Most games don’t even try to be reasonable about stuff like that, so it’s not really your fault. BG3 often enough fails that itself, but it clearly does it’s best to consider stuff like that.
Hope you have fun with the rest of the game, it’s amazing fun. And trying to really roleplay a bit and get into the character interactions is rewarded a lot both throughout the game and at the end, so keep at it.
From the perspective of a DM in a real DnD game, the enemy would simply not have an incentive to follow you. It wants to guard the forge, not kill you at any cost.
If you really wanted to, I’d have let you go that way, but I wouldn’t just let the creature run into suicide or abandon it’s only task for no reason, so I think BG3 does this fight really well. Especially because this is actually a fight where using the environment can make the fight much much easier and there are environmental clues before the fight that hint towards a weakness in the boss.
You should contextualise such claims.
So that vision impaired people or people with whatever other impairment can enjoy the content. The text can be read out by a screen reader.
Historical accuracy is not racism. Choosing to identify yourself based on the racist actions in your history is.
To drive it to the extreme, it would be like saying that Germany depicting Jews being gassed on their new flag isn’t racist, just historically accurate.
The point being made though was that the languages are well shown to be genuinely related through a common ancestral language from which they both deviated, just as have most languages in Europe and parts of the Near East. The connection is tangible and quite real, not something just based on some few similarities.
It’s not quite that simple. Crowdsourcing has many of the drawbacks that AI has too.
While it can have a higher reliability in detecting nonsensical inputs or inputs that it’s simply unfit in processing, that comes at an intrinsic cost in scalability. Some tasks can’t be effectively crowdsourced for, either because of volume or urgency.
Machine Learning systems learn to approximate decision making and thus can attempt at learning from crowdsourcing efforts. It is notable though that depending on the use case, model and training method, machine learning algorithms can potentially be better than the data it was trained on. Or much worse, it’s very fickle.
It is definitely still the case that crowdsourcing is a really important tool and oftentimes machine learning relies on it’s efforts. And it naturally can solve tasks that we don’t have a viable automated approach for.