That requires a substantial amount of hard work but unlikely results in a measurable amount of success. Certainly one less than would be if the proper tools were used.
And I do agree with you that it is not the only factor. But this is why I differentiate cause and correlation. And the disagreement is likely to how we are using those terms. I am using "cause" in the colloquial sense (because context from above) of how most people do not see multivariate equations, but single factor (which is an unfortunate thing) ie. "cause and effect" (but we both know better). I am using "correlation" in the more rigorous manner meaning "related to; a statistical variable; or to be in association with".
And going back to your RL example, I think you mention one part which proves my point as well.
> the exploration/exploitation strategy
You may notice that many learning algorithms have a substantial amount of failure. After all, it is the failure that leads to success. BUT a key point is that it is not the effort put into the attempt that led to success, it is the adaptation of a new strategy after recognizing the failure. You could just as easily never visited that attempt method and thus your efforts would lead to a higher success/work factor. You could also never change strategies and your efforts would result in a substantially lower success/work factor. More explicitly "hard work" is a variable that is coupled with "strategy", and the value of "hard work" can be astronomically high but the value for success can be zero. And for this reason we say it is not "the cause" but rather "a factor" or "correlates with".
Also, as mentioned in a grandchild to my post, this is a saying which I gladly will admit does not cover the entire scope of what factors lead to success. Even the unpacking of implicit information cannot do that, as a full description of the path to success is rather cumbersome.
We could contrive an example whereby "working hard" allowed you to "create more widgets in less time than anyone else" and so you receive a promotion (success). But even then we know that your success isn't from just "working hard", but is instead from the result of doing so. Given the context of this thread, I think we can agree that "creating the most widgets in the least time" can be done without "working hard".
I would argue pointing to "hard work" as a cause of success is confusing how a causal factor was reached with the factor itself.
Not true, hard work is a cause of success, just not the only cause. Luck (opportunity) is a factor, but a much more unreliable one at that. Genetics is also a factor (intelligence, passion, curiosity, playfulness).
I like to see this problem from the point of view of Reinforcement Learning - an agent playing a game in an environment, having to maximise rewards - which is the definition of success. The degree of success depends on many things, including:
- the environment (how complex it is, how many potential rewards it has for the agent)
- the internal structure of the agent (its ability to learn and perceive)
- bodily affordances (what the body can do)
- the exploration/exploitation strategy (will it try something new when it already has a strategy that is sort of ok)
- the amount of time it has to learn (life experience)
- if the agent exists as part of a multi-agent environment, then the strategies of the other agents count (cooperation/betrayal, tit for tat, forgiveness).
So there are many causes of success.