Harsh Feedback Tools
Pushing Yourself
My gym attendance used to be patchy a few months ago - around three workouts a week. Then, I started working out with a friend. He urged me to start coming every day. I suddenly felt a level change in my workout intensity and my drive to keep myself fit. I hit the gym nearly every day without fail.
A month later, though, my gym buddy had to go out of town for a fortnight. And the moment he told me that, I knew I was going to miss the gym. It’s like the lazy part of my mind saw an opening. And yes, I came down with the cold and went only three times in those fifteen days.
What happened there?
Another time I noticed spikes and drops in motivation was in writing. I noticed that I kept procrastinating on actually writing about the “great ideas” I had come across, so I set up an agreement with a friend saying that we would write an essay every single day. And lo, we both wrote an essay nearly every single day for two months on end! This was after months and years of nothing.
However, we took a break after a while, and never really got back on track. I published basically nothing for a year after that. Also, we tried doing it again for a week and yet again I found myself writing like I was possessed.
What had happened?
I don’t think it’s just that I made a commitment to another person and would lose face if I bailed. This explains the writing example. But, there’s also the fact that you look at a person who’s performing better and you think “I can do that too!”. Daniel Coyle in The Talent Code calls this Ignition.
More importantly, why can’t I seem to do it on my own? If committing to writing an essay every day is so powerful, why don’t I just do that by myself?
There’s nothing to keep me honest, I fear. I’m not forced to push past my boundaries, push past my fears, and do the best I can.
PG put it superbly:
Just as inviting people over forces you to clean up your apartment, writing something that other people will read forces you to think well. So it does matter to have an audience. The things I’ve written just for myself are no good. They tend to peter out. When I run into difficulties, I find I conclude with a few vague questions and then drift off to get a cup of tea.
– Paul Graham, The Age of the Essay
So, I don’t push myself far enough when I’m just on my own. I worked out at less than maximum intensity in the gym (and skipped it often) and I didn’t write truly scary essays when writing for myself.
Stone-Cold Feedback
I suspect it’s because I don’t have a cold, harsh empirical measure when I’m doing stuff on my own. I’m free to convince myself that I’ve done “enough”. Sometimes, I don’t do anything at all, thinking that things are good as they are. Other times, I let myself off with sloppy work. Which is fairly inexcusable if you’re a writer or thinker because the best work probably lies in areas where you’re uncomfortable.
PG again:
Perhaps the most important reason to release early, though, is that it makes you work harder. When you’re working on something that isn’t released, problems are intriguing. In something that’s out there, problems are alarming. There is a lot more urgency once you release. And I think that’s precisely why people put it off. They know they’ll have to work a lot harder once they do.
– Paul Graham, The Hardest Lessons for Startups to Learn
A harsh empirical measure forces you to “release” your product. When there’s another person waiting to read your essay, you can’t just tell yourself that the mess of meandering paragraphs you’ve written is a good enough essay. You have to clean it up - how can you let them see such crap? And therein lies most of the work - and profit - of writing.
Similarly, when there’s a guy next to you lifting hard on every set, and getting more ripped by the day, you can’t just go in there and do a couple of easy exercises and tell yourself you’re “doing your best”. You have to lift hard too.
This empirical measure doesn’t have to be a human being. But it can’t just be any measure of your progress. It must have the power to move you.
Then, that’s the core of our problem. What things have the power to move you? Wanting to not lose face is one, as we’ve seen above. PG suggests that this plays a heavy role even at the level of startups.
One of the most interesting things we’ve discovered from working on Y Combinator is that founders are more motivated by the fear of looking bad than by the hope of getting millions of dollars. So if you want to get millions of dollars, put yourself in a position where failure will be public and humiliating.
– Paul Graham, How Not to Die
We don’t want to go the extra mile because it’s hard work. No, it’s more than just hard work, I think. It’s uncomfortable.
Harsh Taskmaster
Your empirical measure should be more than just a measure. It should set a high standard. Having my essay read by others make me work much harder than something I write offline. I want them to see a good essay (and think well of me).
However, I must care about its judgment of success or failure.
A computer is a great harsh, empirical taskmaster. You cannot get your program to do what you want unless you write it exactly the way the programming language needs you to.
Games are fabulously harsh taskmasters. You can’t get to the next stage unless you beat up the monsters on this level. There’s no other way. Jane McGonigal writes about how gamers learn through repeated failure… and love it! Games implement fun failure - where you feel a sense of power and agency even when you fail, so that you say “I’m going to get you next time” instead of “I’m going to give up”.
Specific Problems
On what specific problems do I want to push myself harder?
I want to push myself in the area of fitness. I want to actually lift weights regularly and actually do cardio everyday.
I want to push myself in writing. I want to release my essays - make them good enough to present to others. Which is just a proxy for laying out clear, self-contained, evidence-backed reasoning for my ideas and working out all their implications.
