Home
Contents
New work mindset at Snowflake❄️
Published 2022-04-27
Tags: #life-reflection
This writing is a collection of commitments and mindsets to ensure that my next adventure at Snowflake❄️ will be a productive and fulfilling one.
But first, let’s start with a one-liner answer for whenever I ask myself “what am I doing right now?”. Putting this at the top for self-reminder.
“You are in a 4-year PhD program to be an expert in data privacy; consume and produce artifacts whose scope extends beyond your local organization, and whose lifespan extends beyond your tenure.”
In the rest of this writing I’ll discuss the following:
- Meaningfulness: How data privacy fits within my truth core value
- Fun: Data privacy is a fun and practical field to dive into
- Ambition: I will be an expert in the field
- Jedi mind tricks to cover past motivation-draining thoughts
(Note: This post is just one part of the Google-to-Snowflake series. Other posts: 1. Why quit Google 2. Interview tips 3. How I spend my time 4. New work mindset at Snowflake)
Data privacy is meaningful
Data privacy is a meaningful field to dive into; it ties into my truth core value. Brief rationalization: Data privacy is a key challenge in the way of open data sharing of human data (If we’re talking about data about planets, we won’t be needing to talk about privacy hah!), and you need data to produce useful truths. Here is a relevant quote from Wood, et al., 2018 on the importance of human-related datasets.
- .. the types of information disclosures enabled in John’s opt-out scenario often result in individual and societal benefits. For example, the discovery of a causal relationship between red wine consumption and elevated cancer risk can lead to new public health recommendations, support future scientific research, and inform John about possible changes he could make in his habits that would likely have positive effects on his health. Similarly, the publication of public school teacher salaries may be seen as playing a critical role in transparency and public policy, as it can help communities make informed decisions regarding appropriate salaries for their public employees. … For example, one of the longest running longitudinal studies, the Framingham Heart Study, precipitated the discovery of risk factors for heart disease and many other groundbreaking advances in cardiovascular research.
Data privacy is fun
Data privacy is just a fun field to be an expert in. This field has challenges that satisfy my definition of fun — it has a nice balance between having open foundational research topics (heck we don’t even know if approximate differential privacy will be the privacy standard to settle on), while also requiring some more implementation work (Ch 4) to make those ideas be generally useful. And on a more practical note, I will get to accrue many transferrable skills, since any FAANG company has a data privacy team.
- Ambition: Be an expert. Be an expert at data privacy (the field, not just the team). You are in a 4-year PhD program to be an expert in data privacy; consume and produce artifacts whose scope extends beyond your local organization, and whose lifespan extends beyond your tenure.
- Consume foundational information related to data privacy: Learn about the history, the core results, and brainstorm around the open questions.
- Produce. Extend your impact beyond your org. Play with ideas in the field, brainstorm and create novel artifacts. Translate research into practice. Create consumer-facing products.
- Focus. On time spending — make sure that the side projects are within the field. (In the past, my side projects have always been totally unrelated to my main work, and I suspect that’s draining my motivation for my main work). On new opportunities — be very picky. Check: Does this energize me? If not, can I reframe it into something that ties to my values? If not, decline. Be very careful about “opportunities” that are purely for career growth, but don’t help me become an expert.
Jedi mind tricks
Here are some jedi mind tricks to cover motivation-draining thoughts I had in the past (and will no doubt resurface during my adventure). All the non-bolded texts are quotes from Nate Soares (References below).
On goal uncertainty: Deliberate well once. Only re-deliberate if new major info. It’s optimal to dive in w/ partial info.
- Deliberate well once, and then don’t deliberate again until you come across new information that would have changed your answer.
- It’s ok to change goals. Humans are well — known for their ability to start out pursuing one goal , only to find that goal shift drastically beneath them as their knowledge of the world increases .
- Operating under uncertainty is the norm, not the exception. No matter how hard you deliberate, your deliberation procedure is going to be flawed and biased, and there are going to be considerations you’re missing and evidence you failed to take into account.
- It’s ok to not be 100% clear. You don’t get to know exactly what you’re fighting for , but the world’s in bad enough shape that you don’t need to .
- When you’ve committed yourself to a new action, and you start wondering whether you’re really doing the right thing, the relevant question is not “were my thoughts when I chose this action perfectly unbiased?” Nor is it “did I find literally the best available action?” No, the relevant question is, “am I in a better position now to pick a good action than I was then?”, or alternatively, “could I do a significantly better job picking an action this time around than I did last time around, enough so to make up for the opportunity cost of deliberating again?”
- It’s important to possess a minimal level of ability to update in the face of evidence, and to actually change your mind. But by far the most important thing is to just dive in.
- Optimality includes reachability. “And the best action you can find is exactly what it sounds like — the best action you’re able to find.”
- “In my experience, the way you end up doing good in the world has very little to do with how good your initial plan was. Most of your outcome will depend on luck, timing, and your ability to actually get out of your own way and start somewhere. The way to end up with a good plan is not to start with a good plan, it’s to start with some plan, and then slam that plan against reality until reality hands you a better plan.”
On the distance between action and goal
- Care vs feelings. It’s possible to both lack deep feelings of affection for strangers and still care for them nearly as much as you care for friends . To me , the feelings look like they are arbitrary remnants of the tribal days , while the aesthetics look like they are echoes of my deeper values . I know which one I’m more loyal to .
- If you want to solve hard problems , stop trying to solve the hard problem directly . Change the context such that that’s a background assumption : all your actions are going to be pointed roughly in the direction of solving — the — problem ; what next ? What’s the next thing that needs doing ? Work on that .
- e.g. Actually trying to run MIRI feels very different from the inside . It doesn’t feel like trying to make an institute run , it feels like trying to get all the most important emails handled while not letting administrative duties suck up my day . It feels like struggling to prioritize three important tasks that can’t all be done .
It’s ok to brainwash yourself
- I’ve found that certain beliefs — beliefs which I know are wrong — can make me more productive. (On a related note, remember that religious organizations are generally more coordinated than rationalist groups.)
- It turns out that, under these false beliefs, I can tap into motivational reserves that are otherwise unavailable. The only problem is, I know that these beliefs are downright false.
- See, I am convinced that building a friendly AI is the most important problem for me to be working on, even though there is a very real chance that MIRI’s research won’t turn out to be crucial. Perhaps other existential risks will get to us first.
On deciding to work “harder”.
- Working yourself ragged is not a virtue . You don’t get extra points for effort . In fact , you lose points for effort : effort is costly ;
- The goal is not to appear to be working hard , the goal is to improve the world .
Next
I will be re-reading this writing whenever I need that motivational boost, but I still have more self-reflection to do; I have to think hard about more concrete goals that align with the restrictions above. I’m going to wait until my first month at work so I can pick ones that are aligned with my actual professional responsibilities. **Not going to blog on this, however, so this should be the final post in the google-to-snowflake saga, thank you for following along!
More readings. If you like Nate Soares’ writings, here are the references I used for the quotes, I highly recommend that you check them out!
Comment via: medium