Taking a few minutes to talk to a rubber duck, or other inanimate object, can help you decide on a job or make other big decisions.
When trying to decide whether to take a job (or leave a job), the decision can be difficult. There are lots of conflicting ideas and it can be hard to sort out. You can try a pro and cons list, envisioning each option or other methods. You should also talk to a duck.
In programming there’s a technique referred to as rubber duck debugging. Sometimes as a programmer trying to debug your code you get so lost in trying to keep every detail together that you can’t see the trees for the forest. You miss small, but important details that will unlock the solution. The talk to the duck technique has you explain the code line by line to a rubber duck. It’s not that you expect the duck to give you an answer (and if it does, seek medical help right away), rather it forces you to go through the code line by line, detail by detail. Many people report that shortly after starting to explain the process the answer to the problem hits them.
It doesn’t just work for software debugging; you can use this for many types of problems. The key is that you need to explain it, step by step, as if to a novice. That’s what’s forcing you to look at each piece for a clue or insight to the larger problem.
You don’t have to use a duck; a teddy bear or other inanimate object works just as well. You can also use a friend, but here’s where it can get tricky. The upside of a friend is that she can push you to explore further, or help you discover new questions to consider. The downside of a friend is that she can push you to the wrong questions. The right balance can be tricky. If you are the friend, you can raise the issues, but only the job seeker can determine the importance of each question.
A variant of this is to use AI instead of a friend. This is a hybrid between a person and a duck. On the one hand, it can give you a more of a response than the duck. On the other hand, people often oversubscribe correctness and other attributes of wisdom to AI generated answers. Kabir, Samia & Udo-Imeh, David & Kou, Bonan & Zhang, Tianyi. (2024). Is Stack Overflow Obsolete? An Empirical Study of the Characteristics of ChatGPT Answers to Stack Overflow Questions. 1-17. 10.1145/3613904.3642596. showed that while 52% of ChatGPT answers contain incorrect information and 77% are verbose, study participants still “preferred ChatGPT answers 35% of the time due to their comprehensiveness and well-articulated language style,” and further, “overlooked the misinformation in the ChatGPT answers 39% of the time.” As LLMs improve in competency and style these numbers may go up. Put another way, people are likely to put too much trust in hallucinating LLMs; caveat prompter.
Regardless of your duck preference, consider this the next time you have a career decision, or any major decision. It may seem not that different from thinking through it in your mind, but the act of verbalizing the myriad of information to a “novice” (someone who is coming at the problem for the first time) will help slow down your racing mind and help you see both the forest and the trees that make it up.
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