Thought experiments in the context of "Scenario"

Philosophical methodology encompasses the methods used to philosophize and the study of these methods. Methods of philosophy are procedures for conducting research, creating new theories, and selecting between competing theories. In addition to the description of methods, philosophical methodology also compares and evaluates them.

Philosophers have employed a great variety of methods. Methodological skepticism tries to find principles that cannot be doubted. The geometrical method deduces theorems from self-evident axioms. The phenomenological method describes first-person experience. Verificationists study the conditions of empirical verification of sentences to determine their meaning. Conceptual analysis decomposes concepts into fundamental constituents. Common-sense philosophers use widely held beliefs as their starting point of inquiry, whereas ordinary language philosophers extract philosophical insights from ordinary language. Intuition-based methods, like thought experiments, rely on non-inferential impressions. The method of reflective equilibrium seeks coherence among beliefs, while the pragmatist method assesses theories by their practical consequences. The transcendental method studies the conditions without which an entity could not exist. Experimental philosophers use empirical methods.

In the philosophy of mind, the "hard problem" of consciousness is to explain why and how humans (and other organisms) have qualia, phenomenal consciousness, or subjective experience. It is contrasted with the "easy problems" of explaining why and how physical systems give a human being the ability to discriminate, to integrate information, and to perform behavioural functions such as watching, listening, speaking (including generating an utterance that appears to refer to personal behaviour or belief), and so forth. The easy problems are amenable to functional explanation—that is, explanations that are mechanistic or behavioural—since each physical system can be explained purely by reference to the "structure and dynamics" that underpin the phenomenon.

Proponents of the hard problem propose that it is categorically different from the easy problems since no mechanistic or behavioural explanation could explain the character of an experience, not even in principle. Even after all the relevant functional facts are explicated, they argue, there will still remain a further question: "why is the performance of these functions accompanied by experience?" To bolster their case, proponents of the hard problem frequently turn to various philosophical thought experiments, involving philosophical zombies, or inverted qualia, or the ineffability of colour experiences, or the unknowability of foreign states of consciousness, such as the experience of being a bat.

In philosophy, the brain in a vat (BIV) is a scenario used in a variety of thought experiments intended to draw out certain features of human conceptions of knowledge, reality, truth, mind, consciousness, and meaning. Gilbert Harman conceived the scenario, which Hilary Putnam turned into a modernized version of René Descartes's evil demon thought experiment. Following many science fiction stories, the scenario involves a mad scientist who might remove a person's brain from the body, suspend it in a vat of life-sustaining liquid, and connect its neurons by wires to a supercomputer that would provide it with electrical impulses identical to those a brain normally receives. According to such stories, the computer would then be simulating reality (including appropriate responses to the brain's own output) and the "disembodied" brain would continue to have perfectly normal conscious experiences, like those of a person with an embodied brain, without these being related to objects or events in the real world. According to Putnam, the thought of "being a brain-in-a-vat" is either false or meaningless.

Considered a cornerstone of semantic externalism, the argument produced significant literature. The Matrix franchise and other fictional works (below) are considered inspired by Putnam's argument.

In computer science, an abstract machine is a theoretical model that allows for a detailed and precise analysis of how a computer system functions. It is similar to a mathematical function in that it receives inputs and produces outputs based on predefined rules. Abstract machines vary from literal machines in that they are expected to perform correctly and independently of hardware. Abstract machines are "machines" because they allow step-by-step execution of programs; they are "abstract" because they ignore many aspects of actual (hardware) machines. A typical abstract machine consists of a definition in terms of input, output, and the set of allowable operations used to turn the former into the latter. They can be used for purely theoretical reasons as well as models for real-world computer systems. In the theory of computation, abstract machines are often used in thought experiments regarding computability or to analyse the complexity of algorithms. This use of abstract machines is fundamental to the field of computational complexity theory, such as with finite state machines, Mealy machines, push-down automata, and Turing machines.