Something the best data scientist I ever worked with was adamant about... there is almost never an inherent "speed bump" at 0. If error bounds expand on both sides of 0, we have no idea if the true sign is positive or negative. There is no "directional" read in that case. There are some areas where 0 has a special meaning, but that's rare and the cause of that needs to be understood before assuming that's the case. Everywhere else, 0 is just another point on the number line.

> the error bars would be so large as to make drawing conclusions from these numbers seem pointless

That is often the case, and being truly data based requires acknowledging that. We can then act based on other data, or admit that we're falling back to intuition and abandoning data based decision making for now.