It’s a good question. I tend to treat patterns as clues that point toward underlying structure, but I also remind myself that our models are abstractions. The data can be noisy, the sample biased, and our algorithms can impose patterns that aren’t there. So I see patterns as useful guides, but I always keep a margin for uncertainty and try to validate them with independent evidence.