I want to push myself in learning the scientific method. I want to make myself actually take up hard problems and try to solve them and fail and learn from my failures and try again till I get a method that actually works. When I’m working on my own, I just take up toy problems and only work on them till I’m bored or tired. I don’t tie up the loose ends and review them to polish my methods. I can’t present my “scientific method” to someone else right now. It’s not powerful enough to convince anybody. My aim is to get a model of the scientific method powerful enough to solve important real-world problems, and I can only get there by facing down hard problems.
Taking on Hard Problems
Why am I not taking on the hard problems, then? Why am I working on comfortable problems? Because I’m scared. I’m afraid to try something and find out that it doesn’t work. I feel like it will be a great black mark on my record. I’m afraid of failure, in other words.
What needs to be done here? Right now I’m uncertain about how good is my version of the scientific method. To get the most evidence the quickest, I need to release a working version of my scientific method and then find out what it can’t do.
Theoretically speaking, a “scientific method” is something that can take evidence and build alternative causal models from it (learning), differentiate between them to find out the correct model (research and experimentation), and finally use a given causal model to make inferences (problem-solving). I want a method that is as good as possible. Well, how do you judge a method’s “goodness”? For learning, you look at whether it can learn subtle differences, do so quickly, and learn from sparse evidence. For research, you look at whether it can quickly find experiments to distinguish between alternative models, given constraints like availability and precision of tools. For problem-solving, you look at how quickly it can help you solve problems.
For now, let’s ignore the speed benefits and just focus on correctness. Can my method at least get to the right answer?
Wait. You have to be more precise. Your aim in learning, say, isn’t to get a perfectly predictive causal model based the information in a textbook. That would be needed for a computer. You’re a human, so you can work with incompletely specified models.
So, what is the output of your method for learning? Is it an explicit fully-specified causal model? That is nearly impossible, I think. And wasteful. You would be repeating most of the information in the textbook.
Is it that you would remember the information in a causal manner inside your head? But understanding and memorizing things can be very time-consuming. Perhaps there is no other go. Maybe you have to memorize stuff.
What if I can store the high-level causal structure explicitly on paper and keep the individual causal functional equations in the textbook and refer to them as needed?
Basically, I’m limited by my typing speed. If I go the explicit route, I cannot build a causal model faster than I can type. And most of that would be just a costly repeat of the information in the textbook. A human can understand those English sentences effortlessly, whereas writing them in causal form would be a pain.
So, the question is where do I draw the limits? What do I choose to show explicitly in causal form and what do I choose to keep in the textbook in English?
I need to choose those parts of the domain that are modular - things that don’t depend too much on other things. I can just ignore their details and just view them in abstract form.
Finally, it depends on what problems I would need to solve. Remember, goals dictate abstractions. So, I need to figure out the key variables and work backwards.
I think I chose poorly when I decided to work on a high school biology textbook. Most of the exercise questions ask you to repeat what is in the textbook. There seems little application of the knowledge to solving problems.
Perhaps a high school physics textbook would be more helpful. I would have actual problems to test my models on. In fact, I’m not restricted to just one textbook. Pick textbooks from physics, economics, geography (?), math, and history (?). Further, don’t just take high school textbooks in these subjects, look for books from the lower grades too. It has to involve problem-solving somehow, otherwise I can’t test how good my model is.
Notes
One way: Vie against Conventional Thinking
At each point, I must know exactly where my method is deficient. I seem to believe deep down that a good scientific method can solve any problem more efficiently than conventional human thinking. For this not to be an empty boast, I need to figure out what my method can’t do that conventional thinking can, and eventually make it go beyond conventional limits.
Conventional thinking is the alternative that the scientific method has to beat. If you want to solve problems, you need to use a method of thinking. Most sane people go with either conventional thinking (common sense) or the scientific method. If we are to switch to the scientific method in most cases, then it must give better results. So, as I try to improve my model of the scientific method, I must constantly test if it can do better than orthodox methods.
And, mind you, conventional thinking is pretty damn good. The naive human brain is capable of effortlessly learning to ride a bicycle, something that we still have trouble programming a computer to do (I think).
One way is to focus where conventional thinking is weak. I mean, if conventional thinking is so good, instead of trying to replicate the functionality of the legacy code (our mind), we can just fill in for it where it comes up short.
Feedback Tools and Consequentialism
An empirical measurement forces you to be actually consequentialist! This subsumes all my ideas about how the feedback measure should be capable of failing you. When we deal with humans (or ourselves), we can go easy. We can let some things slide. It must be something you can’t negotiate with. Like reality. Or computers. Maybe that’s why these domains produce the most consequentialist thinkers. And that’s why Robert Greene says that mastery comes about when you work directly with reality.
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