I don't think Hume's work suggests that causality isn't 'real' but that we can't prove causation using inductive methods. This isn't a problem unless our measure of 'truth' is proving some causal effect to be true. The solution is to pretend our models of causation are correct, run them and compare the results to observation. We never 'prove' the causal effect, but we judge its validity by how well it can predict future observations.
In my view the 'real' problem we currently have is that we cannot test hypothesis in isolation (Duhem-Quine thesis). Thus we rely on heuristics like "scientific consensus" to judge whether the hypothesis that make up a field are gaining predictive power or not. The solution to all these problems is to use the Lakatosian Method of Scientific Research Programmes to track a field's progress over time. Anything less than this just devolves into Kuhnian paradigms, which is basically a popularity contest to determine 'valid' scientific methods.
I think this 'real' problem can explain all the failures of modern science: the replication crisis, abuse of statistical methods, funding influencing results.
In my view the 'real' problem we currently have is that we cannot test hypothesis in isolation (Duhem-Quine thesis). Thus we rely on heuristics like "scientific consensus" to judge whether the hypothesis that make up a field are gaining predictive power or not. The solution to all these problems is to use the Lakatosian Method of Scientific Research Programmes to track a field's progress over time. Anything less than this just devolves into Kuhnian paradigms, which is basically a popularity contest to determine 'valid' scientific methods.
I think this 'real' problem can explain all the failures of modern science: the replication crisis, abuse of statistical methods, funding influencing results.