Spotting The Wolf From The Sheep

2 min read

If you have been in any industry long enough, one thing becomes clear. There are three main types of people in this world, the ones who are smart and resilient, the ones who are not but nevertheless try to appear as they are, and finally the ones who are not but do not try to show otherwise.

This does not only apply to the workplace but life in general. The key question is how can you spot the smart ones in a group? There are many different reasons for which you might want to do so. Looking at the problem-question from a business-oriented point of view, knowing the identity of the wolf from the beginning can help you choose team members more efficiently.

The three-steps technique I am going to introduce is simple and quick. The best thing about it is that it can be applied to any environment and it requires a minimal amount of effort and time.

Image this, you are taking place at a Hackathon and you have been asked to select a team. You are not familiar with anyone in the room and you must choose the best possible teammate. Who do you choose?

Assuming that you are in front of a pool of candidates, you should ask them a question. This question should be the easiest question that comes to your mind and is related to the theme of the project. Let’s say for example that you are trying to make a Machine Learning application. An initial question would be “What is the difference between supervised and unsupervised learning?”. Having watched a 3 minutes video explaining what machine learning is would be enough for you to know the answer to this question. A large chunk of people, most probably the majority will frantically try to give you the answer, possibly trying to speak over their peers e.t.c. it is crucial that you try and recognize who was part of that group and who wasn’t.

The next phase of the technique requires that you make a follow-up question. Now this question should not be difficult yet. An example follow up question to our initial example would be “What are three commonly used performance metrics in machine learning projects?”. Once again, the majority, including more people than before will immediately try giving you the answer. They might try to speak as loud as possible, make certain gestures to get your attention e.t.c. You get the point.

It is now time for the third and final phase. Think of the most difficult question possible. This question could even be completely irrelevant to the two previous ones. For example “Derive and implement from scratch Parallel Sampling of HDPs using Sub-Clusters Splits orally”. The question should be such where you are certain that no one knows the answer to it. The same group of people who so eagerly tried to answer your previous questions will now be completely silent. The ones who didn’t though will most probably be the ones who talk. They will most probably not know the answer. Yet, they will try to tackle it from different points of view. Another possibility would be to make questions and try to break down your request to smaller parts so they attempt to first understand it and then bring results.

Congratulations! You have now found the members of your team.

Behind the scenes

Why is this a productive way to spot the wolf you may ask? From the first two questions, you successfully managed to split the herd into two camps. The overeager responders who would do anything to be recognized and would completely disregard due process and factual analysis before reaching a conclusion, and the calculating, patient and with foresight wolves. The wolf will most certainly understand that something is not right.

The first question’s simplicity will make the wolf suspicious of the intentions of the person making it. The sheep on the other hand will not think critically and simply run for the win. The second question will make the wolf understand that this is indeed a trap and a tough question is on the horizon. The sheep, lacking critical thinking, or in reality, disregarding it, will not suspect a thing.

Once the final question hits, the wolf will try to calmly dismantle the question to its parts and according to the phrasing will try to approach the question in the way he/she finds optimal. The sheep will prefer to hide among their peers and become one with the herd, thinking that their inability to respond will go unnoticed.

This article is not only meant to help you detect the wolf, but also become one. Think critically and try imagining that you are in this situation. What are your next moves?

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Filippos Dounis I'm a 16 year-old student freelancer. I have been programming for seven years now and I specialize in Machine Learning. The majority of my research revolves around machine learning models in economics, finance, and medicine.

2 Replies to “Spotting The Wolf From The Sheep”

  1. Pretty sure I read this article already by another author, few weeks back. You gonna give him credit? This is practically beat for beat identical.

    1. Hey Robert! Thanks for taking the time and reading my article to the end. Unfortunately, I can not give credit to any author as I have not read (and obviously copied) any similar material. The technique mentioned above is no secret. In fact, it is known to almost every organizational psychologist that specializes in HR. Personally, I learned this method by the lead software architect of Nokia once I was interning there. With that being said, it is quite possible for many people to have previously spoken about similar approaches in “finding the wolves”.

      I thank you for your healthy criticism and invite you to read more of my work both here and on Medium.

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