I’m still sceptical about your plan on pursuing two very different careers in parallel. It’s not an issue if EtG is important to you but I’m not seeing what justifies doing two in parallel? Why is it better than one person doing EtG and another doing CS?
On the original question, I think it’s very difficult to tell from the outside. You want to do projects to gain experience that lets you enter certain roles (e.g. entry AI safety roles). The people hiring for such roles are the ones who can tell what they are looking for and how people usually get there.
The strategy of doing in parallel is: To attend dental school, but spending much less time on dental school than other students, getting like 2.5 GPA, just aim to pass and graduate in dental school. (In Taiwan, it’s really feasible. Our dental school training is NOT rigid. In fact every time I went to dentist I always think maybe this dentist doesn’t work hard in school)
Imagine: All of the students in dental would know there’s a weird guy called Jack that is studying AI every day and never studies dental school seriously
Once you graduate in dental school, you can get the dental license at any time(even 10 years later) if you passed the exam. Therefore, for me after I graduated from dental school, if I later found myself better at EtG and not direct work, then I can self study dentistry again for years, pass the licence exam and start practicing.
You may ask: Why don’t you study CS first, if 10 years later I found out myself isn’t good enough in direct working, then I apply to dental school? Because I expect dental school would be much harder to apply in the future(which could be nearly impossible to apply)
I’m not saying I’m def nitely going to do this( the probability is around 35%), as I said with you in private messages, I’ll test my personal fit for 2 years first. If I found myself bad at CS, then research mentorship wouldn’t matter at all Because I won’t do CS research in parallel. But if after 2 years I found myself seem to be good at direct work, but not confident then it seems it’s the best plan)
I meant that if EtG is important to you, then why not just go all in on EtG? You might say that AI-related career advice assigns higher priority to research, but I think that assumes you only pick one of these and not split your attention. I think 80k would encourage focusing on EtG if it is important to you for some reason:
Overall, earning to give typically ends up seeming most attractive in the following cases: … There’s a particular job you really want to do for other reasons that’s higher-earning than average, or that can be adapted into. This might look like Jeff working as a software engineer, or someone who really always wanted to be a doctor, or a teacher who does private tutoring and donates the extra. …
I think I’d only encourage seriously doing two of these in parallel if both are important to you for some reason other than impact.
How do you expect to spread your effort across the two? What major sacrifices are you making (e.g., not attend a CS degree, work +N hours a week compared to average) that enable this, and what is your estimate on how it impacts your productivity in the long run?
Not attending CS degree isn’t a sacrifice. Self-learning is very sufficient, the only thing I need from school is research mentorship.
It’s a bit complicated to explain, but doing these two in parallel does NOT reduce productivity at all. If you’re interested at why I could explain in the future
I’m still sceptical about your plan on pursuing two very different careers in parallel. It’s not an issue if EtG is important to you but I’m not seeing what justifies doing two in parallel? Why is it better than one person doing EtG and another doing CS?
On the original question, I think it’s very difficult to tell from the outside. You want to do projects to gain experience that lets you enter certain roles (e.g. entry AI safety roles). The people hiring for such roles are the ones who can tell what they are looking for and how people usually get there.
Hello Peter:
The strategy of doing in parallel is: To attend dental school, but spending much less time on dental school than other students, getting like 2.5 GPA, just aim to pass and graduate in dental school. (In Taiwan, it’s really feasible. Our dental school training is NOT rigid. In fact every time I went to dentist I always think maybe this dentist doesn’t work hard in school)
Imagine: All of the students in dental would know there’s a weird guy called Jack that is studying AI every day and never studies dental school seriously
Once you graduate in dental school, you can get the dental license at any time(even 10 years later) if you passed the exam. Therefore, for me after I graduated from dental school, if I later found myself better at EtG and not direct work, then I can self study dentistry again for years, pass the licence exam and start practicing.
You may ask: Why don’t you study CS first, if 10 years later I found out myself isn’t good enough in direct working, then I apply to dental school? Because I expect dental school would be much harder to apply in the future(which could be nearly impossible to apply)
I’m not saying I’m def nitely going to do this( the probability is around 35%), as I said with you in private messages, I’ll test my personal fit for 2 years first. If I found myself bad at CS, then research mentorship wouldn’t matter at all Because I won’t do CS research in parallel. But if after 2 years I found myself seem to be good at direct work, but not confident then it seems it’s the best plan)
I meant that if EtG is important to you, then why not just go all in on EtG? You might say that AI-related career advice assigns higher priority to research, but I think that assumes you only pick one of these and not split your attention. I think 80k would encourage focusing on EtG if it is important to you for some reason:
I think I’d only encourage seriously doing two of these in parallel if both are important to you for some reason other than impact.
How do you expect to spread your effort across the two? What major sacrifices are you making (e.g., not attend a CS degree, work +N hours a week compared to average) that enable this, and what is your estimate on how it impacts your productivity in the long run?
Not attending CS degree isn’t a sacrifice. Self-learning is very sufficient, the only thing I need from school is research mentorship.
It’s a bit complicated to explain, but doing these two in parallel does NOT reduce productivity at all. If you’re interested at why I could explain in the future