There have always been lower quality work and journals that are inherently given lower weight in the scientific community. Many of these lower quality papers just aren’t considered by working scientists. It’s a bit like email… once you start seeing a significant amount of spam, you just get used to ignoring it. This is a feature of the system. Scientific consensus can change over time, but it takes a lot of evidence to get there. But some papers get more weight than others.
For me, there are two real issues - first, public trust in science. When the public thinks that 14% or “science” is fake, they are likely to discount all scientific findings, regardless of source. This can be dangerous, especially for a public who is already distrustful of science/academia in general. So, instead of looking at results with a critical eye, the danger is that a large fraction of the public will just ignore all results.
The second issue is in polluting AI training. When you feed extra garbage into a system, you’ll get garbage out of the system. As LLMs get more specialized having high quality inputs for training is critically important. A contributing force here is that lower tier journals (those most susceptible to faked data), are also the most likely to make the full text of papers widely available. So, the easiest data to get for training is also the most likely to have faked data.