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Advice: Oct 2021

I’m currently applying to graduate school, which has given me ample time to reflect upon my experiences and aspirations for the future. Doing so has made me think about what I would have wanted to know as an 18 year old, or even earlier. Twitter is filled with ambitious 17 year olds from Canada with websites, accomplishments, and followers. I’m somewhat unsure that this is something to strive towards as a teenager but nontheless it has made me think about whether I could have done this in another life. Growing up, I always learned from example. Behaviors, thought patterns, habits were easy to replicate for me. I read a lot of Medium blogs and wrote down lists upon lists of cringy advice. I also read many pop psychology books from people like Simon Sinek and Cal Newport. I generally looked up to my parents, coaches, and teachers and carefully followed their advice and way of doing things for the most part. Intellectually however, it was harder to develop the certain edginess necessary to motivate myself to the same extent that I have now.

In other words, I didn’t really know what I was doing career wise. Ignorance is bliss but I still remember being a little frustrated that I was wasting my time, and in these moments, the YouTube videos of a certain disgraced pharmaceutical executive were quite centering and were an important outlet for advice and drive. Unfortunately, there were times where I’d watch intro chemistry lectures during class instead of living in the moment. I’d have much preferred a mentor couple years older with the recency to provide meaningful advice.

I’m always interested in how peoples thinking changes over time. For posterity, below are some notes that I think would have been useful to me during my high school college transition, mostly regarding how to learn.

  1. There is a reason for everything. If something seems outrageous either to you or to others, it is important to figure out why and hear both sides. This helps you adjust your mental models and learn new things. Don’t ignore the emotional aspect of wanting to prove people wrong and take the intellectual highground. Motivation comes in all forms :/
  2. Somewhat related, staking your reputation on something being true or an area being interesting gives whatever is being said more credibility. However, be careful of situations where there is a cultural or narrative shift towards a new concept. It is easy to be a sheep in a herd, but much harder to think independently. Be skeptical of when large numbers of people agree, unless each of them individually has a reputation for being an independent thinker. Independence in thought can be bad amongst those that disagree with hard facts, but rising above this level when a certain level of intellectual is reached, independence of thought is both refreshing and in many instances more credible than herd thought. Lots of examples on Twitter here.
  3. Biology must generate ideas as well as data. Take courses in biology and develop mental models for how things work instead of trying to memorize data. Don’t get swept into the hype about applications of math, machine learning, and statistics without consideration of the principles behind them. Experimental error and in general lack of understanding of everything that is going on in an experiment really hampers any statistical analysis in many areas even when careful controls are implemented. The internet has made fields like AI seem incredibly excitng and new, of course some advances are. Remember, some questions are simply hard and while it may be worthwhile to try throwing AI at the problem, the pretest probability of it working is already low. Hard problems are hard. To solve them, you need to think.
  4. Translation doesn’t happen when you put a gun to the head of a young person and say “go translate”. It happens when you finally understand something well enough that you know what you can now do.. Each company is an experiment where entrepreneurs take the risk of testing whether the current cutting edge is robust enough to be commercialized. Not all startups are good or addressing a problem worth your time.
  5. There are different ways to accomplish your goals, but the important thing is to take responsibility, focus, and win. It usually isn’t a bad thing to optimize for exposure to new ideas but some day you need to sit down and decide what your trade will be. Textbooks aren’t a bad way to intake information quickly, and books are always an incredible investment. Lectures from top sciences are freely available online. Read as many papers as possible. Read/listen to the stories of great scientists and inventors (First Rounders, The Long Run, LifeSciVC, etc). Find people you admire and beat them. Being good at science is about winning. There is always the opportunity to win, find the motivation to make it happen.
  6. Classes are useful for a very specific type of learning. I find it difficult to learn when many others are trying to learn the same thing or when learning is done in groups, especially when there are grading implications. I think as a general principle, you need to have a consistent ability to develop your own theses as well as critically evaluate ideas. At its core, learning isn’t hard, the hard part is the dedication to continue and to actually sit down and do the work. Grades are a great motivator to do this, so many students are generally competent. In order to differentiate students, exams are designed to go above and beyond the key concepts that are the real valuable learning objectives from a course. Grading is thus based upon anciliary information that lacks application or is easily looked up. Try to skip as much school as possible.

My current goals are to become more knowledgeable about science and medicine and eventually start doing science that is meaningful in the fullness of time. Hopefully this advice still holds some water when we revisit in several years.