Table 1

Alternative types of reasoning to evade the problem of induction

 Type of reasoning (with examples of key scholars) Shorthand description Explanation Bayesian evasion (Bayes, Hacking) Learning from experience This type of inductive inference agrees with Hume that we cannot predict the future perfectly, but that we can learn from our experiences reasonably well. This allows us to do more and better predictions. This type of reasoning can update current beliefs with information from frequent events (informing prior probabilities and likelihood ratios). However, because we can learn from a single event too, this approach is suited for the individual case scenario.8 Abduction (Peirce) Reasoning to the best explanation Abduction makes inferences by updating beliefs leading to the best explanation.28 Where Bayesian evasion takes prior probabilities as a given (at least as some argue), which may not be the case, abduction does not. It introduces the consideration of theory and mechanism in the act of inferring.29 Mechanistic/deterministic reasoning How things appear to work This type of reasoning makes an inference based on a mechanism. Illari et al 16 define a mechanism as consisting ‘of entities and activities organised in such a way that they are responsible for the phenomenon’. Falsification (Popper) Trial and error Popper30 agreed with Hume: we cannot say anything about the future, there are only theories that cannot even be proven. At best, we can only prove that they are wrong (falsifiable). This ‘anti-inductivist’ reasoning suggests to continue using a certain theory or practice and adjust if they fail. Precautionary principle In case of uncertainty about the future prevent harm The precautionary principle, often used in environmental decision making and occupational health, favours to take preventive action in the face of uncertainty when making an inference. It puts ‘the burden of proof to the proponents of an activity; exploring a wide range of alternatives to possibly harmful actions; and increasing public participation in decision making’.17 31 Means-to-ends reasoning Find ways to reach a goal This type of reasoning asks the question what ways are there to reach a certain wanted outcome and which of those ways would be the more efficient? Often used in clinical consultations to make sure that something happens whatever the circumstances. The inference remains uncertain but less so by using multiple means that will lead to the same outcome.32 Logic of care (Mol) Taking care while the uncertain future unfolds In The Logic of Care Annemarie Mol15 suggests that healthcare is more like a ‘practice’ than it is about making choices. This approach puts emphasis on the importance of taking good care for the patient and the prevention of neglect. Inferring is a process that unfolds over time, while addressing many factors on the way. Non-analytical reasoning (Gigerenzer, Stolper) Using intuition Non-analytical reasoning such as heuristics and gut feelings (combination of heuristics and emotions33) used to make inferences. These types of reasoning are considered fast, intuitive and automatic thought processes. Gigerenzer showed that non-analytical reasoning can in certain environments outperform analytical reasoning in psychological, biological, sociological and economic inference tasks.34
• Types of reasoning are not exclusive and may overlap.