This is a fascinating problem that affects a lot of scientific modeling (in fact, I'll be talking about this in the second part of my series on gun violence research) — the more specific and accurate your predictions, the less reliable they sometimes become. Think about climate science. When you read the IPCC reports, what you see are predictions about what is likely to happen on a global basis, and those predictions come in the form of a range of possible outcomes. Results like that are reliable — i.e, they've matched up with observed changes. But they aren't super accurate — i.e., they don't tell you exactly what will happen, and they generally don't tell you much about what might happen in your city or your state. We have tools that can increase the specificity and accuracy, but those same tools also seem to reduce the reliability of the outcomes. At The Curious Wavefunction, Ashutosh Jogalekar explains the problem in more detail
and talks about how it affects scientist's ability to give politicians and the public the kind of absolute, detailed, specific answers they really want.