Depends on the metric. Humans who up-voted that material clearly thought it was worth.
The problem is distinguishing the various reasons people think something is worth and using the right context.
That requires a lot of intelligence.
The fact that modern language models are able to model sentiment and sarcasm as well as they do is a remarkable achievement.
Sure there is a lot of work to be done to improve that, especially at scale and in products where humans are expecting something more than a good statistical "success rate", but they actually expect the precision level they are used from professionally curated human sources.
The problem is distinguishing the various reasons people think something is worth and using the right context.
That requires a lot of intelligence.
The fact that modern language models are able to model sentiment and sarcasm as well as they do is a remarkable achievement.
Sure there is a lot of work to be done to improve that, especially at scale and in products where humans are expecting something more than a good statistical "success rate", but they actually expect the precision level they are used from professionally curated human sources.