Past exam of the philosophy of science supplementary subject of the University of Oxford / 2018 / 6 / a / Solution

Falsificationism gives an attractive account of one aspect of scientific progress: replace protected dogma by conjectures that make risky claims and expose them to serious tests. From $T\wedge A\Rightarrow E$ and an accepted $\neg E$, deduction rules out the conjunction. A theory that accommodates every possible outcome supplies less opportunity to learn from error. Karl Popper emphasizes exposure to refutation and warns against treating any convenient supporting instance as a demanding test.^[ref]

This captures why a successful novel prediction can be more informative than retrospectively adjusting a model to its original fitting data. It also helps articulate a progressive replacement: the new account should address the earlier successes and the discrepancy, while exposing itself to further independent tests. Merely adding a freely adjustable parameter after each failure need not improve knowledge.

The Duhem problem limits the simple account. A failed prediction is a failure of a package containing initial conditions, instrument assumptions and background theory. It is not a deductive identification of the particular target theory as false. Revising an auxiliary hypothesis can be rational when independently supported, but an unconstrained rescue can frustrate testing. Methodological judgement is needed to distinguish them; the bare logic of falsifiability does not do all the work.

There is also a positive-warrant problem. A theory's survival of past tests does not deductively entail that it will succeed tomorrow. Calling it corroborated records its demanding test history, but does not by itself solve the problem of induction. Nor does the elimination of one theory guarantee that a chosen rival is closer to the truth: many alternatives may remain, and progress can involve improved measurement, new concepts or increased explanatory scope as well as refutation.

A convincing form of falsificationism is therefore a critical methodology within a broader account. It explains the value of error detection, risky commitments and resistance to immunizing manoeuvres. It becomes less convincing as a complete logical algorithm for identifying falsified theories, ranking every successor or deriving confidence about future performance. A more adequate account combines severe criticism with independent checks on assumptions, comparative success and explicit acknowledgement of fallible inference.