Considers that intuitive predictions follow a judgmental heuristic-representativeness. By this heuristic, people predict the outcome that appears most representative of the evidence. Consequently, intuitive predictions are insensitive to the reliability of the evidence or to the prior probability of the outcome, in violation of the logic of statistical prediction. The hypothesis that people predict by representativeness was supported in a series of studies with both naive and sophisticated university students. The ranking of outcomes by likelihood coincided with the ranking by (...) representativeness, and Ss erroneously predicted rare events and extreme values if these happened to be representative. The experience of unjustified confidence in predictions and the prevalence of fallacious intuitions concerning statistical regression are traced to the representativeness heuristic. (shrink)

This article described three heuristics that are employed in making judgements under uncertainty: representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value (...) is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty. (shrink)

Described by the philosopher A.J. Ayer as a work of 'great originality and power', this book revolutionized contemporary thinking on science and knowledge. Ideas such as the now legendary doctrine of 'falsificationism' electrified the scientific community, influencing even working scientists, as well as post-war philosophy. This astonishing work ranks alongside The Open Society and Its Enemies as one of Popper's most enduring books and contains insights and arguments that demand to be read to this day.

It is often claimed that there can be no such thing as a logic of scientific discovery, but only a logic of verification. By 'logic of discovery' is usually meant a normative theory of discovery processes. The claim that such a normative theory is impossible is shown to be incorrect; and two examples are provided of domains where formal processes of varying efficacy for discovering lawfulness can be constructed and compared. The analysis shows how one can treat operationally and formally (...) phenomena that have usually been dismissed with fuzzy labels like 'intuition' and 'creativity'. (shrink)

In this 1958 book, Professor Hanson turns to an equally important but comparatively neglected subject, the philosophical aspects of research and discovery.

Contributors; Preface; Introduction; Part I. Instruments in Experiments: 1. Scientific instruments: models of brass and aids to discovery; 2. Glass works: Newton’s prisms and the uses of experiment; 3. A viol of water or a wedge of glass; Part II. Experiment and Argument: 4. Galileo’s experimental discourse; 5. Fresnel, Poisson and the white spot: the role of successful predictions in the acceptance of scientific theories; 6. The rhetoric of experiment; Part III. Representing and Realising: 7. ’Magnetic curves’ and the magnetic (...) field: experimentation and representation in the history of a theory; 8. Artificial clouds, real particles; 9. Living in the material world; 10. Justification and experimentation; Part IV. The Constituency of Experiment: 11. Extraordinary experiment: electricity and the creation of life in Victorian England; 12. Why did Britain join CERN?; Part V. Hallmarks of Experiment: 13. From Kwajalein to Armageddon? Testing and the social construction of missile accuracy; 14. The epistemology of experiment; Select bibliography; Name index; Subject index. (shrink)

Hans Krebs' discovery, in 1932, of the urea cycle was a major event in biochemistry. This article describes a program, KEKADA, which models the heuristics Hans Krebs used in this discovery. KEKADA reacts to surprises, formulates explanations, and carries out experiments in the same manner as the evidence in the form of laboratory notebooks and interviews indicates Hans Krebs did. Furthermore, we answer a number of questions about the nature of the heuristics used by Krebs, in particular: How domain‐specific are (...) the heuristics? To what extent are they idiosyncratic to Krebs? To what extent do they represent general strategies of problem‐solving search?The relative generality of KEKADA allows us to view the control structure of KEKADA and its domain‐independent heuristics as a model of scientific experimentation that should apply over a broad domain. (shrink)

The empiricism of eighteenth-century experimental science meant that the development of scientific instruments influenced the formulation of new concepts; a two-way process for new theory also affected instrument design. This relationship between concept and instrumentation will be examined by tracing the development of electrical instruments and theory during this period. The different functions fulfilled by these devices will also be discussed. Empiricism was especially important in such a new field of research as electricity, for it gave rise to phenomena that (...) could not have been predicted by theory alone. However, the interpretation of these phenomena, and what the natural philosopher thought he observed, were often unconsciously determined by current ideas and attitudes; the interaction between instrumentally induced phenomena and observation was more complex than was realized at the time. The shortcomings of this empirical approach will be discussed. In the case of electricity this became increasingly apparent during the latter part of the century. The many discoveries had to be placed in a unifying framework before new advances could be made. Instruments, however, continued to play an important role in scientific progress, for they made visible what was hidden in nature. (shrink)

Can the output of human cognition be predicted from the assumption that it is an optimal response to the information-processing demands of the environment? A methodology called rational analysis is described for deriving predictions about cognitive phenomena using optimization assumptions. The predictions flow from the statistical structure of the environment and not the assumed structure of the mind. Bayesian inference is used, assuming that people start with a weak prior model of the world which they integrate with experience to develop (...) stronger models of specific aspects of the world. Cognitive performance maximizes the difference between the expected gain and cost of mental effort. Memory performance can be predicted on the assumption that retrieval seeks a maximal trade-off between the probability of finding the relevant memories and the effort required to do so; in categorization performance there is a similar trade-off between accuracy in predicting object features and the cost of hypothesis formation; in casual inference the trade-off is between accuracy in predicting future events and the cost of hypothesis formation; and in problem solving it is between the probability of achieving goals and the cost of both external and mental problem-solving search. The implemention of these rational prescriptions in neurally plausible architecture is also discussed. (shrink)

ONE Introduction The history of psychology in the twentieth century is a story of the divorce and remarriage of psychology and philosophy. ...