- Tue Jan 01, 2019 11:12 am
#25954
Short question:
Can numbers (the Look then Leap Rule OR the Gittins Index) be used to help a person decide when to stop looking for the most suitable career path and LEAP into it instead or is the career situation too complicated for that?
^^^^^^^^^^^^^^^^^
Details:
Mathematical answers to the question of optimal stopping in general (When you should stop looking and leap)?
Gittins Index , Feynman's restaurant problem (not discussed in details)
Look then Leap Rule (secretary problem, fiancé problem): (√n , n/e , 37%)
How do apply this rule to career choice?
1- Potential ways of application:
A- n is Time .
Like what Michael Trick did https://goo.gl/9hSJT1 . Michael Trick A CMU Operations Research professor who applied this to his decide the best time for his marriage proposal., though he seems to think that this is a failed approach.
In our case, should we do it by age 20-70= 50 years --- 38 years old is where you stop looking for example? Or Should we multiply 37% by 80,000 hours to get a total of 29600 hours of career "looking"?
B- n is the number of available options. Like the secretary problem.
If we have 100 viable job options, we just look into the first 37? If we have 10, we just look into the first 4? If we are still in a stage of our lives where we have thousands of career paths?
2- Why the situation is more complicated in the career choice situation:
A- You can want a career and pursue it and then fail at it.
B- You can mix career paths. If you take option c, it can help you later on with option G. for example, if I went as an IRS, the irs will help me later on if I decide to become a writer so there's overlap between the options and a more dynamic relationship. Also the option you choose in selection #1 will influence the likelihood of choosing other options in Selection 2 (For example, if in 2018 I choose to work at an NGO, that will influence my options if I want to do a career transition in 2023 since that will limit my possibility of entering the corporate world in 2023).
C- You need to be making money so "looking" that does not generate money is seriously costly.
D- The choice is neither strictly sequential nor strictly simultaneous.
E- Looking and leaping alternates over a lifetime not like the example where you keep looking then leap once.
Is there a practical way to measure how the probability of switching back and forth between our career options affects the optimal exploration percentage?
F- There is something between looking and leaping, which is testing the waters. Let me explain. "Looking" here doesn't just mean "thinking" or "self-reflection" without action. It could also mean trying out a field to see if you're suited for it. So we can divide looking into "experimentation looking" and "thinking looking". And what separates looking from leaping is commitment and being settled. There's a trial period.
How does this affect our job/career options example since we can theoretically "look" at all 100 viable job positions without having to formally reject the position? Or does this rule apply to scenarios where looking entails commitment?
G- * You can return to a career that you rejected in the past. Once you leap, you can look again.
"But if you have the option to go back, say by apologizing to the first applicant and begging them to come work with you, and you have a 50% chance of your apology being accepted, then the optimal explore percentage rises all the way to 61%." https://80000hours.org/podcast/episodes ... o-live-by/
*3- A Real-life Example:
Here are some of my major potential career paths:
1- Behavioural Change Communications Company 2- Soft-Skills Training Company, 3- Consulting Company, 4-Blogger 5- Internet Research Specialist 6- Academic 7- Writer (Malcolm Gladwell Style; Popularization of psychology) 8- NGOs
As you can see the options here overlap to a great degree. So with these options, should I just say "ok the root of 8 is about 3" so pick 3 of those and try them for a year each and then stick with whatever comes next and is better?!!
Note: I started a discussion on the topic on ResearchGate here
https://www.researchgate.net/post/Maths ... emn_n_e_37
…. It would be great if you added your thoughts on the issue. You can reply on the Research Gate Discussion directly if you have an account or you can reply here and I can quote you there. If you wish not to be quoted, please let me know.
Can numbers (the Look then Leap Rule OR the Gittins Index) be used to help a person decide when to stop looking for the most suitable career path and LEAP into it instead or is the career situation too complicated for that?
^^^^^^^^^^^^^^^^^
Details:
Mathematical answers to the question of optimal stopping in general (When you should stop looking and leap)?
Gittins Index , Feynman's restaurant problem (not discussed in details)
Look then Leap Rule (secretary problem, fiancé problem): (√n , n/e , 37%)
How do apply this rule to career choice?
1- Potential ways of application:
A- n is Time .
Like what Michael Trick did https://goo.gl/9hSJT1 . Michael Trick A CMU Operations Research professor who applied this to his decide the best time for his marriage proposal., though he seems to think that this is a failed approach.
In our case, should we do it by age 20-70= 50 years --- 38 years old is where you stop looking for example? Or Should we multiply 37% by 80,000 hours to get a total of 29600 hours of career "looking"?
B- n is the number of available options. Like the secretary problem.
If we have 100 viable job options, we just look into the first 37? If we have 10, we just look into the first 4? If we are still in a stage of our lives where we have thousands of career paths?
2- Why the situation is more complicated in the career choice situation:
A- You can want a career and pursue it and then fail at it.
B- You can mix career paths. If you take option c, it can help you later on with option G. for example, if I went as an IRS, the irs will help me later on if I decide to become a writer so there's overlap between the options and a more dynamic relationship. Also the option you choose in selection #1 will influence the likelihood of choosing other options in Selection 2 (For example, if in 2018 I choose to work at an NGO, that will influence my options if I want to do a career transition in 2023 since that will limit my possibility of entering the corporate world in 2023).
C- You need to be making money so "looking" that does not generate money is seriously costly.
D- The choice is neither strictly sequential nor strictly simultaneous.
E- Looking and leaping alternates over a lifetime not like the example where you keep looking then leap once.
Is there a practical way to measure how the probability of switching back and forth between our career options affects the optimal exploration percentage?
F- There is something between looking and leaping, which is testing the waters. Let me explain. "Looking" here doesn't just mean "thinking" or "self-reflection" without action. It could also mean trying out a field to see if you're suited for it. So we can divide looking into "experimentation looking" and "thinking looking". And what separates looking from leaping is commitment and being settled. There's a trial period.
How does this affect our job/career options example since we can theoretically "look" at all 100 viable job positions without having to formally reject the position? Or does this rule apply to scenarios where looking entails commitment?
G- * You can return to a career that you rejected in the past. Once you leap, you can look again.
"But if you have the option to go back, say by apologizing to the first applicant and begging them to come work with you, and you have a 50% chance of your apology being accepted, then the optimal explore percentage rises all the way to 61%." https://80000hours.org/podcast/episodes ... o-live-by/
*3- A Real-life Example:
Here are some of my major potential career paths:
1- Behavioural Change Communications Company 2- Soft-Skills Training Company, 3- Consulting Company, 4-Blogger 5- Internet Research Specialist 6- Academic 7- Writer (Malcolm Gladwell Style; Popularization of psychology) 8- NGOs
As you can see the options here overlap to a great degree. So with these options, should I just say "ok the root of 8 is about 3" so pick 3 of those and try them for a year each and then stick with whatever comes next and is better?!!
Note: I started a discussion on the topic on ResearchGate here
https://www.researchgate.net/post/Maths ... emn_n_e_37
…. It would be great if you added your thoughts on the issue. You can reply on the Research Gate Discussion directly if you have an account or you can reply here and I can quote you there. If you wish not to be quoted, please let me know.
- By AaronBurns
- By Uolevi Kattun