Its learning data is entirely human made, there is no originality in its data that was not produced or made by humans.
Before we even jump to "creative solutions" we need to go through 2 steps first, defining the REAL core issue of the problem and collect multi-side data. IMO AI is better than human for this.
So what if all data came from humans, if the system issue that needs to be solved IS human issues to begin with? What matters here is if the data is limited by one person's personal position or not.
In order to really define the underlying issues, we need data from multiple sides, not just one side. And AI provides those multi-side data faster.
AI also defines the root of the issue better than average human btw. At least from what I've observed this is the case. Humans are more likely to be limited by personal position when they try to define the core of an issue. AI is less likely so.
Case to the point, we had this discussion about piracy before. Your stance was that piracy happened because corporate greed and the lack of quality, which is an personal ideology based stance. So if I ask you how to increase single player game market size and generate more revenue in the market you'll probably just answer "make better games so people don't pirate!" like last time. Because this is the opinion from your personal position as a human.
But the problem is, "not wanting to make better games" is
not the core issue. No one in this world wants to make a bad game lol. So this human "discussion" goes nowhere nor it successfully defined the core issue, let alone
solving it.
At least from AI I can quickly learn multiple reasons on why people don't want to pay, not just your reasons. Then I can have it list several solutions that other studios have tried and proven to reduce piracy and increase revenue.
Of course what other companies have tried and proven to work doesn't solve this issue completely, it is a known solutions from other humans like you said. And known solutions still have limitations. But at least it's a starting point to work on a functional strategy. Then subsequent improvement to those strategy can be applied once the strategy is deployed in practice.
That's also why I said human verification on their experience is the second step, not first. One can use AI to define the core issue and find the first step strategy and use it as a base, collect real human feedback then improve strategy from there. But human feedback is more of a second step thing.
Ultimately, I don't think I dismissed human discussions completely, I just find it less efficient than AI in
many cases.