Can we trust scientific theories that can never be proven or observed?
In short: For decades, the gold standard of science was falsifiability: the ability to prove a theory wrong through testing. But how do we evaluate modern ideas like string theory or the multiverse, which make no empirically verifiable predictions and remain forever beyond our reach?
The traditional scientific benchmark, championed by thinkers like Karl Popper and David Hume, relies on empirical testing. This 'old school' approach, sometimes playfully called the 'Popperazzi' by modern philosophers, demands that a theory be falsifiable to be considered scientific. However, modern physics faces a crisis of observability. Theories such as string theory and the multiverse lack any way to be empirically verified, leading some to question if they have drifted into the realm of metaphysics or even 'quasi-science.'
To navigate this, scientists are increasingly turning to the 18th-century mathematical foundations of Reverend Thomas Bayes. Rather than seeking absolute proof—which is impossible for a theory of the universe—researchers use statistical inference to calculate the likelihood of a theory being correct. By applying Bayesian logic, it is possible to increase confidence in a theory through non-empirical support, provided certain conditions are met, even in the absence of direct physical evidence.
Yet, this shift toward probability is not without controversy. While cosmologists use speculation to drive progress, the lack of data can lead to untrustworthy paths. For instance, the 'anthropic principle' is often criticized as speculation driven by a lack of solutions rather than evidence. Similarly, while 'eternal inflation' provides a theoretical framework for a multiverse, the multiverse itself is by construction causally disconnected from us. We can never see it, and chasing such unchaseable phenomena risks moving away from the data-driven essence of physics.
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Sources
- Summary by Intellect · source: Should We Trust a Theory? - Professor Joseph Silk FRS
- Also: Should We Trust a Theory?
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