Bechtel - Philosophy of science Flashcards
Demarcation of science: Falsificationism
Logical Positivism
Meaningful statements must be either analytic (true by definition) or empirically verifiable through observation or experience. “Logical” reflects the role of modern symbolic logic
Context of Discovery
Refers to the phase in which scientific hypotheses are developed, even if they may not strictly adhere to logical thinking. Scientific ideas may arise from non-logical processes such as intuition or creative insights
Context of Justification
Involves the rational assessment of scientific hypotheses, focusing on the logical relation between the hypothesis and the evidence supporting it. Aims to demonstrate the truth of scientific theories based on empirical evidence and logical reasoning
Verifiability Theory of Meaning
“The meaning of a sentence was the set of conditions that would show that the sentence was true.” Asserts that sentences, not individual words, could be true or false, and the meaning of words had to be analyzed in terms of their roles in sentences. Positivists had a bias towards physically observable phenomena in observation sentences
Analytic Statements
Articulate the meaning of one sentence in terms of another sentence and do not depend on experience, hence cannot be refuted by experience
Verifiability Theory Correlation to How Machines Think
Turing test: acceptance of a machine as thinking when indistinguishable from a human. Behaviorist viewpoint emphasizes observable actions over unobservable mental processes
Deductive-Nomological Model of Explanation and Hypothetico-Deductive Model of Theory Development
Explanation requires deriving events from general laws and known facts. Both explanation and prediction share a similar logical structure, differing in timing. HD-model involves problem identification, hypothesis formation, testing, and confirmation/disconfirmation
Modal Logic
Formal logic dealing with modalities like possibility, necessity, and impossibility. Uses operators such as “possible” and “necessary”
Symbolic Logic
Represents and manipulates logical expressions using symbols. Examines the formal structure of arguments and logical inference validity
The Raven Paradox
Highlights logical equivalence between “All ravens are black” and “All non-black things are non-ravens.” Testing involves observing black ravens and non-black non-ravens, revealing a counterintuitive aspect of logical equivalence
The Axiomatic Account of Theories
Views theory as a network of statements from which specific laws can be derived. Theories are seen as axiomatic structures, with particular laws derived from assumptions and postulates
Theory Reduction
Unifies science by deriving principles of one science from another
Summary of Logical Positivism (sensory experience)
Grounded in sensory experience, proposing a theory of meaning linking scientific discourse to sensory experience.
Provides an account of explanation using deduction and a theory of confirmation.
Suggests unification of scientific laws into axiomatic structures. Impact on psychology: embraced verificationist theory of meaning and influenced behaviorist theories.
Application to cognitive science
Explores human concepts and categorization processes, with typicality judgments seen as grounding concepts in observation
Problem of induction
The problem of induction questions our reasons for believing that the future will resemble the past
Positivists (Popper)
Positivists acknowledged the problem of induction but believed positive tests of a hypothesis could still lend support to it
Modus tollens (Popper)
In modus tollens, if a hypothesis implies a certain prediction, and if that prediction is found to be false, then the hypothesis itself can be inferred to be false. Scientists should aim to falsify hypotheses rather than confirm them
Corroboration (Popper)
Popper’s term for supporting evidence or confirmation of a scientific theory. It signifies a rejection of the Positivists’ distinction between meaningful and meaningless discourse
Demarcation
The process of distinguishing between scientific and non-scientific discourse. Popper’s demarcation criterion involves assessing the risk that true scientific theories face of being wrong
Riskiness of Theories (Popper)
Popper suggests that scientific theories gain strength from their ability to forbid certain outcomes. The more events the theory rules out, the more powerful and informative it is considered
Testability (Popper)
Popper emphasizes the importance of scientific theories being testable through critical experiments where it is clear what evidence would count against the theory
Artificial intelligence (Popper and criterion of demarcation)
AI simulations failing to accommodate existing data suggest they should be rejected based on Popper’s criteria. The difficulty lies in creating theories that can effectively account for empirical evidence
Sternberg (relation to cogsci)
Sternberg’s paradigm exemplifies how competing theories can be empirically tested against each other. Sternberg’s experiment with memory access models allowed for rejecting models that did not fit reaction time data
