You can see that the two trends, that is, suicides and US spending on science and technology over time have very similar trends. If you were to plot these data together (say between 1999 and 2009), you would even see a linear association on regression. Does that mean that increased spending lead to suicides or if you reduce spending on science and technology, suicide rates would come down, :-)? Can you think what must be going on here?
So just because X and Y are correlated with each other does not necessarily imply that X is a cause of Y, nor Y is a cause of X. Had that been the case, you would be able to argue for reduction in the US spending towards science and technology to reduce suicide rates. But why cannot we argue when we see this sort of correlations or what makes these correlations unfit for any use? Well, if you see correlations such as this, you need to ask yourself, why do we get to see these correlations? Is it possible that there is as yet a third variable that can account for both the trends and once we "control" for that third variable that is associated both X and Y, this apparent "association" will disappear? What could be that variable in this case? What is your theory? Could it be that societal complexity and technological advancement that has resulted from increased funding have resulted in dissatisfaction among certain section of people who decide to commit suicide and the pace at which this happens matches the pace of sci/tech funding? Can we study them? How can we study them? What do we need to know?
Here's another issue. Consider the following figure. This figure has come from a study conducted by Xie et al (2014) where they studied morbidity and mortality from heart disease (ischaemic heart disease) in Beijing, China \cite{xie2014relationship}. They studied aggregated measurements of air quality in China and aggregated number of people who died or were admitted to the hospital with ischaemic heart disease in that city in 2014.