This is cute and all but there is a sniff test here. Could you rephrase what you're turning into pseudocode back into prose, specifically into a memo, and have

This is cute and all but there is a sniff test here. Could you rephrase what you're turning into pseudocode back into prose, specifically into a memo, and have it still sound concrete or meaningful? One thing that might jump out if you do that is that there's no mention of historical context or a competitive landscape. What are potential substitutes and comparable products that potential users use to do something that Karma could do a better job of solving? What is the history of that pain point? You touch upon this where you define what the boundaries are of whether karma can definitely help, and the enumeration of pains that you feel. This is my humble gut opinion, but I get the sense that there is too much ground being covered there. Solutions to the problems of social isolation, social injustice in the workplace or the world at large, or lack of academic progression are pretty challenging unsolved spaces in and of themselves, and there are some pretty rough economic structures and systems in place that make things harder there. I'm almost certain you wouldn't solve any of those problems by trying to solve all of them at once, but I'm skeptical that you could solve any individual one in and of itself because even the individual ones are so challenging and work against gravitational forces. There are many algorithms out there -- does this one produce useful work? And if it does, does it do so while effectively minimizing time-space complexity and utilizing data locality to achieve as much useful productivity as possible? If you don't get a satisfactory answer to those questions, I think the real algorithm to help you find a problem worth solving is one that isn't a complete stretch of an analogy. It's finding subproblems, which is a crucial part of using recursion. Keep digging into smaller and smaller problems until you find something that is small enough to trivially solve that you truly do solve it, but it's aggregable enough to start putting together into a larger and larger solution. Otherwise, you might risk building a solution in search of a problem.