that case. 

3.”When did you stop beating your wife?”

This is a classic example of a leading question. It may serve its purpose in interrogation or parenting, but it is devastating in data analysis or decision making. If you want honest inquiry into a subject, you have to work very hard to combat biases. This is really challenging, part of a scientific mindset is to hypothesize first. Make a guess and check that it works. But that mindset very easily leads to confirmation bias if one is not careful to follow it up with the next question.

4.”What are the chances I could be wrong?”

Great question. The answer is non-zero. Failure is always an option. But glorious ‘failure’ that leads to new insight, inventions and to the right answer eventually. But this is the philosophical success of Bayesian reasoning, my confidence can approach but never reach 100%. The trouble is, this mindset needs to be practiced rigorously. It is much more natural to round off likely-hoods and think in terms of 0%,50% or 100% and no nuance in between. 

5.”What is the tallest mountain in Europe?”

This kind of academic or quiz question has its place in the classroom where subject matter expertise needs to be assessed. Even in a classroom setting, this kind of question doesn’t promote creativity or honest inquiry about a subject. But in a professional setting, there is also a kind of question that a person might ask that they know the answer to and they are asking because they want to show off. Furthermore, instead of just making a comment, they ask in such a way as to make the speaker squirm. For my money, this is the worst kind of question.

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