Unfortunately I've only experienced this three times in my life; typically around major life events (once when starting a new job in a new industry, once when quitting that job to make my own stuff, and once in grade school: the summer between 10th and 11th grade, for some reason). I look forward to seeing more research, and hopefully one day can apply these learnings to manually trigger this intense focus and motivation.
As i get older, this happens less and less – which is a massive shame.
I wanted to understand whether there was any good evidence as to what intrinsic motivation is and how i might be able to cultivate it in my adult life. To do this, i did a massive deep dive of the scientific literature surrounding intrinsic motivation. This is the outcome of that research.
Some games are made to burn time, like Thumper.
Some games are made to burn you neurons like Baba is You.
Minecraft has 2 modes. Creative and Zombie. Both equally powerful incentives.
I try to keep the plasticity of my brain. Not to let it crust and crumble like Play Doh left outside the tub.
One of my other favorite theories is HEXACO. And personality does play into intrinsic motivation, to some extent.
Disclaimer: I skimmed the article.
Fun autonomy hacks:
1. Reframe the narrative. For example, when I studied CS at school, I didn't study CS. I studied how to learn as fast as possible. I happened to have studied CS.
2. Listen to Spotify to get into a solo task. I usually turn it down if I happen to get focused.
Also a note: intrinsic motivation is tough when you're sleep deprived. I've had moments where I was motivated and sleep deprived but they often don't coincide.
This is all to say that stuff like this go onto a fundamental layer of physical health. Something I dind't quite get when I was younger.
That's an example
As for the Spotify example. I just like listening to my playlists, every task becomes more chill. Also, I like working on a Mac more than a Windows laptop. I've had one company restricting my choice there to Windows. Me sort of hacking their company policies such that I could work on a Mac made me feel a lot better.
People with high intrinsic motivation and agency will rule the world of tomorrow, weilding AI to acheive their personal visions. Everyone else will be weilded by AI.
You may well be right. Interesting to think about the relationship between agency & intrinsic motivation...
To allow an embodied agent to perform actions within an environment that would generally be considered positive, without the definition of an objective function.
To break that down, to be embodied in this case is to act, sense and have some internal model that can be adapted, all operating within an environment that can be considered external to the agent.
An objective function is where there is some external push towards optimality that requires knowledge of the sensors, actuators, environment, etc. A good test for whether you accidentally baked in system knowledge is if you change the rules considerably and the agent will not operate.
Whether or not an agent acts positively can itself be measured by an environment specific objective function. A properly operating intrinsically motivated agent may perform well on some metrics, i.e. long time lived, reduced search time, etc.
Why do you want an intrinsically motivated agent? Almost all reward/objective functions are somewhat flawed, even if the problem is simple. I am reminded of a group training a robot to walk fast, measured by speed over time with a cut off. Simple enough? Well, they reviewed the trained agent and they immediately feel to the ground to be reset far away. In another test, the agents would purposely break the simulation environment, causing the agents to glitch and be launched far. One thing to note is that in each of those scenarios, the agent optimised for the reward, but made themselves "useless" after doing so.
For AI I have found Empowerment an interesting solution to intrinsic motivation [1]. Essentially agents choose actions to "keep their options open", and try to avoid actions that would reduce the action state space. The actual environment itself is not encoded into the algorithm and the state spaces are arbitrary and could be replaced with any symbol. As a result, you can make large changes to the environment and use the same motivation algorithm.