Past exam of the philosophy of science supplementary subject of the University of Oxford / 2018 / 1

Necessary connections would matter if they provided an independently knowable bridge from observed cases to unobserved ones. Their mere existence would not provide that bridge. In David Hume's problem of induction, observations of past regularities do not deductively entail that the same regularities continue. Appealing to the past reliability of inductive reasoning uses the very kind of inference whose justification is at issue.^[ref]

Suppose, for example, that a particular causal power necessarily makes an isolated system respond in a certain way. If we knew independently that the power exists, that it remains present and that the relevant conditions obtain, a prediction could follow by deduction. But repeated agreement with the prediction does not itself establish those premises without further inductive reasoning. The proposal can relocate the epistemic burden rather than discharge it. A guarantee that every cause has some necessary effect also fails to identify which cause and effect our observations instantiate.

This separates metaphysical necessity from access to it. A scientist might posit causal powers because they unify otherwise separate regularities, explain counterfactual responses and guide successful interventions. An experimentally supported molecular mechanism can make the behaviour of a material intelligible across varied conditions. That supplies a comparative scientific reason to prefer a structured causal model over a bare catalogue. It does not demonstrate that the model captures a connection whose violation is impossible in every relevant world, or that its scope extends beyond the tested domain.

Hume's discussion of necessary connection challenges the idea that inspecting one cause discloses such a connection directly; repeated experience instead explains our expectation.^[ref] A defender of causal powers can reject that account, but must explain both the powers and how we know them. Mathematical necessity in a model is insufficient: the deduction is conditional on the model applying to the physical system.

The defensible conclusion is conditional. Independently warranted knowledge of stable necessary connections could justify particular projections. Simply adding them to one's account of nature does not solve the problem of induction. Scientific support for a causal account can remain strong, comparative and fallible without becoming a noncircular deductive foundation for every future inference.

A scientist should take a sceptical scenario seriously when it exposes a credible way in which the evidence could be misleading and there is a useful way to investigate that possibility. A shared instrument offset, a software error copied across analyses, or an unrecognized background signal can survive the appearance of repeated agreement. Such possibilities motivate independent calibration, changes of apparatus and analysis, and deliberately varied experiments. Mere repetition using the same error-prone chain is weaker than agreement among genuinely independent tests.

Consider two detectors that report the same departure from a predicted signal. Their agreement supports a new effect less strongly if both use the same calibration source and processing program. A proposed common failure is not defeated merely by observing that both detectors agree. An independently constructed detector, measurements at several settings, or analysis of deliberately hidden test signals can make the failure scenario and the target hypothesis predict different outcomes. Here scientific doubt generates a better test rather than an unlimited demand for reassurance.

A radically global sceptical scenario is different. If it is stipulated to reproduce every possible observation and experiment, it supplies no empirical contrast to investigate. That does not make it logically contradictory or prove it false. It limits its role in choosing among scientific models. A researcher cannot improve a detector by an experiment whose outcome is stipulated to be identical whether all experience is globally deceptive or not.

The line is not simply between imaginable and unimaginable errors. Limited time and resources require attention to plausibility, consequences and discriminating power. A low-probability fault may deserve a check when it could invalidate an entire result and is inexpensive to test. Conversely, inventing an unconstrained auxiliary hypothesis after every contrary result can insulate a favoured theory from criticism. The Duhem problem explains why a failed prediction does not isolate the guilty assumption; it does not make every rescue equally well evidenced.

A scientist can therefore combine fallibilism with justified confidence. Results can be warranted by calibration, independent methods and successful interventions without excluding every logically possible deception. Productive scientific scepticism identifies concrete vulnerabilities and seeks evidence against them. It neither assumes that every appearance is reliable nor treats the absence of Cartesian certainty as the absence of scientific knowledge.